diff --git a/_pkgdown.yml b/_pkgdown.yml new file mode 100644 index 0000000..9dc3995 --- /dev/null +++ b/_pkgdown.yml @@ -0,0 +1,35 @@ +url: https://aubreyodom.github.io/legato-docs/ + +template: + bootstrap: 5 + bootswatch: cosmo + +reference: + - title: "Your title here" + desc: "Description here" + contents: + - this_function + +navbar: + bg: dark + title: "LegATo" + left: + - text: "Home" + href: index.html + - text: "Tutorial" + href: articles/LegATo_vignette.html + - text: "Function Reference" + href: reference/index.html + - text: "Package News" + href: news/index.html + right: + - icon: fa-github + href: https://github.com/aubreyodom/legato + +authors: + footer: + roles: [cre] + text: "Site created by" + sidebar: + roles: [aut, cre, ctb, csl, art] + \ No newline at end of file diff --git a/docs/404.html b/docs/404.html new file mode 100644 index 0000000..93d04d1 --- /dev/null +++ b/docs/404.html @@ -0,0 +1,108 @@ + + +
+ + + + +YEAR: 2024 +COPYRIGHT HOLDER: LegATo authors ++ +
Copyright (c) 2024 LegATo authors
+Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
+The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+LegATo_vignette.Rmd
LegATo is a suite of open-source software tools for longitudinal +microbiome analysis that is extendable to several different study forms +with optimal ease-of-use for researchers. Microbiome time-series data +presents distinct challenges including complex covariate dependencies +and variety of longitudinal study designs. This toolkit will allow +researchers to determine which microbial taxa are affected over time by +perturbations such as onset of disease or lifestyle choices, and to +predict the effects of these perturbations over time, including changes +in composition or stability of commensal bacteria.
+LegATo integrates visualization, modeling and testing procedures. It +will be supplemented by hierarchical clustering tools and multivariate +generalized estimating equations (JGEEs) to adjust for the compositional +nature of microbiome data.
+## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
+## ✔ dplyr 1.1.4 ✔ readr 2.1.5
+## ✔ forcats 1.0.0 ✔ stringr 1.5.1
+## ✔ ggplot2 3.4.4 ✔ tibble 3.2.1
+## ✔ lubridate 1.9.3 ✔ tidyr 1.3.0
+## ✔ purrr 1.0.2
+## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
+## ✖ dplyr::filter() masks stats::filter()
+## ✖ dplyr::lag() masks stats::lag()
+## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
+We will be utilizing nasopharyngeal microbiome data from Zambian +Infants from Odom et al.:
+
+dat <- system.file("extdata", "MAE.RDS", package = "LegATo") %>%
+ readRDS()
+
+dat_0.05 <- filter_animalcules_MAE(dat, 0.05)
+
+parsed <- parse_MAE_SE(dat, which_assay = "MicrobeGenetics", type = "MAE")
+parsed$sam
## Sample Subject HIVStatus MothChild timepoint Age pairing
+## X1754 X1754 0469-0 Control Mother 0 9999 NA
+## X1755 X1755 0469-1 Control Infant 0 7 1
+## X2214 X2214 0507-0 Control Mother 0 9999 NA
+## X2216 X2216 0507-1 Control Infant 0 6 2
+## X2429 X2429 0539-0 Control Mother 0 9999 NA
+## X2431 X2431 0539-1 Control Infant 0 9 3
+## X2561 X2561 0554-1 HIV Infant 0 6 1
+## X2562 X2562 0554-0 HIV Mother 0 9999 NA
+## X2697 X2697 0620-0 HIV Mother 0 9999 NA
+## X2699 X2699 0620-1 HIV Infant 0 4 2
+## X2927 X2927 0469-1 Control Infant 1 21 1
+## X3042 X3042 0645-0 HIV Mother 0 9999 NA
+## X3043 X3043 0645-1 HIV Infant 0 7 3
+## X3266 X3266 0507-1 Control Infant 1 20 2
+## X3306 X3306 0718-1 Control Infant 0 6 4
+## X3308 X3308 0718-0 Control Mother 0 9999 NA
+## X3646 X3646 0539-1 Control Infant 1 25 3
+## X3847 X3847 0749-1 HIV Infant 0 6 4
+## X3848 X3848 0749-0 HIV Mother 0 9999 NA
+## X3897 X3897 0620-1 HIV Infant 1 21 2
+## X3928 X3928 0554-1 HIV Infant 1 24 1
+## X4212 X4212 0645-1 HIV Infant 1 23 3
+## X4247 X4247 0801-1 Control Infant 0 6 5
+## X4249 X4249 0801-0 Control Mother 0 9999 NA
+## X4335 X4335 0798-0 HIV Mother 0 9999 NA
+## X4336 X4336 0798-1 HIV Infant 0 9 5
+## X4632 X4632 0718-1 Control Infant 1 24 4
+## X4753 X4753 0839-0 Control Mother 0 9999 NA
+## X4755 X4755 0839-1 Control Infant 0 6 6
+## X4756 X4756 0469-1 Control Infant 2 44 1
+## X4927 X4927 0850-1 HIV Infant 0 5 6
+## X4928 X4928 0850-0 HIV Mother 0 9999 NA
+## X5031 X5031 0749-1 HIV Infant 1 25 4
+## X5035 X5035 0554-1 HIV Infant 2 42 1
+## X5036 X5036 0890-0 Control Mother 0 9999 NA
+## X5037 X5037 0890-1 Control Infant 0 10 8
+## X5042 X5042 0507-1 Control Infant 2 42 2
+## X5116 X5116 0539-1 Control Infant 2 44 3
+## X5186 X5186 0645-1 HIV Infant 2 35 3
+## X5218 X5218 0878-0 Control Mother 0 9999 NA
+## X5220 X5220 0878-1 Control Infant 0 7 7
+## X5382 X5382 0895-1 HIV Infant 0 7 7
+## X5383 X5383 0895-0 HIV Mother 0 9999 NA
+## X5449 X5449 0620-1 HIV Infant 2 36 2
+## X5650 X5650 0801-1 Control Infant 1 20 5
+## X5659 X5659 0915-0 HIV Mother 0 9999 NA
+## X5660 X5660 0915-1 HIV Infant 0 6 8
+## X5806 X5806 0798-1 HIV Infant 1 24 5
+## X6202 X6202 0469-1 Control Infant 3 58 1
+## X6214 X6214 0839-1 Control Infant 1 20 6
+## X6280 X6280 0890-1 Control Infant 1 20 8
+## X6354 X6354 0507-1 Control Infant 3 56 2
+## X6474 X6474 0850-1 HIV Infant 1 24 6
+## X6534 X6534 0878-1 Control Infant 1 22 7
+## X6541 X6541 0718-1 Control Infant 2 44 4
+## X6644 X6644 0539-1 Control Infant 3 59 3
+## X6822 X6822 0554-1 HIV Infant 3 57 1
+## X6863 X6863 0895-0 HIV Mother 6 9999 NA
+## X6864 X6864 0895-1 HIV Infant 1 23 7
+## X6870 X6870 0749-1 HIV Infant 2 42 4
+## X7031 X7031 0987-1 HIV Infant 0 8 9
+## X7090 X7090 0915-1 HIV Infant 1 25 8
+## X7223 X7223 0620-1 HIV Infant 3 58 2
+## X7272 X7272 0801-1 Control Infant 2 42 5
+## X7274 X7274 0507-1 Control Infant 4 70 2
+## X7288 X7288 0798-1 HIV Infant 2 44 5
+## X7426 X7426 0645-1 HIV Infant 3 60 3
+## X7448 X7448 0469-1 Control Infant 4 74 1
+## X7695 X7695 0718-1 Control Infant 3 59 4
+## X7746 X7746 0539-1 Control Infant 4 74 3
+## X7958 X7958 0554-1 HIV Infant 4 72 1
+## X8066 X8066 0839-1 Control Infant 2 42 6
+## X8180 X8180 0987-1 HIV Infant 1 22 9
+## X8261 X8261 1049-0 Control Mother 0 9999 NA
+## X8262 X8262 1049-1 Control Infant 0 6 10
+## X8268 X8268 0890-1 Control Infant 2 45 8
+## X8285 X8285 1040-0 Control Mother 0 9999 NA
+## X8287 X8287 1040-1 Control Infant 0 7 9
+## X8288 X8288 0850-1 HIV Infant 2 44 6
+## X8312 X8312 0878-1 Control Infant 2 42 7
+## X8332 X8332 0749-1 HIV Infant 3 60 4
+## X8500 X8500 0620-1 HIV Infant 4 72 2
+## X8550 X8550 0801-1 Control Infant 3 56 5
+## X8607 X8607 1095-0 HIV Mother 0 9999 NA
+## X8608 X8608 1095-1 HIV Infant 0 6 10
+## X8686 X8686 0915-0 HIV Mother 6 9999 NA
+## X8688 X8688 0915-1 HIV Infant 2 41 8
+## X8726 X8726 0645-1 HIV Infant 4 73 3
+## X8736 X8736 0507-1 Control Infant 5 84 2
+## X8742 X8742 0798-1 HIV Infant 3 59 5
+## X8789 X8789 0469-1 Control Infant 5 92 1
+## X9000 X9000 0718-1 Control Infant 4 74 4
+## X9080 X9080 0539-1 Control Infant 5 88 3
+## X9376 X9376 0839-1 Control Infant 3 56 6
+## X9384 X9384 1040-1 Control Infant 1 21 9
+## X9424 X9424 1049-1 Control Infant 1 22 10
+## X9518 X9518 0850-1 HIV Infant 3 60 6
+## X9555 X9555 0620-1 HIV Infant 5 86 2
+## X9572 X9572 0554-1 HIV Infant 5 91 1
+## X9603 X9603 0749-1 HIV Infant 4 74 4
+## X9632 X9632 0878-1 Control Infant 3 58 7
+## X9684 X9684 0890-1 Control Infant 3 60 8
+## X9708 X9708 1095-1 HIV Infant 1 20 10
+## X9714 X9714 0645-1 HIV Infant 5 87 3
+## X9922 X9922 0987-1 HIV Infant 2 42 9
+## X9956 X9956 0798-1 HIV Infant 4 76 5
+## X9983 X9983 0469-0 Control Mother 6 9999 NA
+## X9984 X9984 0469-1 Control Infant 6 105 1
+## X10062 X10062 0507-0 Control Mother 6 9999 NA
+## X10064 X10064 0507-1 Control Infant 6 101 2
+## X10255 X10255 0718-1 Control Infant 5 88 4
+## X10401 X10401 0539-0 Control Mother 6 9999 NA
+## X10402 X10402 0539-1 Control Infant 6 104 3
+## X10590 X10590 0554-0 HIV Mother 6 9999 NA
+## X10592 X10592 0554-1 HIV Infant 6 104 1
+## X10724 X10724 0749-1 HIV Infant 5 88 4
+## X10754 X10754 0850-1 HIV Infant 4 75 6
+## X10892 X10892 0987-1 HIV Infant 3 56 9
+## X10907 X10907 0890-1 Control Infant 4 75 8
+## X10973 X10973 0878-1 Control Infant 4 73 7
+## X10986 X10986 1040-1 Control Infant 2 42 9
+## X11041 X11041 0620-0 HIV Mother 6 9999 NA
+## X11043 X11043 0620-1 HIV Infant 6 102 2
+## X11120 X11120 1049-1 Control Infant 2 42 10
+## X11170 X11170 0801-1 Control Infant 5 87 5
+## X11220 X11220 0839-1 Control Infant 4 80 6
+## X11244 X11244 0798-1 HIV Infant 5 90 5
+## X11269 X11269 0645-0 HIV Mother 6 9999 NA
+## X11270 X11270 0645-1 HIV Infant 6 106 3
+## X11373 X11373 0718-0 Control Mother 6 9999 NA
+## X11374 X11374 0718-1 Control Infant 6 104 4
+## X11376 X11376 1095-1 HIV Infant 2 42 10
+## X11822 X11822 0850-1 HIV Infant 5 89 6
+## X11916 X11916 0878-1 Control Infant 5 88 7
+## X12080 X12080 0987-1 HIV Infant 4 74 9
+## X12115 X12115 0839-1 Control Infant 5 95 6
+## X12136 X12136 0890-1 Control Infant 5 88 8
+## X12185 X12185 0749-0 HIV Mother 6 9999 NA
+## X12187 X12187 0749-1 HIV Infant 6 105 4
+## X12327 X12327 1049-1 Control Infant 3 56 10
+## X12342 X12342 0798-0 HIV Mother 6 9999 NA
+## X12344 X12344 0798-1 HIV Infant 6 107 5
+## X12455 X12455 0801-0 Control Mother 6 9999 NA
+## X12456 X12456 0801-1 Control Infant 6 104 5
+## X12504 X12504 1095-1 HIV Infant 3 56 10
+## X12838 X12838 0850-0 HIV Mother 6 9999 NA
+## X12840 X12840 0850-1 HIV Infant 6 104 6
+## X13074 X13074 1095-1 HIV Infant 4 73 10
+## X13183 X13183 0878-0 Control Mother 6 9999 NA
+## X13184 X13184 0878-1 Control Infant 6 105 7
+## X13219 X13219 1040-1 Control Infant 4 73 9
+## X13281 X13281 0890-0 Control Mother 6 9999 NA
+## X13283 X13283 0890-1 Control Infant 6 107 8
+## X13354 X13354 0987-1 HIV Infant 5 90 9
+## X13473 X13473 0839-0 Control Mother 6 9999 NA
+## X13474 X13474 0839-1 Control Infant 6 111 6
+## X13530 X13530 1049-1 Control Infant 4 73 10
+## X14194 X14194 1040-1 Control Infant 5 87 9
+## X14385 X14385 0987-0 HIV Mother 0 9999 NA
+## X14387 X14387 0987-1 HIV Infant 6 104 9
+## X14502 X14502 1049-1 Control Infant 5 87 10
+## X14800 X14800 1095-1 HIV Infant 5 87 10
+## X15367 X15367 1040-0 Control Mother 6 9999 NA
+## X15368 X15368 1040-1 Control Infant 6 103 9
+## X15601 X15601 1049-1 Control Infant 6 104 10
+## X15925 X15925 1095-1 HIV Infant 6 103 10
+## X15926 X15926 1095-0 HIV Mother 6 9999 NA
+
+alluvial_df <- get_long_data(dat_0.05, "genus")
## Registered S3 method overwritten by 'httr':
+## method from
+## print.response rmutil
+
+group_vars <- c("HIVStatus", "MothChild")
+get_summary_table(dat_0.05, group_vars)
## HIVStatus MothChild mean_reads sd_reads min_reads max_reads num_total
+## 1 Control Infant 156209.16 408000.52 24176 3016276 68
+## 2 Control Mother 68648.79 50526.74 14339 168157 19
+## 3 HIV Infant 90008.20 51395.08 13218 202079 61
+## 4 HIV Mother 72277.53 48180.28 20118 208029 19
+
+best_genus <- get_top_taxa(dat_0.05, "genus")
+best_species <- get_top_taxa(dat_0.05, "species")
+this_palette <- paletteer::palettes_d[["ggsci"]]["category20_d3"] |>
+ unlist() |> unname()
+
+plot_stacked_area(dat_0.05, "genus",
+ "HIVStatus",
+ "timepoint",
+ palette_input = this_palette)
+plot_stacked_bar(dat_0.05, "genus",
+ "HIVStatus",
+ "timepoint",
+ palette_input = this_palette)
+plot_alluvial(dat = dat_0.05,
+ taxon_level = "genus",
+ covariate_1 = "HIVStatus",
+ covariate_time = "timepoint",
+ palette_input = this_palette,
+ subtitle = "Alluvial plot")
+plot_spaghetti(dat = dat_0.05,
+ covariate_time = "timepoint",
+ covariate_1 = "HIVStatus",
+ unit_var = "Subject",
+ taxon_level = "genus",
+ which_taxon = "Corynebacterium",
+ palette_input= this_palette,
+ title = "Spaghetti Plot",
+ subtitle = NULL) +
+ ggplot2::xlab("Infant Age (Days)") +
+ ggplot2::ylab("Relative Abundance (log CPM)")
+run_gee_model(dat, unit_var = "Subject",
+ fixed_cov = c("HIVStatus", "MothChild", "Age"),
+ corstr = "ar1",
+ plot_out = FALSE,
+ plotsave_loc = ".",
+ plot_terms = NULL)
## Coefficient Coefficient Estimate Standard Error Statistic
+## 1 (Intercept) 4.702448e+04 3.979432e+04 1.396387e+00
+## 2 (Intercept) 2.070172e+03 3.238258e+03 4.086862e-01
+## 3 (Intercept) 9.530864e+03 5.106186e+03 3.483945e+00
+## 4 (Intercept) 6.120925e+04 2.592733e+04 5.573378e+00
+## 5 (Intercept) 4.741639e+04 2.051563e+04 5.341797e+00
+## 6 (Intercept) -7.011414e+02 1.529727e+03 2.100794e-01
+## 7 (Intercept) 1.134651e+03 5.499470e+02 4.256798e+00
+## 8 (Intercept) 2.076618e+03 1.219839e+03 2.898065e+00
+## 9 (Intercept) 2.054780e+03 9.842547e+02 4.358285e+00
+## 10 (Intercept) 4.195871e+03 3.007082e+03 1.946945e+00
+## 11 (Intercept) 5.014573e+02 2.760020e+02 3.300985e+00
+## 12 (Intercept) 2.959834e+02 1.259813e+02 5.519786e+00
+## 13 (Intercept) 1.281196e+02 1.274034e+02 1.011273e+00
+## 14 (Intercept) -9.488892e+02 9.262133e+02 1.049564e+00
+## 15 (Intercept) 7.089552e+02 3.755248e+02 3.564185e+00
+## 16 (Intercept) 1.526145e+02 5.257275e+01 8.426950e+00
+## 17 (Intercept) 2.063306e+02 1.062556e+02 3.770717e+00
+## 18 (Intercept) 8.101896e+01 7.929888e+01 1.043853e+00
+## 19 (Intercept) 9.430793e+01 5.240601e+01 3.238428e+00
+## 20 (Intercept) 6.308457e+02 4.130694e+02 2.332385e+00
+## 21 (Intercept) 9.930723e+01 4.060469e+01 5.981489e+00
+## 22 (Intercept) 1.053014e+03 1.026625e+03 1.052069e+00
+## 23 (Intercept) 5.994022e+01 5.712665e+01 1.100929e+00
+## 24 (Intercept) 4.534493e+01 1.834481e+01 6.109856e+00
+## 25 (Intercept) 1.062805e+01 3.764940e+01 7.968771e-02
+## 26 (Intercept) 6.342971e+01 4.223319e+01 2.255682e+00
+## 27 (Intercept) 5.549567e+01 3.041488e+01 3.329246e+00
+## 28 (Intercept) -2.081198e+01 2.518016e+01 6.831396e-01
+## 29 (Intercept) -3.351121e+00 1.594618e+01 4.416383e-02
+## 30 (Intercept) 6.842275e+01 3.907756e+01 3.065816e+00
+## 31 (Intercept) -8.542355e+00 4.939945e+01 2.990274e-02
+## 32 (Intercept) 9.639983e+01 4.651837e+01 4.294410e+00
+## 33 (Intercept) 7.738408e+01 4.553870e+01 2.887633e+00
+## 34 (Intercept) 2.303199e+01 1.765742e+01 1.701407e+00
+## 35 (Intercept) 4.166442e+01 2.137829e+01 3.798261e+00
+## 36 (Intercept) 3.552748e+02 3.130368e+02 1.288065e+00
+## 37 (Intercept) -1.512589e+00 1.912379e+01 6.255965e-03
+## 38 (Intercept) -2.227466e+00 2.902759e+01 5.888438e-03
+## 39 (Intercept) 5.701181e+01 4.849190e+01 1.382264e+00
+## 40 (Intercept) 5.348917e+01 4.274545e+01 1.565856e+00
+## 41 (Intercept) 9.075834e+01 5.902282e+01 2.364467e+00
+## 42 (Intercept) 4.329713e+01 2.060413e+01 4.415801e+00
+## 43 (Intercept) 3.358584e+01 3.241233e+01 1.073722e+00
+## 44 (Intercept) -1.286103e+00 8.452930e+00 2.314924e-02
+## 45 (Intercept) 6.159703e+01 3.617142e+01 2.899937e+00
+## 46 (Intercept) 7.605558e+00 3.006248e+01 6.400479e-02
+## 47 (Intercept) 6.443894e+01 3.079589e+01 4.378357e+00
+## 48 (Intercept) 1.277925e+01 2.037126e+01 3.935277e-01
+## 49 (Intercept) 1.425788e+01 9.919692e+00 2.065921e+00
+## 50 (Intercept) 4.074046e+01 2.753721e+01 2.188830e+00
+## 51 (Intercept) 2.272532e+01 1.558961e+01 2.124955e+00
+## 52 (Intercept) 6.454419e+00 1.348331e+01 2.291508e-01
+## 53 (Intercept) 7.543769e+00 7.934460e+00 9.039449e-01
+## 54 (Intercept) 1.985378e+01 1.624549e+01 1.493553e+00
+## 55 (Intercept) 5.863766e+01 3.339047e+01 3.083956e+00
+## 56 (Intercept) 3.604530e+01 1.767795e+01 4.157511e+00
+## 57 (Intercept) -4.052184e-01 1.122229e+01 1.303812e-03
+## 58 (Intercept) 8.018781e+00 8.656160e+00 8.581557e-01
+## 59 (Intercept) 1.676624e+01 1.050890e+01 2.545407e+00
+## 60 (Intercept) 1.023403e+01 8.501561e+00 1.449092e+00
+## 61 (Intercept) 8.486455e+01 6.536480e+01 1.685640e+00
+## 62 (Intercept) 8.308952e+01 5.277141e+01 2.479106e+00
+## 63 (Intercept) 6.770671e+01 3.371497e+01 4.032905e+00
+## 64 (Intercept) 1.539512e+01 2.920865e+01 2.778071e-01
+## 65 (Intercept) 1.539590e+01 8.506559e+00 3.275686e+00
+## 66 (Intercept) -4.472032e+00 4.812331e+00 8.635724e-01
+## 67 (Intercept) 1.852459e+01 1.255395e+01 2.177391e+00
+## 68 (Intercept) 1.504187e+01 6.047327e+00 6.186955e+00
+## 69 (Intercept) 9.284554e+00 1.077920e+01 7.419067e-01
+## 70 (Intercept) 1.438389e+01 9.335799e+00 2.373829e+00
+## 71 (Intercept) -7.131572e+00 5.477546e+00 1.695112e+00
+## 72 (Intercept) 1.023608e+02 8.244052e+01 1.541652e+00
+## 73 (Intercept) -1.232703e+01 1.318638e+01 8.739074e-01
+## 74 (Intercept) 2.971374e+01 1.778998e+01 2.789739e+00
+## 75 (Intercept) -1.628307e+00 7.822308e+00 4.333142e-02
+## 76 (Intercept) 6.629574e+00 8.935556e+00 5.504630e-01
+## 77 (Intercept) 1.543420e+01 8.814437e+00 3.066047e+00
+## 78 (Intercept) 2.365216e+01 1.032264e+01 5.250007e+00
+## 79 (Intercept) -5.121470e-01 2.874809e+00 3.173740e-02
+## 80 (Intercept) 5.382371e-01 3.252847e+00 2.737916e-02
+## 81 (Intercept) 1.224725e+01 7.297333e+00 2.816754e+00
+## 82 (Intercept) 2.886423e+01 1.872218e+01 2.376878e+00
+## 83 (Intercept) 9.190484e+00 4.445900e+00 4.273242e+00
+## 84 (Intercept) 9.492862e+00 7.003668e+00 1.837144e+00
+## 85 (Intercept) 3.614868e+01 2.886017e+01 1.568871e+00
+## 86 (Intercept) -3.539824e+00 7.982123e+00 1.966647e-01
+## 87 (Intercept) 9.446837e+00 6.479941e+00 2.125352e+00
+## 88 (Intercept) -5.655511e+00 1.013204e+01 3.115662e-01
+## 89 (Intercept) -1.189325e-01 3.201013e+00 1.380468e-03
+## 90 (Intercept) 2.125350e+00 2.343013e+00 8.228329e-01
+## 91 (Intercept) -3.670697e-02 1.549623e+00 5.611060e-04
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+## 1892 HIVStatusHIV -1.166138e-02 1.107225e-02 1.109247e+00
+## 1893 HIVStatusHIV -1.166138e-02 1.107225e-02 1.109247e+00
+## 1894 HIVStatusHIV -1.166138e-02 1.107225e-02 1.109247e+00
+## 1895 HIVStatusHIV -6.337990e-02 6.028787e-02 1.105206e+00
+## 1896 HIVStatusHIV 2.621310e-02 2.463630e-02 1.132103e+00
+## 1897 HIVStatusHIV 2.621310e-02 2.463630e-02 1.132103e+00
+## 1898 HIVStatusHIV 2.356800e-02 2.560989e-02 8.468962e-01
+## 1899 HIVStatusHIV 1.189083e-02 1.162946e-02 1.045455e+00
+## 1900 HIVStatusHIV 2.568400e-02 2.416381e-02 1.129781e+00
+## 1901 HIVStatusHIV -2.115522e-02 2.005465e-02 1.112769e+00
+## 1902 HIVStatusHIV -1.145517e-02 1.086592e-02 1.111399e+00
+## 1903 HIVStatusHIV -4.183634e-02 3.959740e-02 1.116283e+00
+## 1904 HIVStatusHIV -1.821186e-02 3.231834e-02 3.175489e-01
+## 1905 HIVStatusHIV 3.567249e-02 3.488838e-02 1.045455e+00
+## 1906 HIVStatusHIV -2.402212e-02 2.285310e-02 1.104924e+00
+## 1907 HIVStatusHIV 1.345738e-02 1.261722e-02 1.137612e+00
+## 1908 HIVStatusHIV 1.345738e-02 1.261722e-02 1.137612e+00
+## 1909 HIVStatusHIV -4.213989e-02 3.993121e-02 1.113684e+00
+## 1910 HIVStatusHIV 2.378166e-02 2.325892e-02 1.045455e+00
+## 1911 HIVStatusHIV -1.030536e-01 9.916696e-02 1.079922e+00
+## 1912 HIVStatusHIV -1.169607e-02 1.107591e-02 1.115117e+00
+## 1913 HIVStatusHIV -1.169607e-02 1.107591e-02 1.115117e+00
+## 1914 HIVStatusHIV -1.169607e-02 1.107591e-02 1.115117e+00
+## 1915 HIVStatusHIV -1.169607e-02 1.107591e-02 1.115117e+00
+## 1916 HIVStatusHIV -1.169607e-02 1.107591e-02 1.115117e+00
+## 1917 HIVStatusHIV -1.169607e-02 1.107591e-02 1.115117e+00
+## 1918 HIVStatusHIV -1.207921e-02 1.148593e-02 1.105974e+00
+## 1919 HIVStatusHIV -1.207921e-02 1.148593e-02 1.105974e+00
+## 1920 HIVStatusHIV -1.189083e-02 1.162946e-02 1.045455e+00
+## 1921 HIVStatusHIV -1.189083e-02 1.162946e-02 1.045455e+00
+## 1922 HIVStatusHIV -1.165674e-02 1.107147e-02 1.108521e+00
+## 1923 HIVStatusHIV -1.208225e-02 1.153177e-02 1.097750e+00
+## 1924 HIVStatusHIV -3.168995e-02 3.014393e-02 1.105206e+00
+## 1925 HIVStatusHIV 1.336531e-02 1.262769e-02 1.120238e+00
+## 1926 HIVStatusHIV 1.310655e-02 1.231815e-02 1.132103e+00
+## 1927 HIVStatusHIV 3.946604e-02 3.705050e-02 1.134642e+00
+## 1928 HIVStatusHIV -1.209442e-02 1.151014e-02 1.104100e+00
+## 1929 HIVStatusHIV -5.725201e-02 5.509276e-02 1.079922e+00
+## 1930 HIVStatusHIV -2.106995e-02 1.996560e-02 1.113684e+00
+## 1931 HIVStatusHIV -2.413730e-02 2.319497e-02 1.082903e+00
+## 1932 HIVStatusHIV 1.189083e-02 1.162946e-02 1.045455e+00
+## 1933 HIVStatusHIV -1.102694e-02 1.045101e-02 1.113253e+00
+## 1934 HIVStatusHIV -2.284845e-02 2.168049e-02 1.110645e+00
+## 1935 HIVStatusHIV -2.495278e-02 2.518678e-02 9.815051e-01
+## 1936 HIVStatusHIV -2.495278e-02 2.518678e-02 9.815051e-01
+## 1937 HIVStatusHIV -2.338807e-02 2.217847e-02 1.112053e+00
+## 1938 HIVStatusHIV 1.337917e-02 1.260365e-02 1.126849e+00
+## 1939 HIVStatusHIV 1.242471e-02 1.221920e-02 1.033921e+00
+## 1940 HIVStatusHIV -3.027605e-01 2.875803e-01 1.108358e+00
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+## 1943 MothChildMother -1.884367e+06 4.657222e+05 1.637107e+01
+## 1944 MothChildMother -1.200823e+06 5.822301e+05 4.253720e+00
+## 1945 MothChildMother 6.081656e+06 2.170732e+06 7.849302e+00
+## 1946 MothChildMother 3.537821e+06 1.691472e+06 4.374637e+00
+## 1947 MothChildMother -1.417844e+06 3.856761e+05 1.351485e+01
+## 1948 MothChildMother -1.127497e+05 1.295451e+05 7.575109e-01
+## 1949 MothChildMother 9.338708e+04 8.614884e+04 1.175100e+00
+## 1950 MothChildMother 6.371588e+04 9.196123e+04 4.800493e-01
+## 1951 MothChildMother 6.269315e+05 4.837589e+05 1.679508e+00
+## 1952 MothChildMother -6.749208e+03 2.534460e+04 7.091443e-02
+## 1953 MothChildMother -1.486818e+04 2.183899e+04 4.635005e-01
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+## 1955 MothChildMother -1.861381e+05 1.811074e+05 1.056325e+00
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+## 1959 MothChildMother 9.684195e+03 9.569952e+03 1.024018e+00
+## 1960 MothChildMother -1.567137e+03 2.756002e+03 3.233367e-01
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+## 1965 MothChildMother 2.837683e+03 1.366355e+03 4.313213e+00
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+## 1969 MothChildMother -1.614439e+03 1.744027e+03 8.569134e-01
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+## 1978 MothChildMother -6.902244e+03 3.933929e+03 3.078418e+00
+## 1979 MothChildMother -1.295684e+03 2.246386e+03 3.326822e-01
+## 1980 MothChildMother 2.481933e+03 2.542571e+03 9.528706e-01
+## 1981 MothChildMother 1.138283e+03 2.897735e+03 1.543060e-01
+## 1982 MothChildMother 4.931563e+03 5.004530e+03 9.710520e-01
+## 1983 MothChildMother 1.335885e+03 1.602256e+03 6.951439e-01
+## 1984 MothChildMother -2.003876e+02 9.847567e+02 4.140796e-02
+## 1985 MothChildMother -8.961096e+02 8.976976e+02 9.964652e-01
+## 1986 MothChildMother -1.104230e+03 9.909517e+02 1.241693e+00
+## 1987 MothChildMother -8.985370e+02 3.141388e+03 8.181423e-02
+## 1988 MothChildMother 3.405910e+03 1.650787e+03 4.256810e+00
+## 1989 MothChildMother 4.173224e+02 1.384304e+03 9.088255e-02
+## 1990 MothChildMother 2.532507e+02 5.554646e+02 2.078684e-01
+## 1991 MothChildMother -4.402697e+03 5.034859e+03 7.646504e-01
+## 1992 MothChildMother 1.273810e+03 1.183784e+03 1.157882e+00
+## 1993 MothChildMother -2.877727e+03 3.325260e+03 7.489416e-01
+## 1994 MothChildMother -3.854640e+03 3.793272e+03 1.032618e+00
+## 1995 MothChildMother 2.691824e+03 2.538740e+03 1.124235e+00
+## 1996 MothChildMother 4.841055e+03 2.977938e+03 2.642705e+00
+## 1997 MothChildMother -2.403196e+03 4.538350e+03 2.804027e-01
+## 1998 MothChildMother 3.828057e+02 3.330689e+02 1.320957e+00
+## 1999 MothChildMother 6.024198e+02 6.093111e+02 9.775079e-01
+## 2000 MothChildMother -1.413500e+03 2.573279e+03 3.017295e-01
+## 2001 MothChildMother -7.649843e+01 4.033336e+02 3.597297e-02
+## 2002 MothChildMother 2.961400e+03 2.665147e+03 1.234673e+00
+## 2003 MothChildMother 7.727827e+03 5.165675e+03 2.238003e+00
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+## 2010 MothChildMother -5.144682e+02 8.108857e+02 4.025297e-01
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+## 2013 MothChildMother 1.422086e+04 1.303552e+04 1.190130e+00
+## 2014 MothChildMother 3.412602e+01 2.762009e+02 1.526585e-02
+## 2015 MothChildMother 2.418606e+03 1.584301e+03 2.330531e+00
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+## 2020 MothChildMother -5.543109e+02 4.573537e+02 1.468935e+00
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+## 2393 MothChildMother 2.170116e+01 2.215422e+01 9.595174e-01
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+## 2395 MothChildMother 6.187947e-01 7.044411e-01 7.716205e-01
+## 2396 MothChildMother 1.515521e+01 1.731745e+01 7.658721e-01
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+## 2398 MothChildMother 3.092522e+01 2.077281e+01 2.216333e+00
+## 2399 MothChildMother 9.182390e+00 9.276553e+00 9.798016e-01
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+## 2403 MothChildMother 2.205385e+01 1.598004e+01 1.904641e+00
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+## 2406 MothChildMother -1.946447e+00 8.571571e+00 5.156610e-02
+## 2407 MothChildMother -4.050186e+01 3.912140e+01 1.071818e+00
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+## 2409 MothChildMother 2.578309e+00 2.935171e+00 7.716198e-01
+## 2410 MothChildMother -9.584091e-01 1.537746e+00 3.884479e-01
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+## 2414 MothChildMother -8.065938e+01 7.719471e+01 1.091779e+00
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+## 2417 MothChildMother -3.019579e+01 2.962291e+01 1.039052e+00
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+## 2421 MothChildMother -2.344903e+00 2.532814e+00 8.571236e-01
+## 2422 MothChildMother -1.242426e+01 1.202781e+01 1.067008e+00
+## 2423 MothChildMother 1.959515e+00 2.230730e+00 7.716198e-01
+## 2424 MothChildMother -2.054116e+01 1.989811e+01 1.065679e+00
+## 2425 MothChildMother -2.054116e+01 1.989811e+01 1.065679e+00
+## 2426 MothChildMother -6.030223e-01 5.774953e-01 1.090360e+00
+## 2427 MothChildMother 1.745706e+01 1.699559e+01 1.055042e+00
+## 2428 MothChildMother 2.006330e+01 1.962119e+01 1.045572e+00
+## 2429 MothChildMother -5.516068e+00 5.207207e+00 1.122146e+00
+## 2430 MothChildMother -2.388107e+01 1.529992e+01 2.436292e+00
+## 2431 MothChildMother -5.233389e+01 5.065105e+01 1.067552e+00
+## 2432 MothChildMother -7.061962e-01 1.133076e+00 3.884478e-01
+## 2433 MothChildMother -1.583791e+01 1.540254e+01 1.057331e+00
+## 2434 MothChildMother -2.601910e+01 2.509101e+01 1.075346e+00
+## 2435 MothChildMother -6.764257e+00 1.012250e+01 4.465441e-01
+## 2436 MothChildMother -2.592403e+01 2.845140e+01 8.302285e-01
+## 2437 MothChildMother -1.611274e+01 1.906961e+01 7.139287e-01
+## 2438 MothChildMother 7.162556e+01 6.970143e+01 1.055973e+00
+## 2439 MothChildMother 7.030701e+01 6.677526e+01 1.108577e+00
+## 2440 MothChildMother -3.673578e+00 7.788607e+00 2.224636e-01
+## 2441 MothChildMother -2.312401e-02 1.637713e-01 1.993660e-02
+## 2442 MothChildMother 3.018963e+01 3.484129e+01 7.508048e-01
+## 2443 MothChildMother -1.711763e+01 1.658176e+01 1.065679e+00
+## 2444 MothChildMother -4.423019e+00 7.332170e+00 3.638920e-01
+## 2445 MothChildMother -3.091210e+00 3.010407e+00 1.054402e+00
+## 2446 MothChildMother -2.025931e+01 1.983023e+01 1.043743e+00
+## 2447 MothChildMother -1.184378e+01 6.382823e+00 3.443142e+00
+## 2448 MothChildMother 3.093973e-01 3.522206e-01 7.716205e-01
+## 2449 MothChildMother -3.867435e+01 3.817052e+01 1.026573e+00
+## 2450 MothChildMother -4.522667e-01 4.331215e-01 1.090360e+00
+## 2451 MothChildMother -4.522667e-01 4.331215e-01 1.090360e+00
+## 2452 MothChildMother -1.031264e+01 1.026840e+01 1.008636e+00
+## 2453 MothChildMother -1.348572e+01 1.393544e+01 9.364988e-01
+## 2454 MothChildMother 7.684812e+01 7.499708e+01 1.049972e+00
+## 2455 MothChildMother 3.642614e+01 3.819086e+01 9.097194e-01
+## 2456 MothChildMother 1.246933e+01 1.213971e+01 1.055042e+00
+## 2457 MothChildMother -2.146895e+01 2.077926e+01 1.067484e+00
+## 2458 MothChildMother -3.026560e-01 4.856042e-01 3.884487e-01
+## 2459 MothChildMother -1.610790e+01 1.373024e+01 1.376327e+00
+## 2460 MothChildMother -8.282840e+00 8.018542e+00 1.067008e+00
+## 2461 MothChildMother 3.428040e+00 3.363097e+00 1.038993e+00
+## 2462 MothChildMother 2.078633e+01 2.021498e+01 1.057326e+00
+## 2463 MothChildMother -1.734683e-02 1.228275e-01 1.994568e-02
+## 2464 MothChildMother -3.782721e+01 3.676204e+01 1.058789e+00
+## 2465 MothChildMother 7.710625e+00 7.486883e+00 1.060662e+00
+## 2466 MothChildMother 1.201754e+01 1.782258e+01 4.546634e-01
+## 2467 MothChildMother 1.490127e+01 1.472053e+01 1.024706e+00
+## 2468 MothChildMother -3.485830e+00 3.265643e+00 1.139397e+00
+## 2469 MothChildMother -3.459409e+01 3.100874e+01 1.244617e+00
+## 2470 MothChildMother -1.091816e+01 1.313400e+01 6.910426e-01
+## 2471 MothChildMother 1.443853e+00 1.643695e+00 7.716198e-01
+## 2472 MothChildMother -1.825546e+01 1.754948e+01 1.082074e+00
+## 2473 MothChildMother -3.761063e+01 4.030493e+01 8.707730e-01
+## 2474 MothChildMother 1.221772e+01 9.727349e+00 1.577580e+00
+## 2475 MothChildMother 2.275863e+00 2.183110e+00 1.086779e+00
+## 2476 MothChildMother 4.022602e+00 3.874036e+00 1.078169e+00
+## 2477 MothChildMother 4.022602e+00 3.874036e+00 1.078169e+00
+## 2478 MothChildMother 5.116405e+01 4.980409e+01 1.055358e+00
+## 2479 MothChildMother -2.208007e+00 2.150291e+00 1.054402e+00
+## 2480 MothChildMother 8.592163e+00 7.364933e+00 1.361029e+00
+## 2481 MothChildMother 5.606614e+00 6.896507e+00 6.609110e-01
+## 2482 MothChildMother -6.902367e+00 6.682118e+00 1.067008e+00
+## 2483 MothChildMother 4.125298e-01 4.696274e-01 7.716205e-01
+## 2484 MothChildMother -9.595311e-01 4.514420e+00 4.517667e-02
+## 2485 MothChildMother -1.612065e+01 1.577634e+01 1.044125e+00
+## 2486 MothChildMother 1.712076e+01 1.685074e+01 1.032305e+00
+## 2487 MothChildMother -1.490519e-01 2.190134e-01 4.631627e-01
+## 2488 MothChildMother 1.727336e+00 1.692349e+00 1.041775e+00
+## 2489 MothChildMother 1.727336e+00 1.692349e+00 1.041775e+00
+## 2490 MothChildMother 2.044163e+01 1.899670e+01 1.157910e+00
+## 2491 MothChildMother -3.015111e-01 2.887476e-01 1.090360e+00
+## 2492 MothChildMother -1.342035e+01 1.316574e+01 1.039052e+00
+## 2493 MothChildMother -5.037742e+00 6.841743e+00 5.421736e-01
+## 2494 MothChildMother 3.361795e+00 3.373830e+00 9.928781e-01
+## 2495 MothChildMother -1.916923e+01 1.832405e+01 1.094376e+00
+## 2496 MothChildMother 2.750241e+01 2.675220e+01 1.056872e+00
+## 2497 MothChildMother 2.750241e+01 2.675220e+01 1.056872e+00
+## 2498 MothChildMother 1.031324e+00 1.174069e+00 7.716205e-01
+## 2499 MothChildMother 1.994942e+01 1.946861e+01 1.050003e+00
+## 2500 MothChildMother -1.509908e+01 1.469179e+01 1.056213e+00
+## 2501 MothChildMother -7.251138e+00 7.020677e+00 1.066730e+00
+## 2502 MothChildMother -7.251138e+00 7.020677e+00 1.066730e+00
+## 2503 MothChildMother -1.156455e-02 8.188500e-02 1.994568e-02
+## 2504 MothChildMother -1.156455e-02 8.188500e-02 1.994568e-02
+## 2505 MothChildMother 5.140417e+00 4.991256e+00 1.060662e+00
+## 2506 MothChildMother 5.140417e+00 4.991256e+00 1.060662e+00
+## 2507 MothChildMother 3.410741e+01 3.319116e+01 1.055973e+00
+## 2508 MothChildMother 7.481596e+00 7.283823e+00 1.055042e+00
+## 2509 MothChildMother -3.035948e+00 2.904883e+00 1.092273e+00
+## 2510 MothChildMother -1.115104e+01 1.075329e+01 1.075346e+00
+## 2511 MothChildMother -3.828847e+00 1.152952e+01 1.102843e-01
+## 2512 MothChildMother -1.006526e+01 9.874304e+00 1.039052e+00
+## 2513 MothChildMother -1.006526e+01 9.874304e+00 1.039052e+00
+## 2514 MothChildMother 7.155065e+00 6.469721e+00 1.223083e+00
+## 2515 MothChildMother 7.155065e+00 6.469721e+00 1.223083e+00
+## 2516 MothChildMother -2.407390e+01 2.339571e+01 1.058816e+00
+## 2517 MothChildMother -1.746173e+00 3.103344e+00 3.166027e-01
+## 2518 MothChildMother -2.656455e+00 2.541773e+00 1.092273e+00
+## 2519 MothChildMother -4.215892e+00 4.424623e+00 9.078755e-01
+## 2520 MothChildMother -6.847052e+00 6.632703e+00 1.065679e+00
+## 2521 MothChildMother -7.558712e+00 6.503102e+00 1.350997e+00
+## 2522 MothChildMother -3.194879e+00 2.921192e+00 1.196158e+00
+## 2523 MothChildMother 7.219271e-01 8.218480e-01 7.716205e-01
+## 2524 MothChildMother -5.044267e-02 8.093404e-02 3.884487e-01
+## 2525 MothChildMother -2.397291e+01 2.331871e+01 1.056897e+00
+## 2526 MothChildMother 2.548703e+01 2.494557e+01 1.043883e+00
+## 2527 MothChildMother -1.719419e+01 1.671002e+01 1.058789e+00
+## 2528 MothChildMother -9.378862e+00 1.090928e+01 7.391082e-01
+## 2529 MothChildMother 2.011301e+00 1.937018e+00 1.078169e+00
+## 2530 MothChildMother -3.177036e+00 3.037921e+00 1.093683e+00
+## 2531 MothChildMother 1.460888e+01 1.420163e+01 1.058175e+00
+## 2532 MothChildMother 4.987731e+00 4.855882e+00 1.055042e+00
+## 2533 MothChildMother -3.026560e-01 4.856042e-01 3.884486e-01
+## 2534 MothChildMother 3.093973e-01 3.522206e-01 7.716205e-01
+## 2535 MothChildMother 6.187947e-01 7.044411e-01 7.716205e-01
+## 2536 MothChildMother 1.616251e+01 1.109990e+01 2.120213e+00
+## 2537 MothChildMother -2.333257e+00 2.274144e+00 1.052662e+00
+## 2538 MothChildMother 6.960422e+00 6.740913e+00 1.066188e+00
+## 2539 MothChildMother 8.636719e-01 8.461742e-01 1.041785e+00
+## 2540 MothChildMother 8.636719e-01 8.461742e-01 1.041785e+00
+## 2541 MothChildMother 8.636719e-01 8.461742e-01 1.041785e+00
+## 2542 MothChildMother -2.054821e+01 1.998746e+01 1.056897e+00
+## 2543 MothChildMother -2.628670e+00 2.537286e+00 1.073330e+00
+## 2544 MothChildMother -2.628670e+00 2.537286e+00 1.073330e+00
+## 2545 MothChildMother -1.804175e+00 5.576677e+00 1.046662e-01
+## 2546 MothChildMother -5.044267e-02 8.093404e-02 3.884487e-01
+## 2547 MothChildMother -4.676951e-01 4.993972e-01 8.770683e-01
+## 2548 MothChildMother -6.709657e+00 6.535406e+00 1.054036e+00
+## 2549 MothChildMother -5.782276e-03 4.094250e-02 1.994568e-02
+## 2550 MothChildMother -1.536369e+01 1.470376e+01 1.091779e+00
+## 2551 MothChildMother -1.265216e+01 1.008604e+01 1.573577e+00
+## 2552 MothChildMother -1.513280e-01 2.428021e-01 3.884486e-01
+## 2553 MothChildMother 4.434506e+00 4.349372e+00 1.039531e+00
+## 2554 MothChildMother -2.552323e+00 2.462376e+00 1.074392e+00
+## 2555 MothChildMother -2.552323e+00 2.462376e+00 1.074392e+00
+## 2556 MothChildMother -1.425857e+01 1.382515e+01 1.063683e+00
+## 2557 MothChildMother -1.008853e-01 1.618681e-01 3.884487e-01
+## 2558 MothChildMother -2.594128e-01 5.330842e-01 2.368052e-01
+## 2559 MothChildMother 1.005655e+00 9.685087e-01 1.078180e+00
+## 2560 MothChildMother 1.005655e+00 9.685087e-01 1.078180e+00
+## 2561 MothChildMother 1.005655e+00 9.685087e-01 1.078180e+00
+## 2562 MothChildMother 1.005655e+00 9.685087e-01 1.078180e+00
+## 2563 MothChildMother 1.005655e+00 9.685087e-01 1.078180e+00
+## 2564 MothChildMother 1.005655e+00 9.685087e-01 1.078180e+00
+## 2565 MothChildMother 2.493865e+00 2.427941e+00 1.055042e+00
+## 2566 MothChildMother 2.493865e+00 2.427941e+00 1.055042e+00
+## 2567 MothChildMother 1.031324e-01 1.174069e-01 7.716205e-01
+## 2568 MothChildMother 1.031324e-01 1.174069e-01 7.716205e-01
+## 2569 MothChildMother 8.554035e-01 8.451423e-01 1.024430e+00
+## 2570 MothChildMother 3.480212e+00 3.370456e+00 1.066188e+00
+## 2571 MothChildMother -1.027411e+01 9.993731e+00 1.056897e+00
+## 2572 MothChildMother -3.369349e+00 3.279866e+00 1.055309e+00
+## 2573 MothChildMother -1.314335e+00 1.268643e+00 1.073330e+00
+## 2574 MothChildMother -4.561624e+00 4.386462e+00 1.081460e+00
+## 2575 MothChildMother 3.481373e+00 3.396171e+00 1.050805e+00
+## 2576 MothChildMother -1.441182e-01 2.961579e-01 2.368052e-01
+## 2577 MothChildMother -7.129283e+00 6.912573e+00 1.063683e+00
+## 2578 MothChildMother 6.821482e+00 6.638232e+00 1.055973e+00
+## 2579 MothChildMother -5.044267e-02 8.093404e-02 3.884487e-01
+## 2580 MothChildMother -2.315068e+00 2.252116e+00 1.056686e+00
+## 2581 MothChildMother -2.933509e-01 2.932920e-01 1.000402e+00
+## 2582 MothChildMother 2.150318e-01 2.506225e-01 7.361479e-01
+## 2583 MothChildMother 2.150318e-01 2.506225e-01 7.361479e-01
+## 2584 MothChildMother 2.004335e+00 1.945544e+00 1.061350e+00
+## 2585 MothChildMother -3.438837e+00 3.342004e+00 1.058789e+00
+## 2586 MothChildMother 2.080698e+00 1.992931e+00 1.090018e+00
+## 2587 MothChildMother 2.063294e+01 2.036972e+01 1.026011e+00
+## 2588 MothChildMother -4.461865e-01 4.327966e-01 1.062833e+00
+## Unadj p-value Lower 95% CI Upper 95% CI
+## 1 2.373294e-01 -3.097095e+04 1.250199e+05
+## 2 5.226371e-01 -4.276698e+03 8.417042e+03
+## 3 6.196683e-02 -4.770759e+02 1.953880e+04
+## 4 1.823554e-02 1.039262e+04 1.120259e+05
+## 5 2.082000e-02 7.206499e+03 8.762628e+04
+## 6 6.467052e-01 -3.699351e+03 2.297068e+03
+## 7 3.909353e-02 5.677489e+01 2.212527e+03
+## 8 8.868597e-02 -3.142228e+02 4.467458e+03
+## 9 3.682936e-02 1.256762e+02 3.983884e+03
+## 10 1.629165e-01 -1.697902e+03 1.008964e+04
+## 11 6.923834e-02 -3.949660e+01 1.042411e+03
+## 12 1.880255e-02 4.906451e+01 5.429022e+02
+## 13 3.145980e-01 -1.215866e+02 3.778257e+02
+## 14 3.056075e-01 -2.764234e+03 8.664555e+02
+## 15 5.903872e-02 -2.705998e+01 1.444970e+03
+## 16 3.697000e-03 4.957384e+01 2.556552e+02
+## 17 5.215727e-02 -1.926472e+00 4.145877e+02
+## 18 3.069271e-01 -7.440399e+01 2.364419e+02
+## 19 7.192961e-02 -8.405956e+00 1.970218e+02
+## 20 1.267076e-01 -1.787554e+02 1.440447e+03
+## 21 1.445679e-02 1.972350e+01 1.788910e+02
+## 22 3.050310e-01 -9.591346e+02 3.065162e+03
+## 23 2.940624e-01 -5.202595e+01 1.719064e+02
+## 24 1.344301e-02 9.389761e+00 8.130010e+01
+## 25 7.777211e-01 -6.316341e+01 8.441952e+01
+## 26 1.331248e-01 -1.934581e+01 1.462052e+02
+## 27 6.805805e-02 -4.116401e+00 1.151077e+02
+## 28 4.085077e-01 -7.016419e+01 2.854024e+01
+## 29 8.335491e-01 -3.460506e+01 2.790282e+01
+## 30 7.995502e-02 -8.167871e+00 1.450134e+02
+## 31 8.627111e-01 -1.053635e+02 8.827879e+01
+## 32 3.823786e-02 5.225495e+00 1.875742e+02
+## 33 8.926197e-02 -1.187013e+01 1.666383e+02
+## 34 1.921040e-01 -1.157592e+01 5.763989e+01
+## 35 5.130584e-02 -2.362562e-01 8.356509e+01
+## 36 2.564048e-01 -2.582661e+02 9.688157e+02
+## 37 9.369573e-01 -3.899453e+01 3.596935e+01
+## 38 9.388334e-01 -5.912050e+01 5.466557e+01
+## 39 2.397158e-01 -3.803058e+01 1.520542e+02
+## 40 2.108098e-01 -3.029038e+01 1.372687e+02
+## 41 1.241263e-01 -2.492426e+01 2.064409e+02
+## 42 3.560756e-02 2.913769e+00 8.368049e+01
+## 43 3.001062e-01 -2.994116e+01 9.711284e+01
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+## 1701 2.922463e-01 -3.336258e-01 1.003984e-01
+## 1702 1.061141e-01 -1.160504e+00 1.116589e-01
+## 1703 2.875885e-01 -2.390476e-01 8.061397e-01
+## 1704 3.065562e-01 -8.721995e-02 2.774732e-01
+## 1705 2.940091e-01 -7.288076e-01 2.205307e-01
+## 1706 2.895919e-01 -2.225425e-01 7.457173e-01
+## 1707 2.698605e-01 -7.031686e-01 1.966216e-01
+## 1708 4.434777e-01 -5.061166e-01 2.215884e-01
+## 1709 2.696461e-01 -8.704904e+00 2.432289e+00
+## 1710 2.304619e-01 -2.755877e-01 6.636803e-02
+## 1711 4.246694e-01 -4.003659e-01 1.686076e-01
+## 1712 3.065567e-01 -2.071476e-01 6.589987e-01
+## 1713 1.569752e-01 -2.544415e-01 1.576827e+00
+## 1714 2.887952e-01 -2.101802e-01 7.060732e-01
+## 1715 2.921657e-01 -4.335253e-01 1.304284e-01
+## 1716 3.065567e-01 -8.324194e-01 2.616601e-01
+## 1717 2.848625e-01 -2.309030e-01 6.787432e-02
+## 1718 4.641225e-01 -3.461398e-01 1.578807e-01
+## 1719 2.927620e-01 -3.348596e-01 1.009324e-01
+## 1720 2.927620e-01 -3.348596e-01 1.009324e-01
+## 1721 3.117907e-01 -4.740949e-01 1.513327e-01
+## 1722 3.003557e-01 -5.613362e-01 1.819291e+00
+## 1723 2.234529e-01 -1.447583e+00 3.383079e-01
+## 1724 3.065562e-01 -1.090249e-01 3.468415e-01
+## 1725 1.204518e-01 -4.992008e-01 5.784959e-02
+## 1726 6.794029e-01 -2.370689e-01 3.637596e-01
+## 1727 5.997718e-01 -1.353074e-01 2.342454e-01
+## 1728 2.993488e-01 -1.475269e+01 4.537982e+00
+## 1729 2.842625e-01 -2.528408e-01 8.618129e-01
+## 1730 6.009818e-01 -1.203240e-01 6.963584e-02
+## 1731 3.873530e-01 -2.464981e-01 6.354944e-01
+## 1732 2.861574e-01 -1.127190e-01 3.818667e-01
+## 1733 2.925519e-01 -2.101539e-01 6.330238e-02
+## 1734 1.446240e-01 -1.932774e-01 2.833385e-02
+## 1735 3.065562e-01 -2.427891e-01 7.631745e-02
+## 1736 6.851948e-01 -2.929849e-01 1.925586e-01
+## 1737 2.917678e-01 -4.480417e-01 1.346277e-01
+## 1738 2.939405e-01 -2.416552e+01 7.310710e+00
+## 1739 2.502564e-01 -7.634847e-01 1.989277e-01
+## 1740 3.065567e-01 -2.725626e-01 8.671035e-01
+## 1741 2.921657e-01 -3.334810e-01 1.003296e-01
+## 1742 3.065562e-01 -3.468415e-01 1.090249e-01
+## 1743 2.995323e-01 -1.100122e+00 3.385907e-01
+## 1744 5.326453e-01 -5.166788e-01 9.993071e-01
+## 1745 7.544418e-01 -3.726738e-01 5.142104e-01
+## 1746 2.884912e-01 -3.318440e-01 1.115864e+00
+## 1747 4.248311e-01 -2.251991e-01 5.345627e-01
+## 1748 3.065562e-01 -2.081049e-01 6.541496e-02
+## 1749 9.967193e-01 -3.292699e-01 3.306543e-01
+## 1750 2.920837e-01 -2.716647e-01 8.171079e-02
+## 1751 8.791881e-01 -1.299754e-01 1.518299e-01
+## 1752 2.885675e-01 -1.175205e-01 3.950806e-01
+## 1753 6.446628e-01 -5.552271e-01 3.437041e-01
+## 1754 3.014078e-01 -8.285626e-01 2.564658e-01
+## 1755 2.884247e-01 -2.242509e-01 7.542293e-01
+## 1756 6.485183e-01 -1.885626e-01 1.174049e-01
+## 1757 2.917691e-01 -1.965130e-01 5.904854e-02
+## 1758 2.840352e-01 -1.114660e-01 3.802136e-01
+## 1759 9.348337e-01 -6.392130e-02 6.948676e-02
+## 1760 2.872866e-01 -3.096391e-01 1.045202e+00
+## 1761 3.065562e-01 -3.121574e-01 9.812244e-02
+## 1762 3.065567e-01 -8.671035e-01 2.725626e-01
+## 1763 3.065567e-01 -2.071476e-01 6.589987e-01
+## 1764 2.920837e-01 -2.112948e-01 6.355283e-02
+## 1765 2.935775e-01 -1.729478e-01 5.226222e-02
+## 1766 3.065567e-01 -9.017877e-01 2.834651e-01
+## 1767 2.907203e-01 -6.270906e-01 1.878089e-01
+## 1768 2.912925e-01 -1.062622e+01 3.188210e+00
+## 1769 7.831644e-01 -4.308510e-01 5.716055e-01
+## 1770 3.046438e-01 -2.770176e-01 8.658285e-02
+## 1771 9.550404e-01 -6.973538e-02 7.386607e-02
+## 1772 2.949605e-01 -3.469346e-01 1.052897e-01
+## 1773 3.369840e-01 -1.749479e-01 5.109570e-01
+## 1774 2.882191e-01 -8.694090e-02 2.926021e-01
+## 1775 2.877085e-01 -9.961210e-02 3.357931e-01
+## 1776 3.065567e-01 -6.589987e-01 2.071476e-01
+## 1777 2.920837e-01 -1.811098e-01 5.447386e-02
+## 1778 2.920837e-01 -1.811098e-01 5.447386e-02
+## 1779 2.919483e-01 -1.306792e-01 3.928875e-02
+## 1780 2.929588e-01 -2.421385e-01 7.302955e-02
+## 1781 2.887952e-01 -9.458108e-02 3.177329e-01
+## 1782 2.918902e-01 -6.190374e-01 1.860800e-01
+## 1783 4.791781e-01 -1.760422e-01 8.264558e-02
+## 1784 2.868928e-01 -2.264331e-01 7.652989e-01
+## 1785 3.065567e-01 -1.526351e-01 4.855780e-01
+## 1786 2.920865e-01 -4.166878e-01 1.253317e-01
+## 1787 2.840352e-01 -7.802619e-02 2.661495e-01
+## 1788 7.941884e-01 -2.295459e-01 1.756177e-01
+## 1789 2.399980e-01 -7.970575e-02 3.183221e-01
+## 1790 4.976873e-01 -1.357421e-01 2.793667e-01
+## 1791 2.980489e-01 -7.307854e-01 2.239021e-01
+## 1792 2.892785e-01 -2.222475e-01 7.454683e-01
+## 1793 6.002577e-02 -6.362430e-03 3.079062e-01
+## 1794 2.917691e-01 -1.310087e-01 3.936569e-02
+## 1795 1.860402e-01 -9.857020e-02 5.074531e-01
+## 1796 2.920837e-01 -1.509248e-01 4.539488e-02
+## 1797 2.446079e-02 -1.266786e-01 -8.722009e-03
+## 1798 2.876021e-01 -7.606327e-02 2.564969e-01
+## 1799 2.995323e-01 -5.500608e-01 1.692953e-01
+## 1800 7.221131e-02 -1.354086e-02 3.137440e-01
+## 1801 3.065562e-01 -1.040525e-01 3.270748e-02
+## 1802 1.463944e-01 -4.728771e-01 7.033926e-02
+## 1803 2.919483e-01 -9.800937e-02 2.946656e-02
+## 1804 2.919483e-01 -9.800937e-02 2.946656e-02
+## 1805 2.878867e-01 -2.610259e-01 8.794206e-01
+## 1806 4.126004e-01 -5.864466e-02 1.428942e-01
+## 1807 2.941845e-01 -8.272366e-01 2.504509e-01
+## 1808 2.365712e-01 -1.104874e-01 4.473734e-01
+## 1809 2.929588e-01 -1.729560e-01 5.216397e-02
+## 1810 2.859496e-01 -6.732931e-02 2.282488e-01
+## 1811 3.065562e-01 -6.541496e-02 2.081049e-01
+## 1812 1.668416e-01 -2.159867e-01 3.732092e-02
+## 1813 2.877085e-01 -6.640807e-02 2.238621e-01
+## 1814 2.921657e-01 -1.333924e-01 4.013183e-02
+## 1815 2.873961e-01 -5.984973e-02 2.019551e-01
+## 1816 2.917780e-01 -9.825596e-02 2.952493e-02
+## 1817 2.884485e-01 -1.245588e-01 4.189005e-01
+## 1818 2.900406e-01 -1.035606e-01 3.094918e-02
+## 1819 1.393469e-01 -2.792066e-02 1.992720e-01
+## 1820 2.907285e-01 -7.420378e-02 2.477587e-01
+## 1821 4.903494e-01 -4.643560e-02 9.686677e-02
+## 1822 4.597195e-01 -2.506005e-01 1.133256e-01
+## 1823 3.522826e-01 -3.444861e-01 1.227449e-01
+## 1824 3.065567e-01 -4.855780e-01 1.526351e-01
+## 1825 3.244649e-01 -1.448021e-01 4.375811e-01
+## 1826 2.464139e-01 -3.736095e-01 9.592899e-02
+## 1827 1.699155e-01 -1.161319e-01 2.047335e-02
+## 1828 5.367122e-01 -5.019346e-02 2.613445e-02
+## 1829 2.909730e-01 -1.336178e-01 4.004938e-02
+## 1830 2.909730e-01 -1.336178e-01 4.004938e-02
+## 1831 2.925625e-01 -5.182650e-01 1.561166e-01
+## 1832 2.876021e-01 -5.433090e-02 1.832121e-01
+## 1833 1.700192e-01 -1.173057e-01 2.069407e-02
+## 1834 7.343808e-01 -6.951596e-02 9.862390e-02
+## 1835 2.877085e-01 -5.534006e-02 1.865517e-01
+## 1836 3.065562e-01 -1.387366e-01 4.360997e-02
+## 1837 2.948017e-01 -2.930305e-01 8.888683e-02
+## 1838 2.289438e-01 -2.340681e-01 5.600972e-02
+## 1839 2.898730e-01 -8.451258e-02 2.829414e-01
+## 1840 1.624140e-01 -1.424292e-02 8.493053e-02
+## 1841 2.922463e-01 -6.672515e-02 2.007969e-02
+## 1842 2.922463e-01 -6.672515e-02 2.007969e-02
+## 1843 2.340876e-01 -2.874210e-01 7.026788e-02
+## 1844 2.919483e-01 -6.533958e-02 1.964438e-02
+## 1845 3.046438e-01 -1.231189e-01 3.848126e-02
+## 1846 9.166660e-01 -6.175818e-02 6.872408e-02
+## 1847 6.514202e-01 -3.945568e-02 6.309446e-02
+## 1848 1.984263e-01 -1.604702e-01 3.331577e-02
+## 1849 2.981290e-01 -3.833718e-01 1.174883e-01
+## 1850 2.981290e-01 -3.833718e-01 1.174883e-01
+## 1851 3.065562e-01 -3.468415e-01 1.090249e-01
+## 1852 2.888427e-01 -6.037384e-02 2.027876e-01
+## 1853 2.880556e-01 -1.218824e-01 4.104123e-01
+## 1854 2.876010e-01 -3.395447e-02 1.145000e-01
+## 1855 2.876010e-01 -3.395447e-02 1.145000e-01
+## 1856 2.917780e-01 -6.550397e-02 1.968329e-02
+## 1857 2.917780e-01 -6.550397e-02 1.968329e-02
+## 1858 2.900406e-01 -6.904038e-02 2.063279e-02
+## 1859 2.900406e-01 -6.904038e-02 2.063279e-02
+## 1860 2.980489e-01 -3.479931e-01 1.066200e-01
+## 1861 2.929588e-01 -1.037736e-01 3.129838e-02
+## 1862 2.873620e-01 -8.675231e-02 2.927662e-01
+## 1863 2.840352e-01 -3.343979e-02 1.140641e-01
+## 1864 5.202235e-01 -1.159377e-01 2.291497e-01
+## 1865 3.046438e-01 -9.233919e-02 2.886095e-02
+## 1866 3.046438e-01 -9.233919e-02 2.886095e-02
+## 1867 3.144110e-01 -9.416647e-02 2.927763e-01
+## 1868 3.144110e-01 -9.416647e-02 2.927763e-01
+## 1869 2.881640e-01 -1.134089e-01 3.817477e-01
+## 1870 1.378016e-01 -1.637307e-02 1.184795e-01
+## 1871 2.873620e-01 -7.590827e-02 2.561704e-01
+## 1872 7.932529e-02 -1.215641e-01 6.720314e-03
+## 1873 2.920837e-01 -6.036994e-02 1.815795e-02
+## 1874 1.070372e-01 -1.129641e-02 1.158350e-01
+## 1875 5.810301e-01 -3.790070e-02 6.761012e-02
+## 1876 3.065562e-01 -2.427891e-01 7.631745e-02
+## 1877 3.065562e-01 -1.090249e-02 3.468415e-02
+## 1878 2.931264e-01 -2.117989e-01 6.391251e-02
+## 1879 2.903642e-01 -8.128550e-02 2.717157e-01
+## 1880 2.884485e-01 -5.661764e-02 1.904093e-01
+## 1881 6.960445e-01 -1.145017e-01 7.644223e-02
+## 1882 2.909730e-01 -6.680889e-02 2.002469e-02
+## 1883 2.860028e-01 -2.204826e-02 7.473160e-02
+## 1884 2.915169e-01 -2.069839e-01 6.214563e-02
+## 1885 2.929588e-01 -6.918242e-02 2.086559e-02
+## 1886 3.065562e-01 -6.541496e-02 2.081049e-01
+## 1887 3.065562e-01 -1.040525e-01 3.270748e-02
+## 1888 3.065562e-01 -2.081049e-01 6.541496e-02
+## 1889 1.194579e-01 -1.533008e-02 1.338164e-01
+## 1890 2.891739e-01 -1.137410e-02 3.816397e-02
+## 1891 2.947605e-01 -6.936820e-02 2.103922e-02
+## 1892 2.922456e-01 -3.336259e-02 1.003983e-02
+## 1893 2.922456e-01 -3.336259e-02 1.003983e-02
+## 1894 2.922456e-01 -3.336259e-02 1.003983e-02
+## 1895 2.931264e-01 -1.815419e-01 5.478215e-02
+## 1896 2.873273e-01 -2.207316e-02 7.449936e-02
+## 1897 2.873273e-01 -2.207316e-02 7.449936e-02
+## 1898 3.574319e-01 -2.662646e-02 7.376246e-02
+## 1899 3.065562e-01 -1.090249e-02 3.468415e-02
+## 1900 2.878221e-01 -2.167621e-02 7.304420e-02
+## 1901 2.914809e-01 -6.046161e-02 1.815117e-02
+## 1902 2.917780e-01 -3.275199e-02 9.841645e-03
+## 1903 2.907203e-01 -1.194458e-01 3.577313e-02
+## 1904 5.730844e-01 -8.155464e-02 4.513092e-02
+## 1905 3.065562e-01 -3.270748e-02 1.040525e-01
+## 1906 2.931880e-01 -6.881337e-02 2.076913e-02
+## 1907 2.861574e-01 -1.127190e-02 3.818667e-02
+## 1908 2.861574e-01 -1.127190e-02 3.818667e-02
+## 1909 2.912825e-01 -1.204036e-01 3.612384e-02
+## 1910 3.065562e-01 -2.180499e-02 6.936831e-02
+## 1911 2.987150e-01 -2.974173e-01 9.131006e-02
+## 1912 2.909722e-01 -3.340446e-02 1.001233e-02
+## 1913 2.909722e-01 -3.340446e-02 1.001233e-02
+## 1914 2.909722e-01 -3.340446e-02 1.001233e-02
+## 1915 2.909722e-01 -3.340446e-02 1.001233e-02
+## 1916 2.909722e-01 -3.340446e-02 1.001233e-02
+## 1917 2.909722e-01 -3.340446e-02 1.001233e-02
+## 1918 2.929588e-01 -3.459121e-02 1.043279e-02
+## 1919 2.929588e-01 -3.459121e-02 1.043279e-02
+## 1920 3.065562e-01 -3.468415e-02 1.090249e-02
+## 1921 3.065562e-01 -3.468415e-02 1.090249e-02
+## 1922 2.924037e-01 -3.335641e-02 1.004294e-02
+## 1923 2.947604e-01 -3.468411e-02 1.051961e-02
+## 1924 2.931264e-01 -9.077097e-02 2.739108e-02
+## 1925 2.898672e-01 -1.138451e-02 3.811512e-02
+## 1926 2.873273e-01 -1.103658e-02 3.724968e-02
+## 1927 2.867873e-01 -3.315160e-02 1.120837e-01
+## 1928 2.933680e-01 -3.465389e-02 1.046505e-02
+## 1929 2.987150e-01 -1.652318e-01 5.072781e-02
+## 1930 2.912825e-01 -6.020181e-02 1.806192e-02
+## 1931 2.980489e-01 -6.959861e-02 2.132401e-02
+## 1932 3.065562e-01 -1.090249e-02 3.468415e-02
+## 1933 2.913759e-01 -3.151055e-02 9.456657e-03
+## 1934 2.919417e-01 -6.534143e-02 1.964453e-02
+## 1935 3.218275e-01 -7.431796e-02 2.441240e-02
+## 1936 3.218275e-01 -7.431796e-02 2.441240e-02
+## 1937 2.916360e-01 -6.685707e-02 2.008093e-02
+## 1938 2.884485e-01 -1.132353e-02 3.808186e-02
+## 1939 3.092395e-01 -1.152447e-02 3.637390e-02
+## 1940 2.924391e-01 -8.664076e-01 2.608866e-01
+## 1941 2.875464e-01 -1.086544e-02 3.664642e-02
+## 1942 9.765692e-01 -3.644586e+06 3.755477e+06
+## 1943 5.207389e-05 -2.797166e+06 -9.715685e+05
+## 1944 3.916445e-02 -2.341973e+06 -5.967330e+04
+## 1945 5.084033e-03 1.827098e+06 1.033621e+07
+## 1946 3.647760e-02 2.225966e+05 6.853046e+06
+## 1947 2.366835e-04 -2.173755e+06 -6.619322e+05
+## 1948 3.841086e-01 -3.666534e+05 1.411540e+05
+## 1949 2.783559e-01 -7.546155e+04 2.622357e+05
+## 1950 4.884000e-01 -1.165248e+05 2.439566e+05
+## 1951 1.949898e-01 -3.212186e+05 1.575082e+06
+## 1952 7.900100e-01 -5.642372e+04 4.292530e+04
+## 1953 4.959926e-01 -5.767182e+04 2.793546e+04
+## 1954 3.726929e-01 -2.645872e+03 7.060634e+03
+## 1955 3.040548e-01 -5.411021e+05 1.688260e+05
+## 1956 5.314263e-02 -1.157338e+03 1.719730e+05
+## 1957 9.236906e-01 -2.540801e+04 2.304028e+04
+## 1958 1.816588e-01 -4.272321e+03 2.255327e+04
+## 1959 3.115679e-01 -9.072567e+03 2.844096e+04
+## 1960 5.696093e-01 -6.968803e+03 3.834528e+03
+## 1961 1.551429e-01 -3.581412e+04 2.249543e+05
+## 1962 9.889712e-02 -8.523224e+02 9.934283e+03
+## 1963 3.082336e-01 -1.566118e+05 4.957668e+05
+## 1964 5.694521e-01 -5.835504e+03 1.060808e+04
+## 1965 3.781748e-02 1.596771e+02 5.515689e+03
+## 1966 2.889204e-01 -2.354882e+03 7.907780e+03
+## 1967 3.644554e-01 -1.037478e+03 2.824461e+03
+## 1968 4.722862e-01 -1.029845e+03 2.222588e+03
+## 1969 3.546039e-01 -5.032669e+03 1.803791e+03
+## 1970 8.926165e-01 -1.746238e+03 1.521191e+03
+## 1971 1.362950e-01 -6.017019e+03 8.201887e+02
+## 1972 9.493297e-01 -3.376417e+03 3.164344e+03
+## 1973 7.362065e-01 -6.339136e+03 8.970591e+03
+## 1974 7.167151e-01 -6.407373e+03 9.318793e+03
+## 1975 2.855241e-01 -1.372219e+04 4.042268e+03
+## 1976 7.311700e-01 -1.980706e+03 1.389865e+03
+## 1977 3.127365e-01 -2.931981e+04 9.160130e+04
+## 1978 7.933767e-02 -1.461260e+04 8.081152e+02
+## 1979 5.640840e-01 -5.698521e+03 3.107152e+03
+## 1980 3.289897e-01 -2.501415e+03 7.465282e+03
+## 1981 6.944539e-01 -4.541174e+03 6.817740e+03
+## 1982 3.244179e-01 -4.877136e+03 1.474026e+04
+## 1983 4.044203e-01 -1.804478e+03 4.476248e+03
+## 1984 8.387525e-01 -2.130475e+03 1.729700e+03
+## 1985 3.181673e-01 -2.655564e+03 8.633453e+02
+## 1986 2.651449e-01 -3.046460e+03 8.379993e+02
+## 1987 7.748537e-01 -7.055544e+03 5.258470e+03
+## 1988 3.909326e-02 1.704270e+02 6.641392e+03
+## 1989 7.630582e-01 -2.295863e+03 3.130508e+03
+## 1990 6.484433e-01 -8.354400e+02 1.341941e+03
+## 1991 3.818771e-01 -1.427084e+04 5.465446e+03
+## 1992 2.819052e-01 -1.046364e+03 3.593985e+03
+## 1993 3.868115e-01 -9.395117e+03 3.639663e+03
+## 1994 3.095446e-01 -1.128932e+04 3.580037e+03
+## 1995 2.890084e-01 -2.284014e+03 7.667663e+03
+## 1996 1.040263e-01 -9.955969e+02 1.067771e+04
+## 1997 5.964374e-01 -1.129820e+04 6.491807e+03
+## 1998 2.504204e-01 -2.699974e+02 1.035609e+03
+## 1999 3.228148e-01 -5.918080e+02 1.796648e+03
+## 2000 5.828002e-01 -6.457035e+03 3.630035e+03
+## 2001 8.495713e-01 -8.670177e+02 7.140209e+02
+## 2002 2.665002e-01 -2.262192e+03 8.184993e+03
+## 2003 1.346548e-01 -2.396710e+03 1.785236e+04
+## 2004 5.172353e-02 -4.088820e+01 1.098519e+04
+## 2005 2.548243e-01 -7.170481e+04 1.900422e+04
+## 2006 9.205679e-02 -9.088367e+01 1.203104e+03
+## 2007 3.177582e-01 -2.204401e+03 7.158348e+02
+## 2008 2.084910e-01 -6.208866e+03 1.355042e+03
+## 2009 1.005320e-01 -8.239558e+01 9.342892e+02
+## 2010 5.257857e-01 -2.103775e+03 1.074838e+03
+## 2011 6.881615e-01 -7.995960e+02 1.211397e+03
+## 2012 1.824945e-01 -2.758831e+03 5.251542e+02
+## 2013 2.753033e-01 -1.132830e+04 3.977001e+04
+## 2014 9.016676e-01 -5.072179e+02 5.754699e+02
+## 2015 1.268586e-01 -6.865670e+02 5.523779e+03
+## 2016 8.930167e-02 -6.465380e+01 9.068542e+02
+## 2017 1.527593e-01 -1.309351e+03 2.047609e+02
+## 2018 2.042484e-01 -6.027901e+02 2.819593e+03
+## 2019 5.136293e-01 -8.102723e+02 1.620313e+03
+## 2020 2.255138e-01 -1.450708e+03 3.420858e+02
+## 2021 8.737346e-01 -9.386681e+01 1.104316e+02
+## 2022 1.235176e-01 -2.139949e+02 1.784260e+03
+## 2023 1.588164e-01 -7.113285e+02 4.350123e+03
+## 2024 4.966282e-02 6.714015e-01 9.104822e+02
+## 2025 4.432891e-01 -7.837143e+02 1.790718e+03
+## 2026 2.365029e-01 -2.105031e+03 8.525820e+03
+## 2027 4.369639e-01 -3.976852e+02 9.204723e+02
+## 2028 1.558231e-01 -6.016027e+03 9.626134e+02
+## 2029 5.307125e-01 -4.040427e+02 7.840778e+02
+## 2030 1.317452e-01 -7.188066e+02 9.385327e+01
+## 2031 7.865765e-01 -1.236027e+02 1.632267e+02
+## 2032 2.408817e-02 -5.803498e+02 -4.071508e+01
+## 2033 5.757836e-01 -7.458546e+02 4.145643e+02
+## 2034 2.957414e-01 -2.741566e+04 8.340383e+03
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+## 2036 5.885419e-01 -5.782461e+02 1.019119e+03
+## 2037 3.235223e-02 7.749813e+01 1.764572e+03
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+## 2522 2.740909e-01 -8.920310e+00 2.530552e+00
+## 2523 3.797162e-01 -8.888653e-01 2.332720e+00
+## 2524 5.331160e-01 -2.090705e-01 1.081851e-01
+## 2525 3.039239e-01 -6.967674e+01 2.173091e+01
+## 2526 3.069202e-01 -2.340539e+01 7.437945e+01
+## 2527 3.034915e-01 -4.994522e+01 1.555685e+01
+## 2528 3.899467e-01 -3.076066e+01 1.200294e+01
+## 2529 2.991075e-01 -1.785184e+00 5.807786e+00
+## 2530 2.956566e-01 -9.131251e+00 2.777179e+00
+## 2531 3.036318e-01 -1.322580e+01 4.244356e+01
+## 2532 3.043487e-01 -4.529623e+00 1.450508e+01
+## 2533 5.331160e-01 -1.254423e+00 6.491108e-01
+## 2534 3.797162e-01 -3.809423e-01 9.997369e-01
+## 2535 3.797162e-01 -7.618846e-01 1.999474e+00
+## 2536 1.453663e-01 -5.592896e+00 3.791792e+01
+## 2537 3.048948e-01 -6.790498e+00 2.123984e+00
+## 2538 3.018081e-01 -6.251525e+00 2.017237e+01
+## 2539 3.074068e-01 -7.947992e-01 2.522143e+00
+## 2540 3.074068e-01 -7.947992e-01 2.522143e+00
+## 2541 3.074068e-01 -7.947992e-01 2.522143e+00
+## 2542 3.039239e-01 -5.972292e+01 1.862649e+01
+## 2543 3.001945e-01 -7.601658e+00 2.344319e+00
+## 2544 3.001945e-01 -7.601658e+00 2.344319e+00
+## 2545 7.463003e-01 -1.273426e+01 9.125910e+00
+## 2546 5.331160e-01 -2.090705e-01 1.081851e-01
+## 2547 3.490059e-01 -1.446496e+00 5.111055e-01
+## 2548 3.045793e-01 -1.951882e+01 6.099503e+00
+## 2549 8.876889e-01 -8.602810e-02 7.446355e-02
+## 2550 2.960774e-01 -4.418252e+01 1.345514e+01
+## 2551 2.096883e-01 -3.242044e+01 7.116115e+00
+## 2552 5.331160e-01 -6.272114e-01 3.245554e-01
+## 2553 3.079307e-01 -4.090107e+00 1.295912e+01
+## 2554 2.999555e-01 -7.378491e+00 2.273844e+00
+## 2555 2.999555e-01 -7.378491e+00 2.273844e+00
+## 2556 3.023767e-01 -4.135536e+01 1.283822e+01
+## 2557 5.331160e-01 -4.181409e-01 2.163703e-01
+## 2558 6.265232e-01 -1.304239e+00 7.854131e-01
+## 2559 2.991051e-01 -8.925870e-01 2.903897e+00
+## 2560 2.991051e-01 -8.925870e-01 2.903897e+00
+## 2561 2.991051e-01 -8.925870e-01 2.903897e+00
+## 2562 2.991051e-01 -8.925870e-01 2.903897e+00
+## 2563 2.991051e-01 -8.925870e-01 2.903897e+00
+## 2564 2.991051e-01 -8.925870e-01 2.903897e+00
+## 2565 3.043487e-01 -2.264811e+00 7.252542e+00
+## 2566 3.043487e-01 -2.264811e+00 7.252542e+00
+## 2567 3.797162e-01 -1.269808e-01 3.332456e-01
+## 2568 3.797162e-01 -1.269808e-01 3.332456e-01
+## 2569 3.114705e-01 -8.010450e-01 2.511852e+00
+## 2570 3.018080e-01 -3.125762e+00 1.008618e+01
+## 2571 3.039239e-01 -2.986146e+01 9.313246e+00
+## 2572 3.042875e-01 -9.797769e+00 3.059071e+00
+## 2573 3.001945e-01 -3.800829e+00 1.172160e+00
+## 2574 2.983713e-01 -1.315893e+01 4.035683e+00
+## 2575 3.053218e-01 -3.174999e+00 1.013774e+01
+## 2576 6.265232e-01 -7.245771e-01 4.363406e-01
+## 2577 3.023767e-01 -2.067768e+01 6.419112e+00
+## 2578 3.041356e-01 -6.189213e+00 1.983218e+01
+## 2579 5.331160e-01 -2.090705e-01 1.081851e-01
+## 2580 3.039722e-01 -6.729133e+00 2.098997e+00
+## 2581 3.172133e-01 -8.681926e-01 2.814908e-01
+## 2582 3.908976e-01 -2.761793e-01 7.062429e-01
+## 2583 3.908976e-01 -2.761793e-01 7.062429e-01
+## 2584 3.029075e-01 -1.808861e+00 5.817530e+00
+## 2585 3.034915e-01 -9.989044e+00 3.111370e+00
+## 2586 2.964672e-01 -1.825374e+00 5.986770e+00
+## 2587 3.110974e-01 -1.929098e+01 6.055685e+01
+## 2588 3.025699e-01 -1.294452e+00 4.020794e-01
+## Taxon Adj p-value
+## 1 Dolosigranulum 1.00000000
+## 2 Streptococcus 1.00000000
+## 3 Moraxella 1.00000000
+## 4 Staphylococcus 1.00000000
+## 5 Corynebacterium 1.00000000
+## 6 Haemophilus 1.00000000
+## 7 Anaerobacillus 1.00000000
+## 8 Paracoccus 1.00000000
+## 9 Acinetobacter 1.00000000
+## 10 Pseudomonas 1.00000000
+## 11 Alkalihalophilus 1.00000000
+## 12 Delftia 1.00000000
+## 13 Noviherbaspirillum 1.00000000
+## 14 Weissella 1.00000000
+## 15 Escherichia 1.00000000
+## 16 Brucella 1.00000000
+## 17 Aeromonas 1.00000000
+## 18 Mycoplasma 1.00000000
+## 19 Kocuria 1.00000000
+## 20 Enterobacter 1.00000000
+## 21 Cutibacterium 1.00000000
+## 22 Listeria 1.00000000
+## 23 Micrococcus 1.00000000
+## 24 Sphingomonas 1.00000000
+## 25 Knoellia 1.00000000
+## 26 Finegoldia 1.00000000
+## 27 Peptoniphilus 1.00000000
+## 28 Ornithinimicrobium 1.00000000
+## 29 Nocardioides 1.00000000
+## 30 Agrobacterium 1.00000000
+## 31 Neisseria 1.00000000
+## 32 Janibacter 1.00000000
+## 33 Alkalihalobacillus 1.00000000
+## 34 Halolactibacillus 1.00000000
+## 35 Anaerococcus 1.00000000
+## 36 Bifidobacterium 1.00000000
+## 37 Bacillus 1.00000000
+## 38 Exiguobacterium 1.00000000
+## 39 Marmoricola 1.00000000
+## 40 Brachybacterium 1.00000000
+## 41 Salinicoccus 1.00000000
+## 42 Halomonas 1.00000000
+## 43 Suttonella 1.00000000
+## 44 Microvirga 1.00000000
+## 45 Rothia 1.00000000
+## 46 Planococcus 1.00000000
+## 47 Herbaspirillum 1.00000000
+## 48 Psychrobacter 1.00000000
+## 49 Dietzia 1.00000000
+## 50 Veillonella 1.00000000
+## 51 Alishewanella 1.00000000
+## 52 Glaesserella 1.00000000
+## 53 Helcococcus 1.00000000
+## 54 Paenisporosarcina 1.00000000
+## 55 Serinicoccus 1.00000000
+## 56 Gemella 1.00000000
+## 57 Rubellimicrobium 1.00000000
+## 58 Lysobacter 1.00000000
+## 59 Variovorax 1.00000000
+## 60 Tessaracoccus 1.00000000
+## 61 Stenotrophomonas 1.00000000
+## 62 Ligilactobacillus 1.00000000
+## 63 Klebsiella 1.00000000
+## 64 Fusobacterium 1.00000000
+## 65 Campylobacter 1.00000000
+## 66 Gordonia 1.00000000
+## 67 Alkalihalobacterium 1.00000000
+## 68 Brevibacterium 1.00000000
+## 69 Pseudarthrobacter 1.00000000
+## 70 Jeotgalicoccus 1.00000000
+## 71 Neobacillus 1.00000000
+## 72 Enterococcus 1.00000000
+## 73 Haematobacter 1.00000000
+## 74 Comamonas 1.00000000
+## 75 Kaistella 1.00000000
+## 76 Aeribacillus 1.00000000
+## 77 Bradyrhizobium 1.00000000
+## 78 Shewanella 1.00000000
+## 79 Domibacillus 1.00000000
+## 80 Aquimonas 1.00000000
+## 81 Cytobacillus 1.00000000
+## 82 Thalassospira 1.00000000
+## 83 Citrobacter 1.00000000
+## 84 Rhodococcus 1.00000000
+## 85 Pantoea 1.00000000
+## 86 Arthrobacter 1.00000000
+## 87 Granulicatella 1.00000000
+## 88 Piscicoccus 1.00000000
+## 89 Aerococcus 1.00000000
+## 90 Actinotalea 1.00000000
+## 91 Priestia 1.00000000
+## 92 Metabacillus 1.00000000
+## 93 Pluralibacter 1.00000000
+## 94 Negativicoccus 1.00000000
+## 95 Proteus 1.00000000
+## 96 Flavisolibacter 1.00000000
+## 97 Halopseudomonas 1.00000000
+## 98 Nosocomiicoccus 1.00000000
+## 99 Streptomyces 1.00000000
+## 100 Planomicrobium 1.00000000
+## 101 Pusillimonas_(ex_Stolz_et_al._2005) 1.00000000
+## 102 Pedococcus 1.00000000
+## 103 Eremococcus 1.00000000
+## 104 Massilia 1.00000000
+## 105 Novosphingobium 1.00000000
+## 106 Ruminococcus 1.00000000
+## 107 Blastococcus 1.00000000
+## 108 Cellulomonas 1.00000000
+## 109 Pontibacter 1.00000000
+## 110 Gardnerella 1.00000000
+## 111 Anoxybacillus 1.00000000
+## 112 Lawsonella 1.00000000
+## 113 Obesumbacterium 1.00000000
+## 114 Epilithonimonas 1.00000000
+## 115 Tepidimonas 1.00000000
+## 116 Flavobacterium 1.00000000
+## 117 Glutamicibacter 1.00000000
+## 118 Prevotella 1.00000000
+## 119 Phycicoccus 1.00000000
+## 120 Geodermatophilus 1.00000000
+## 121 Limosilactobacillus 1.00000000
+## 122 Sphaerobacter 1.00000000
+## 123 Schinkia 1.00000000
+## 124 Mediterraneibacter 1.00000000
+## 125 Alkalibacterium 1.00000000
+## 126 Fenollaria 1.00000000
+## 127 Bosea 1.00000000
+## 128 Lautropia 1.00000000
+## 129 Pseudostreptobacillus 1.00000000
+## 130 Nissabacter 1.00000000
+## 131 Luteimonas 1.00000000
+## 132 Globicatella 1.00000000
+## 133 Thauera 1.00000000
+## 134 Microbacterium 1.00000000
+## 135 Archangium 1.00000000
+## 136 Enterocloster 1.00000000
+## 137 Leptothrix 1.00000000
+## 138 Dyadobacter 1.00000000
+## 139 Lactobacillus 1.00000000
+## 140 Rhizorhabdus 1.00000000
+## 141 Azospirillum 1.00000000
+## 142 Acidovorax 1.00000000
+## 143 Aeromicrobium 1.00000000
+## 144 Paenarthrobacter 1.00000000
+## 145 Deinococcus 1.00000000
+## 146 Burkholderia 1.00000000
+## 147 Clostridium 1.00000000
+## 148 Aquabacterium 1.00000000
+## 149 Aquincola 1.00000000
+## 150 Macrococcus 1.00000000
+## 151 Rheinheimera 1.00000000
+## 152 Aliarcobacter 1.00000000
+## 153 Collinsella 1.00000000
+## 154 Brochothrix 1.00000000
+## 155 Caulobacter 1.00000000
+## 156 Niallia 1.00000000
+## 157 Brevundimonas 1.00000000
+## 158 Desnuesiella 1.00000000
+## 159 Rubrobacter 1.00000000
+## 160 Pediococcus 1.00000000
+## 161 Mycolicibacterium 1.00000000
+## 162 Fimbriimonas 1.00000000
+## 163 Tsuneonella 1.00000000
+## 164 Methylobacterium 1.00000000
+## 165 Lactococcus 1.00000000
+## 166 Devosia 1.00000000
+## 167 Leptotrichia 1.00000000
+## 168 Chishuiella 1.00000000
+## 169 Pseudorhizobium 1.00000000
+## 170 Cloacibacterium 1.00000000
+## 171 Abyssicoccus 1.00000000
+## 172 Pseudoxanthomonas 1.00000000
+## 173 Thermoactinomyces 1.00000000
+## 174 Megamonas 1.00000000
+## 175 Methylibium 1.00000000
+## 176 Beutenbergia 1.00000000
+## 177 Vibrio 1.00000000
+## 178 Schaalia 1.00000000
+## 179 Jeotgalibacillus 1.00000000
+## 180 Afipia 1.00000000
+## 181 Bryobacter 1.00000000
+## 182 Bacteroides 1.00000000
+## 183 Qipengyuania 1.00000000
+## 184 Mesobacillus 1.00000000
+## 185 Capnocytophaga 1.00000000
+## 186 Gemmatimonas 1.00000000
+## 187 Mesorhizobium 1.00000000
+## 188 Kallipyga 1.00000000
+## 189 Arenimonas 1.00000000
+## 190 Sphingobium 1.00000000
+## 191 Megasphaera 1.00000000
+## 192 Erythrobacter 1.00000000
+## 193 Youngiibacter 1.00000000
+## 194 Mucilaginibacter 1.00000000
+## 195 Rufibacter 1.00000000
+## 196 Methylorubrum 1.00000000
+## 197 Sphingobacterium 1.00000000
+## 198 Ferrimicrobium 1.00000000
+## 199 Flaviflexus 1.00000000
+## 200 Solibacillus 1.00000000
+## 201 Phocaeicola 1.00000000
+## 202 Paeniglutamicibacter 1.00000000
+## 203 Achromobacter 1.00000000
+## 204 Latilactobacillus 1.00000000
+## 205 Nakamurella 1.00000000
+## 206 Legionella 1.00000000
+## 207 Cellvibrio 1.00000000
+## 208 Leuconostoc 1.00000000
+## 209 Viridibacillus 1.00000000
+## 210 Leucobacter 1.00000000
+## 211 Propionicicella 1.00000000
+## 212 Oerskovia 1.00000000
+## 213 Catenibacterium 1.00000000
+## 214 Saccharopolyspora 1.00000000
+## 215 Paramesorhizobium 1.00000000
+## 216 Silanimonas 1.00000000
+## 217 Blautia 1.00000000
+## 218 Lancefieldella 1.00000000
+## 219 Mageeibacillus 1.00000000
+## 220 Fimbriiglobus 1.00000000
+## 221 Croceibacterium 1.00000000
+## 222 Gemmobacter 1.00000000
+## 223 Curvibacter 1.00000000
+## 224 Ensifer 1.00000000
+## 225 Mammaliicoccus 1.00000000
+## 226 Halarcobacter 1.00000000
+## 227 Janthinobacterium 1.00000000
+## 228 Belnapia 1.00000000
+## 229 Pseudidiomarina 1.00000000
+## 230 Nitratireductor 1.00000000
+## 231 Schlegelella 1.00000000
+## 232 Erysipelatoclostridium 1.00000000
+## 233 Phenylobacterium 1.00000000
+## 234 Luteipulveratus 1.00000000
+## 235 Daejeonella 1.00000000
+## 236 Ezakiella 1.00000000
+## 237 Nigerium 1.00000000
+## 238 Peribacillus 1.00000000
+## 239 Alloiococcus 1.00000000
+## 240 Trichococcus 1.00000000
+## 241 Buttiauxella 1.00000000
+## 242 Saccharothrix 1.00000000
+## 243 Intestinibacter 1.00000000
+## 244 Rodentibacter 1.00000000
+## 245 Brevibacillus 1.00000000
+## 246 Liquorilactobacillus 1.00000000
+## 247 Nonomuraea 1.00000000
+## 248 Thioclava 1.00000000
+## 249 Pimelobacter 1.00000000
+## 250 Scytonema 1.00000000
+## 251 Geosporobacter 1.00000000
+## 252 Kushneria 1.00000000
+## 253 Eubacterium 1.00000000
+## 254 Catonella 1.00000000
+## 255 Roseomonas 1.00000000
+## 256 Aggregatibacter 1.00000000
+## 257 Geobacter 1.00000000
+## 258 Xenophilus 1.00000000
+## 259 Flavihumibacter 1.00000000
+## 260 Akkermansia 1.00000000
+## 261 Acetobacter 1.00000000
+## 262 Altererythrobacter 1.00000000
+## 263 Pseudonocardia 1.00000000
+## 264 Fructobacillus 1.00000000
+## 265 Peptostreptococcus 1.00000000
+## 266 Rubrivivax 1.00000000
+## 267 Ciceribacter 1.00000000
+## 268 Desulfuromonas 1.00000000
+## 269 Pseudoglutamicibacter 1.00000000
+## 270 Fictibacillus 1.00000000
+## 271 Porphyromonas 1.00000000
+## 272 Caldilinea 1.00000000
+## 273 Stomatobaculum 1.00000000
+## 274 Pelagerythrobacter 1.00000000
+## 275 Marinilactibacillus 1.00000000
+## 276 Kluyvera 1.00000000
+## 277 Abiotrophia 1.00000000
+## 278 Acidisphaera 1.00000000
+## 279 Pelomonas 1.00000000
+## 280 Kytococcus 1.00000000
+## 281 Actinomyces 1.00000000
+## 282 Carnobacterium 1.00000000
+## 283 Robertmurraya 1.00000000
+## 284 Micromonospora 1.00000000
+## 285 Paucilactobacillus 1.00000000
+## 286 Agrococcus 1.00000000
+## 287 Chryseobacterium 1.00000000
+## 288 Lysinibacillus 1.00000000
+## 289 Demequina 1.00000000
+## 290 Sphaerochaeta 1.00000000
+## 291 Riemerella 1.00000000
+## 292 Amphibacillus 1.00000000
+## 293 Nesterenkonia 1.00000000
+## 294 Tenacibaculum 1.00000000
+## 295 Wenxinia 1.00000000
+## 296 Pyrinomonas 1.00000000
+## 297 Asanoa 1.00000000
+## 298 Sandaracinus 1.00000000
+## 299 Nocardia 1.00000000
+## 300 Dermabacter 1.00000000
+## 301 Cronobacter 1.00000000
+## 302 Ornatilinea 1.00000000
+## 303 Solirubrum 1.00000000
+## 304 Cereibacter 1.00000000
+## 305 Rossellomorea 1.00000000
+## 306 Thermanaerothrix 1.00000000
+## 307 Solirubrobacter 1.00000000
+## 308 Raineyella 1.00000000
+## 309 Azotobacter 1.00000000
+## 310 Ramlibacter 1.00000000
+## 311 Aquamicrobium 1.00000000
+## 312 Faecalibacterium 1.00000000
+## 313 Pararheinheimera 1.00000000
+## 314 Chondromyces 1.00000000
+## 315 Marinobacter 1.00000000
+## 316 Ralstonia 1.00000000
+## 317 Sphingopyxis 1.00000000
+## 318 Halalkalibacterium_(ex_Joshi_et_al._2022) 1.00000000
+## 319 Salinimicrobium 1.00000000
+## 320 Gillisia 1.00000000
+## 321 Hyphomicrobium 1.00000000
+## 322 Immundisolibacter 1.00000000
+## 323 Methylovorus 1.00000000
+## 324 Pedobacter 1.00000000
+## 325 Aequorivita 1.00000000
+## 326 Aureimonas 1.00000000
+## 327 Kurthia 1.00000000
+## 328 Methylocystis 1.00000000
+## 329 Snodgrassella 1.00000000
+## 330 Hymenobacter 1.00000000
+## 331 Bergeyella 1.00000000
+## 332 Paenibacillus 1.00000000
+## 333 Alkanindiges 1.00000000
+## 334 Aromatoleum 1.00000000
+## 335 Pseudoalteromonas 1.00000000
+## 336 Auraticoccus 1.00000000
+## 337 Dorea 1.00000000
+## 338 Facklamia 1.00000000
+## 339 Tolumonas 1.00000000
+## 340 Geobacillus 1.00000000
+## 341 Ilumatobacter 1.00000000
+## 342 Palleronia 1.00000000
+## 343 Lachnoclostridium 1.00000000
+## 344 Trueperella 1.00000000
+## 345 Rhodopseudomonas 1.00000000
+## 346 Kingella 1.00000000
+## 347 Terribacillus 1.00000000
+## 348 Fannyhessea 1.00000000
+## 349 Rudanella 1.00000000
+## 350 Lactiplantibacillus 1.00000000
+## 351 Rickettsia 1.00000000
+## 352 Methylophilus 1.00000000
+## 353 Algoriphagus 1.00000000
+## 354 Sanguibacteroides 1.00000000
+## 355 Ureaplasma 1.00000000
+## 356 Rubritepida 1.00000000
+## 357 Azoarcus 1.00000000
+## 358 Pseudooctadecabacter 1.00000000
+## 359 Cupriavidus 1.00000000
+## 360 Oceanospirillum 1.00000000
+## 361 Anaeromyxobacter 1.00000000
+## 362 Oscillatoria 1.00000000
+## 363 Salmonella 1.00000000
+## 364 Cellulosimicrobium 1.00000000
+## 365 Jannaschia 1.00000000
+## 366 Curtobacterium 1.00000000
+## 367 Alcanivorax 1.00000000
+## 368 Conexibacter 1.00000000
+## 369 Atopostipes 1.00000000
+## 370 Salegentibacter 1.00000000
+## 371 Acetivibrio 1.00000000
+## 372 Leifsonia 1.00000000
+## 373 Pseudorhodoplanes 1.00000000
+## 374 Agarivorans 1.00000000
+## 375 Hydrogenophaga 1.00000000
+## 376 Krasilnikoviella 1.00000000
+## 377 Rickettsiella 1.00000000
+## 378 Bellilinea 1.00000000
+## 379 Romboutsia 1.00000000
+## 380 Skermanella 1.00000000
+## 381 Morganella 1.00000000
+## 382 Nioella 1.00000000
+## 383 Simiduia 1.00000000
+## 384 Frankia 1.00000000
+## 385 Myxococcus 1.00000000
+## 386 Serratia 1.00000000
+## 387 Virgibacillus 1.00000000
+## 388 Avibacterium 1.00000000
+## 389 Marinomonas 1.00000000
+## 390 Turicibacter 1.00000000
+## 391 Merdimonas 1.00000000
+## 392 Diaphorobacter 1.00000000
+## 393 Acidithrix 1.00000000
+## 394 Tolypothrix 1.00000000
+## 395 Buchnera 1.00000000
+## 396 Margalitia 1.00000000
+## 397 Sarcina 1.00000000
+## 398 Lacticaseibacillus 1.00000000
+## 399 Pedosphaera 1.00000000
+## 400 Allgaiera 1.00000000
+## 401 Lacrimispora 1.00000000
+## 402 Erwinia 1.00000000
+## 403 Gulosibacter 1.00000000
+## 404 Parabacteroides 1.00000000
+## 405 Castellaniella 1.00000000
+## 406 Sutcliffiella 1.00000000
+## 407 Ruminobacter 1.00000000
+## 408 Vagococcus 1.00000000
+## 409 Ketogulonicigenium 1.00000000
+## 410 Aestuariimicrobium 1.00000000
+## 411 Nitriliruptor 1.00000000
+## 412 Dokdonella 1.00000000
+## 413 Williamsia 1.00000000
+## 414 Rhizobium 1.00000000
+## 415 Modestobacter 1.00000000
+## 416 Colwellia 1.00000000
+## 417 Holdemanella 1.00000000
+## 418 Caldimonas 1.00000000
+## 419 Phascolarctobacterium 1.00000000
+## 420 Neomicrococcus 1.00000000
+## 421 Hyalangium 1.00000000
+## 422 Brevefilum 1.00000000
+## 423 Sporosarcina 1.00000000
+## 424 Geminicoccus 1.00000000
+## 425 Falsiruegeria 1.00000000
+## 426 Oceanibacterium 1.00000000
+## 427 Allorhizobium 1.00000000
+## 428 Pseudoclavibacter 1.00000000
+## 429 Rhizobacter 1.00000000
+## 430 Patulibacter 1.00000000
+## 431 Roseburia 1.00000000
+## 432 Herbiconiux 1.00000000
+## 433 Nitrospira 1.00000000
+## 434 Cryobacterium 1.00000000
+## 435 Oceanobacillus 1.00000000
+## 436 Gemmata 1.00000000
+## 437 Rhodoferax 1.00000000
+## 438 Chromohalobacter 1.00000000
+## 439 Kitasatospora 1.00000000
+## 440 Verrucomicrobium 1.00000000
+## 441 Aphanizomenon 1.00000000
+## 442 Senegalimassilia 1.00000000
+## 443 Tepidibacter 1.00000000
+## 444 Plesiocystis 1.00000000
+## 445 Nitrosospira 1.00000000
+## 446 Yaniella 1.00000000
+## 447 Subdoligranulum 1.00000000
+## 448 Spirosoma 1.00000000
+## 449 Pseudoflavonifractor 1.00000000
+## 450 Metaplanococcus 1.00000000
+## 451 Sinorhizobium 1.00000000
+## 452 Fredinandcohnia 1.00000000
+## 453 Alcaligenes 1.00000000
+## 454 Thermoleophilum 1.00000000
+## 455 Oceanicella 1.00000000
+## 456 Thiolapillus 1.00000000
+## 457 Pseudobdellovibrio 1.00000000
+## 458 Plantibacter 1.00000000
+## 459 Thermus 1.00000000
+## 460 Quasibacillus 1.00000000
+## 461 Cesiribacter 1.00000000
+## 462 Sulfitobacter 1.00000000
+## 463 Plesiomonas 1.00000000
+## 464 Promicromonospora 1.00000000
+## 465 Streptacidiphilus 1.00000000
+## 466 Perlucidibaca 1.00000000
+## 467 Kutzneria 1.00000000
+## 468 Sanguibacter 1.00000000
+## 469 Oceaniovalibus 1.00000000
+## 470 Neosynechococcus 1.00000000
+## 471 Selenomonas 1.00000000
+## 472 Alloprevotella 1.00000000
+## 473 Providencia 1.00000000
+## 474 Dialister 1.00000000
+## 475 Siminovitchia 1.00000000
+## 476 Aliivibrio 1.00000000
+## 477 Aquimixticola 1.00000000
+## 478 Chitinimonas 1.00000000
+## 479 Pleomorphomonas 1.00000000
+## 480 Hyphomonas 1.00000000
+## 481 Caenibius 1.00000000
+## 482 Spirillospora 1.00000000
+## 483 Edaphobacter 1.00000000
+## 484 Geminisphaera 1.00000000
+## 485 Chloroflexus 1.00000000
+## 486 Fervidicola 1.00000000
+## 487 Cloacibacillus 1.00000000
+## 488 Desulfovibrio 1.00000000
+## 489 Oligella 1.00000000
+## 490 Adhaeribacter 1.00000000
+## 491 Lentzea 1.00000000
+## 492 Chthoniobacter 1.00000000
+## 493 Rhodoluna 1.00000000
+## 494 Kineococcus 1.00000000
+## 495 Mobilicoccus 1.00000000
+## 496 Oceanisphaera 1.00000000
+## 497 Lentilactobacillus 1.00000000
+## 498 Methylomonas 1.00000000
+## 499 Halobacillus 1.00000000
+## 500 Rhodovibrio 1.00000000
+## 501 Pelagibacterium 1.00000000
+## 502 Gottschalkia 1.00000000
+## 503 Actinokineospora 1.00000000
+## 504 Thalassobacillus 1.00000000
+## 505 Stigmatella 1.00000000
+## 506 Steroidobacter 1.00000000
+## 507 Pirellula 1.00000000
+## 508 Canicola 1.00000000
+## 509 Desulfonatronum 1.00000000
+## 510 Thermosinus 1.00000000
+## 511 Blastochloris 1.00000000
+## 512 Thermomonas 1.00000000
+## 513 Kerstersia 1.00000000
+## 514 Intrasporangium 1.00000000
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+## 1864 Roseateles 1.00000000
+## 1865 Dactylosporangium 1.00000000
+## 1866 Jonesia 1.00000000
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+## 1869 Tissierella 1.00000000
+## 1870 Microlunatus 1.00000000
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+## 1877 Roseivivax 1.00000000
+## 1878 Dolosicoccus 1.00000000
+## 1879 Yokenella 1.00000000
+## 1880 Melissococcus 1.00000000
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+## 1883 Lampropedia 1.00000000
+## 1884 Mycobacterium 1.00000000
+## 1885 Maricaulis 1.00000000
+## 1886 Oribacterium 1.00000000
+## 1887 Planctopirus 1.00000000
+## 1888 Ruania 1.00000000
+## 1889 Cedecea 1.00000000
+## 1890 Rahnella 1.00000000
+## 1891 Jeotgalibaca 1.00000000
+## 1892 Edwardsiella 1.00000000
+## 1893 Mycoplasmopsis 1.00000000
+## 1894 Pseudaminobacter 1.00000000
+## 1895 Bibersteinia 1.00000000
+## 1896 Kribbia 1.00000000
+## 1897 Salinarimonas 1.00000000
+## 1898 Shimwellia 1.00000000
+## 1899 Bordetella 1.00000000
+## 1900 Neofamilia 1.00000000
+## 1901 Lentibacillus 1.00000000
+## 1902 Thiohalomonas 1.00000000
+## 1903 Paeniclostridium 1.00000000
+## 1904 Actinobacillus 1.00000000
+## 1905 Salinibacillus 1.00000000
+## 1906 Terrisporobacter 1.00000000
+## 1907 Heyndrickxia 1.00000000
+## 1908 Lederbergia 1.00000000
+## 1909 Caldalkalibacillus 1.00000000
+## 1910 Beijerinckia 1.00000000
+## 1911 Agromyces 1.00000000
+## 1912 Hydrogenoanaerobacterium 1.00000000
+## 1913 Massilioclostridium 1.00000000
+## 1914 Pasteurella 1.00000000
+## 1915 Rhodopirellula 1.00000000
+## 1916 Saccharomonospora 1.00000000
+## 1917 Wolbachia 1.00000000
+## 1918 Afifella 1.00000000
+## 1919 Ardenticatena 1.00000000
+## 1920 Companilactobacillus 1.00000000
+## 1921 Paraburkholderia 1.00000000
+## 1922 Azospira 1.00000000
+## 1923 Barnesiella 1.00000000
+## 1924 Marivita 1.00000000
+## 1925 Altibacter 1.00000000
+## 1926 Dysgonomonas 1.00000000
+## 1927 Neorhizobium 1.00000000
+## 1928 Tumebacillus 1.00000000
+## 1929 Nitrosovibrio 1.00000000
+## 1930 Glycomyces 1.00000000
+## 1931 Salinicola 1.00000000
+## 1932 Methylosinus 1.00000000
+## 1933 Xylophilus 1.00000000
+## 1934 Fusicatenibacter 1.00000000
+## 1935 Azovibrio 1.00000000
+## 1936 Geotalea 1.00000000
+## 1937 Microbulbifer 1.00000000
+## 1938 Algoriella 1.00000000
+## 1939 Shigella 1.00000000
+## 1940 Mycetocola 1.00000000
+## 1941 Urmitella 1.00000000
+## 1942 Dolosigranulum 1.00000000
+## 1943 Streptococcus 0.03369181
+## 1944 Moraxella 1.00000000
+## 1945 Staphylococcus 1.00000000
+## 1946 Corynebacterium 1.00000000
+## 1947 Haemophilus 0.15313421
+## 1948 Anaerobacillus 1.00000000
+## 1949 Paracoccus 1.00000000
+## 1950 Acinetobacter 1.00000000
+## 1951 Pseudomonas 1.00000000
+## 1952 Alkalihalophilus 1.00000000
+## 1953 Delftia 1.00000000
+## 1954 Noviherbaspirillum 1.00000000
+## 1955 Weissella 1.00000000
+## 1956 Escherichia 1.00000000
+## 1957 Brucella 1.00000000
+## 1958 Aeromonas 1.00000000
+## 1959 Mycoplasma 1.00000000
+## 1960 Kocuria 1.00000000
+## 1961 Enterobacter 1.00000000
+## 1962 Cutibacterium 1.00000000
+## 1963 Listeria 1.00000000
+## 1964 Micrococcus 1.00000000
+## 1965 Sphingomonas 1.00000000
+## 1966 Knoellia 1.00000000
+## 1967 Finegoldia 1.00000000
+## 1968 Peptoniphilus 1.00000000
+## 1969 Ornithinimicrobium 1.00000000
+## 1970 Nocardioides 1.00000000
+## 1971 Agrobacterium 1.00000000
+## 1972 Neisseria 1.00000000
+## 1973 Janibacter 1.00000000
+## 1974 Alkalihalobacillus 1.00000000
+## 1975 Halolactibacillus 1.00000000
+## 1976 Anaerococcus 1.00000000
+## 1977 Bifidobacterium 1.00000000
+## 1978 Bacillus 1.00000000
+## 1979 Exiguobacterium 1.00000000
+## 1980 Marmoricola 1.00000000
+## 1981 Brachybacterium 1.00000000
+## 1982 Salinicoccus 1.00000000
+## 1983 Halomonas 1.00000000
+## 1984 Suttonella 1.00000000
+## 1985 Microvirga 1.00000000
+## 1986 Rothia 1.00000000
+## 1987 Planococcus 1.00000000
+## 1988 Herbaspirillum 1.00000000
+## 1989 Psychrobacter 1.00000000
+## 1990 Dietzia 1.00000000
+## 1991 Veillonella 1.00000000
+## 1992 Alishewanella 1.00000000
+## 1993 Glaesserella 1.00000000
+## 1994 Helcococcus 1.00000000
+## 1995 Paenisporosarcina 1.00000000
+## 1996 Serinicoccus 1.00000000
+## 1997 Gemella 1.00000000
+## 1998 Rubellimicrobium 1.00000000
+## 1999 Lysobacter 1.00000000
+## 2000 Variovorax 1.00000000
+## 2001 Tessaracoccus 1.00000000
+## 2002 Stenotrophomonas 1.00000000
+## 2003 Ligilactobacillus 1.00000000
+## 2004 Klebsiella 1.00000000
+## 2005 Fusobacterium 1.00000000
+## 2006 Campylobacter 1.00000000
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+## 2008 Alkalihalobacterium 1.00000000
+## 2009 Brevibacterium 1.00000000
+## 2010 Pseudarthrobacter 1.00000000
+## 2011 Jeotgalicoccus 1.00000000
+## 2012 Neobacillus 1.00000000
+## 2013 Enterococcus 1.00000000
+## 2014 Haematobacter 1.00000000
+## 2015 Comamonas 1.00000000
+## 2016 Kaistella 1.00000000
+## 2017 Aeribacillus 1.00000000
+## 2018 Bradyrhizobium 1.00000000
+## 2019 Shewanella 1.00000000
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+## 2418 Aquimixticola 1.00000000
+## 2419 Chitinimonas 1.00000000
+## 2420 Pleomorphomonas 1.00000000
+## 2421 Hyphomonas 1.00000000
+## 2422 Caenibius 1.00000000
+## 2423 Spirillospora 1.00000000
+## 2424 Edaphobacter 1.00000000
+## 2425 Geminisphaera 1.00000000
+## 2426 Chloroflexus 1.00000000
+## 2427 Fervidicola 1.00000000
+## 2428 Cloacibacillus 1.00000000
+## 2429 Desulfovibrio 1.00000000
+## 2430 Oligella 1.00000000
+## 2431 Adhaeribacter 1.00000000
+## 2432 Lentzea 1.00000000
+## 2433 Chthoniobacter 1.00000000
+## 2434 Rhodoluna 1.00000000
+## 2435 Kineococcus 1.00000000
+## 2436 Mobilicoccus 1.00000000
+## 2437 Oceanisphaera 1.00000000
+## 2438 Lentilactobacillus 1.00000000
+## 2439 Methylomonas 1.00000000
+## 2440 Halobacillus 1.00000000
+## 2441 Rhodovibrio 1.00000000
+## 2442 Pelagibacterium 1.00000000
+## 2443 Gottschalkia 1.00000000
+## 2444 Actinokineospora 1.00000000
+## 2445 Thalassobacillus 1.00000000
+## 2446 Stigmatella 1.00000000
+## 2447 Steroidobacter 1.00000000
+## 2448 Pirellula 1.00000000
+## 2449 Canicola 1.00000000
+## 2450 Desulfonatronum 1.00000000
+## 2451 Thermosinus 1.00000000
+## 2452 Blastochloris 1.00000000
+## 2453 Thermomonas 1.00000000
+## 2454 Kerstersia 1.00000000
+## 2455 Intrasporangium 1.00000000
+## 2456 Flexilinea 1.00000000
+## 2457 Clostridioides 1.00000000
+## 2458 Pelosinus 1.00000000
+## 2459 Cardiobacterium 1.00000000
+## 2460 Albimonas 1.00000000
+## 2461 Thermostaphylospora 1.00000000
+## 2462 Falseniella 1.00000000
+## 2463 Acidiferrobacter 1.00000000
+## 2464 Catellicoccus 1.00000000
+## 2465 Acidobacterium 1.00000000
+## 2466 Methylocella 1.00000000
+## 2467 Isoptericola 1.00000000
+## 2468 Tepidiphilus 1.00000000
+## 2469 Kribbella 1.00000000
+## 2470 Kosakonia 1.00000000
+## 2471 Nocardiopsis 1.00000000
+## 2472 Weizmannia 1.00000000
+## 2473 Mannheimia 1.00000000
+## 2474 Niastella 1.00000000
+## 2475 Nitrobacter 1.00000000
+## 2476 Limimonas 1.00000000
+## 2477 Wolinella 1.00000000
+## 2478 Mycobacteroides 1.00000000
+## 2479 Negativibacillus 1.00000000
+## 2480 Rhodomicrobium 1.00000000
+## 2481 Caloramator 1.00000000
+## 2482 Pandoraea 1.00000000
+## 2483 Cnuella 1.00000000
+## 2484 Aurantiacibacter 1.00000000
+## 2485 Bavariicoccus 1.00000000
+## 2486 Rugamonas 1.00000000
+## 2487 Klenkia 1.00000000
+## 2488 Colibacter 1.00000000
+## 2489 Nitratifractor 1.00000000
+## 2490 Soonwooa 1.00000000
+## 2491 Tetrasphaera 1.00000000
+## 2492 Actinophytocola 1.00000000
+## 2493 Lactonifactor 1.00000000
+## 2494 Azohydromonas 1.00000000
+## 2495 Methylobacter 1.00000000
+## 2496 Actinomycetospora 1.00000000
+## 2497 Chroococcidiopsis 1.00000000
+## 2498 Arsenicicoccus 1.00000000
+## 2499 Pseudescherichia 1.00000000
+## 2500 Methylocapsa 1.00000000
+## 2501 Alteromonas 1.00000000
+## 2502 Psychromonas 1.00000000
+## 2503 Cryptosporangium 1.00000000
+## 2504 Marinospirillum 1.00000000
+## 2505 Kangiella 1.00000000
+## 2506 Zavarzinella 1.00000000
+## 2507 Sneathia 1.00000000
+## 2508 Niameybacter 1.00000000
+## 2509 Nostoc 1.00000000
+## 2510 Coprococcus 1.00000000
+## 2511 Roseateles 1.00000000
+## 2512 Dactylosporangium 1.00000000
+## 2513 Jonesia 1.00000000
+## 2514 Ornithinibacillus 1.00000000
+## 2515 Ruminiclostridium 1.00000000
+## 2516 Tissierella 1.00000000
+## 2517 Microlunatus 1.00000000
+## 2518 Mariniphaga 1.00000000
+## 2519 Caballeronia 1.00000000
+## 2520 Merdibacter 1.00000000
+## 2521 Salipiger 1.00000000
+## 2522 Pontibacillus 1.00000000
+## 2523 Croceicoccus 1.00000000
+## 2524 Roseivivax 1.00000000
+## 2525 Dolosicoccus 1.00000000
+## 2526 Yokenella 1.00000000
+## 2527 Melissococcus 1.00000000
+## 2528 Sutterella 1.00000000
+## 2529 Xanthomonas 1.00000000
+## 2530 Lampropedia 1.00000000
+## 2531 Mycobacterium 1.00000000
+## 2532 Maricaulis 1.00000000
+## 2533 Oribacterium 1.00000000
+## 2534 Planctopirus 1.00000000
+## 2535 Ruania 1.00000000
+## 2536 Cedecea 1.00000000
+## 2537 Rahnella 1.00000000
+## 2538 Jeotgalibaca 1.00000000
+## 2539 Edwardsiella 1.00000000
+## 2540 Mycoplasmopsis 1.00000000
+## 2541 Pseudaminobacter 1.00000000
+## 2542 Bibersteinia 1.00000000
+## 2543 Kribbia 1.00000000
+## 2544 Salinarimonas 1.00000000
+## 2545 Shimwellia 1.00000000
+## 2546 Bordetella 1.00000000
+## 2547 Neofamilia 1.00000000
+## 2548 Lentibacillus 1.00000000
+## 2549 Thiohalomonas 1.00000000
+## 2550 Paeniclostridium 1.00000000
+## 2551 Actinobacillus 1.00000000
+## 2552 Salinibacillus 1.00000000
+## 2553 Terrisporobacter 1.00000000
+## 2554 Heyndrickxia 1.00000000
+## 2555 Lederbergia 1.00000000
+## 2556 Caldalkalibacillus 1.00000000
+## 2557 Beijerinckia 1.00000000
+## 2558 Agromyces 1.00000000
+## 2559 Hydrogenoanaerobacterium 1.00000000
+## 2560 Massilioclostridium 1.00000000
+## 2561 Pasteurella 1.00000000
+## 2562 Rhodopirellula 1.00000000
+## 2563 Saccharomonospora 1.00000000
+## 2564 Wolbachia 1.00000000
+## 2565 Afifella 1.00000000
+## 2566 Ardenticatena 1.00000000
+## 2567 Companilactobacillus 1.00000000
+## 2568 Paraburkholderia 1.00000000
+## 2569 Azospira 1.00000000
+## 2570 Barnesiella 1.00000000
+## 2571 Marivita 1.00000000
+## 2572 Altibacter 1.00000000
+## 2573 Dysgonomonas 1.00000000
+## 2574 Neorhizobium 1.00000000
+## 2575 Tumebacillus 1.00000000
+## 2576 Nitrosovibrio 1.00000000
+## 2577 Glycomyces 1.00000000
+## 2578 Salinicola 1.00000000
+## 2579 Methylosinus 1.00000000
+## 2580 Xylophilus 1.00000000
+## 2581 Fusicatenibacter 1.00000000
+## 2582 Azovibrio 1.00000000
+## 2583 Geotalea 1.00000000
+## 2584 Microbulbifer 1.00000000
+## 2585 Algoriella 1.00000000
+## 2586 Shigella 1.00000000
+## 2587 Mycetocola 1.00000000
+## 2588 Urmitella 1.00000000
+
+# Trying out plotting
+#run_gee_model(dat, unit_var = "Subject",
+# taxon_level = "genus",
+# fixed_cov = c("MothChild", "HIVStatus", "Age"),
+# corstr = "ar1",
+# plot_out = TRUE,
+# plotsave_loc = #"/restricted/projectnb/infant-microbiome/work/aodom",
+# plot_terms = "MothChild",
+# width = 6, height = 4, units = "in", scale = 0.7)
+#
+test_hotelling_t2(dat = dat_0.05,
+ test_index = which(dat_0.05$MothChild == "Infant" &
+ dat_0.05$timepoint == 6),
+ taxon_level = "genus",
+ # To avoid n < p, use top 5-6 species
+ num_taxa = 6,
+ paired = TRUE,
+ grouping_var = "HIVStatus",
+ pairing_var = "pairing")
## $df1
+## [1] 6
+##
+## $df2
+## [1] 2
+##
+## $crit_F
+## [1] 19.32953
+##
+## $F_stat
+## [1] 2.578132
+##
+## $pvalue
+## [1] 0.3056466
+
+test_hotelling_t2(dat = dat_0.05,
+ test_index = which(dat_0.05$MothChild == "Mother" &
+ dat_0.05$timepoint == 0),
+ taxon_level = "genus",
+ # To avoid n < p, use top 5-6 species
+ num_taxa = 12,
+ grouping_var = "HIVStatus",
+ unit_var = "Subject",
+ paired = FALSE)
## $df1
+## [1] 12
+##
+## $df2
+## [1] 7
+##
+## $crit_F
+## [1] 3.574676
+##
+## $F_stat
+## [1] 0.4781539
+##
+## $pvalue
+## [1] 0.875078
+
+sessionInfo()
## R version 4.3.1 (2023-06-16)
+## Platform: x86_64-pc-linux-gnu (64-bit)
+## Running under: AlmaLinux 8.9 (Midnight Oncilla)
+##
+## Matrix products: default
+## BLAS: /share/pkg.8/r/4.3.1/install/lib64/R/lib/libRblas.so
+## LAPACK: /share/pkg.8/r/4.3.1/install/lib64/R/lib/libRlapack.so; LAPACK version 3.11.0
+##
+## locale:
+## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
+## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
+## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
+## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
+## [9] LC_ADDRESS=C LC_TELEPHONE=C
+## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
+##
+## time zone: America/New_York
+## tzcode source: system (glibc)
+##
+## attached base packages:
+## [1] stats graphics grDevices utils datasets methods base
+##
+## other attached packages:
+## [1] lubridate_1.9.3 forcats_1.0.0 stringr_1.5.1 dplyr_1.1.4
+## [5] purrr_1.0.2 readr_2.1.5 tidyr_1.3.0 tibble_3.2.1
+## [9] ggplot2_3.4.4 tidyverse_2.0.0 LegATo_0.0.0.9000 BiocStyle_2.28.0
+##
+## loaded via a namespace (and not attached):
+## [1] rstudioapi_0.15.0 jsonlite_1.8.8
+## [3] umap_0.2.10.0 MultiAssayExperiment_1.28.0
+## [5] magrittr_2.0.3 farver_2.1.1
+## [7] rmarkdown_2.25 geepack_1.3.9
+## [9] fs_1.6.3 zlibbioc_1.48.0
+## [11] ragg_1.2.5 vctrs_0.6.5
+## [13] memoise_2.0.1 paletteer_1.5.0
+## [15] RCurl_1.98-1.14 askpass_1.2.0
+## [17] BiocBaseUtils_1.4.0 htmltools_0.5.7
+## [19] S4Arrays_1.2.0 broom_1.0.5
+## [21] SparseArray_1.2.3 sass_0.4.8
+## [23] TBSignatureProfiler_1.15.0 bslib_0.6.1
+## [25] htmlwidgets_1.6.4 desc_1.4.3
+## [27] plyr_1.8.9 covr_3.6.2
+## [29] plotly_4.10.2 cachem_1.0.8
+## [31] lifecycle_1.0.4 iterators_1.0.14
+## [33] pkgconfig_2.0.3 Matrix_1.6-5
+## [35] R6_2.5.1 fastmap_1.1.1
+## [37] GenomeInfoDbData_1.2.11 MatrixGenerics_1.14.0
+## [39] clue_0.3-65 digest_0.6.34
+## [41] colorspace_2.1-0 rematch2_2.1.2
+## [43] spatial_7.3-16 S4Vectors_0.40.2
+## [45] DESeq2_1.40.1 RSpectra_0.16-1
+## [47] textshaping_0.3.6 GenomicRanges_1.54.1
+## [49] vegan_2.6-4 labeling_0.4.3
+## [51] fansi_1.0.6 timechange_0.2.0
+## [53] httr_1.4.7 abind_1.4-5
+## [55] mgcv_1.8-42 compiler_4.3.1
+## [57] withr_3.0.0 backports_1.4.1
+## [59] inline_0.3.19 BiocParallel_1.36.0
+## [61] highr_0.10 MASS_7.3-60
+## [63] tsne_0.1-3.1 openssl_2.1.1
+## [65] DelayedArray_0.28.0 fBasics_4022.94.9000
+## [67] permute_0.9-7 tools_4.3.1
+## [69] ape_5.7-1 rentrez_1.2.3
+## [71] glue_1.7.0 stabledist_0.7-1
+## [73] nlme_3.1-162 grid_4.3.1
+## [75] cluster_2.1.4 reshape2_1.4.4
+## [77] generics_0.1.3 gtable_0.3.4
+## [79] tzdb_0.4.0 data.table_1.14.10
+## [81] hms_1.1.3 utf8_1.2.4
+## [83] XVector_0.42.0 rmutil_1.1.10
+## [85] BiocGenerics_0.48.1 ggrepel_0.9.3
+## [87] foreach_1.5.2 pillar_1.9.0
+## [89] limma_3.56.2 splines_4.3.1
+## [91] lattice_0.21-8 GUniFrac_1.8
+## [93] tidyselect_1.2.0 locfit_1.5-9.8
+## [95] knitr_1.45 bookdown_0.34
+## [97] IRanges_2.36.0 edgeR_3.42.4
+## [99] SummarizedExperiment_1.32.0 stats4_4.3.1
+## [101] xfun_0.41 Biobase_2.62.0
+## [103] statmod_1.5.0 timeDate_4032.109
+## [105] matrixStats_1.2.0 DT_0.28
+## [107] rex_1.2.1 stringi_1.8.3
+## [109] lazyeval_0.2.2 yaml_2.3.8
+## [111] evaluate_0.23 codetools_0.2-19
+## [113] timeSeries_4030.106.9000 BiocManager_1.30.22
+## [115] cli_3.6.2 rpart_4.1.19
+## [117] reticulate_1.30 systemfonts_1.0.4
+## [119] munsell_0.5.0 jquerylib_0.1.4
+## [121] Rcpp_1.0.12 GenomeInfoDb_1.38.5
+## [123] stable_1.1.6 png_0.1-8
+## [125] XML_3.99-0.16 parallel_4.3.1
+## [127] modeest_2.4.0 ellipsis_0.3.2
+## [129] pkgdown_2.0.7 assertthat_0.2.1
+## [131] animalcules_1.18.2 ggalluvial_0.12.5
+## [133] bitops_1.0-7 viridisLite_0.4.2
+## [135] scales_1.3.0 statip_0.2.3
+## [137] crayon_1.5.2 rlang_1.1.3
+## [139] shinyjs_2.1.0
+animalcules_MAE_formatting.Rmd
This vignette will discuss the formatting of an animalcules MAE for +usage with the package.
+Coming soon!
+I will also add a function that properly creates a MAE with proper +checks…
+LegATo-package.Rd
Streamlining longitudinal microbiome profiling in Bioconductor.
+clean_animalcules_MAE.Rd
This functional is an optional method for fixing up taxon names in a
+MultiAssayExperiment
to be run before filter_animalcules_MAE
.
+Specifically it removes brackets from species names, replaces species labeled
+as "others" with "sp." and finally replaces underscores with spaces.
clean_animalcules_MAE(dat)
A MultiAssayExperiment
object specially formatted as an
+animalcules output.
An animalcules-formatted MultiAssayExperiment
object with
+ cleaned-up taxonomy nomenclature.
in_dat <- system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS()
+#> Error in system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS(): could not find function "%>%"
+clean_animalcules_MAE(in_dat)
+#> Error in eval(expr, envir, enclos): object 'in_dat' not found
+
+
filter_animalcules_MAE.Rd
This function takes an animalcules-formatted MultiAssayExperiment
+(MAE) object and identifies all taxa at the "genus" level that represent
+<filter_pct
average relative abundance across all samples in the MAE.
+After identification at the genus level, taxa across the genus and species
+levels are then consolidated into the category "Other".
filter_animalcules_MAE(dat, filter_pct = 0.05)
A MultiAssayExperiment
object specially formatted as an
+animalcules output.
A double strictly between 0 and 1.
An animalcules-formatted MultiAssayExperiment
object with
+ appropriate filtration.
in_dat <- system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS()
+#> Error in system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS(): could not find function "%>%"
+filter_animalcules_MAE(in_dat, 0.01)
+#> Error in eval(expr, envir, enclos): object 'in_dat' not found
+
+
get_long_data.Rd
This function takes a MultiAssayExperiment
object and a specified
+taxon level of interest and creates a long data.frame
that can be used
+more easily for plotting counts.
get_long_data(dat, taxon_level, log = FALSE, counts_to_CPM = FALSE)
A MultiAssayExperiment
object specially formatted as an
+animalcules output.
Character string indicating the level of taxonomy to
+aggregate the counts data. Must be the name of a column in
+MultiAssayExperiment::rowData(dat)
.
logical. Indicate whether an assay returned should be the log of
+whichever assay is specified in "output_name"
. If
+counts_to_CPM = TRUE
as well, then a log CPM assay will also be
+created. Default is FALSE
.
logical. This argument only applies if the
+input_type
is a counts assay. If TRUE
, then the output assays
+will include a normalized CPM assay. If log = TRUE
as well, then a
+log CPM assay will also be created. Default is TRUE
.
A data.frame
consisting of the counts data, taxa, and
+ metadata.
in_dat <- system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS()
+#> Error in system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS(): could not find function "%>%"
+out <- get_long_data(in_dat, "genus", log = TRUE, counts_to_CPM = TRUE)
+#> Error in eval(expr, envir, enclos): object 'in_dat' not found
+head(out)
+#> Error in eval(expr, envir, enclos): object 'out' not found
+
+
get_stacked_data.Rd
Documentation
+get_stacked_data(dat, taxon_level = "genus", covariate_1, covariate_time)
in_dat <- system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS()
+#> Error in system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS(): could not find function "%>%"
+get_stacked_data(in_dat, "genus", covariate_1 = "Sex", covariate_time = "Month")
+#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'assays': object 'in_dat' not found
+
+
get_summary_table.Rd
This function takes a MultiAssayExperiment
of microbial read counts
+and aggregates them by one or more grouping vars within a unit.
get_summary_table(dat, group_vars)
A MultiAssayExperiment
object specially formatted as an
+animalcules output.
A character string or character vector of covariates
+found in colData(dat)
to use in grouping counts. The variables
+should be listed in order of desired grouping.
A data.frame
of the grouping columns, mean_reads, sd_reads,
+min_reads, max_reads and num_total.
in_dat <- system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS()
+#> Error in system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS(): could not find function "%>%"
+out <- get_summary_table(in_dat, c("Group", "Subject"))
+#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'assays': object 'in_dat' not found
+head(out)
+#> Error in eval(expr, envir, enclos): object 'out' not found
+
+
get_top_taxa.Rd
This function takes a MultiAssayExperiment
object and returns a
+data.frame of the present taxa at a user-supplied taxonomy level,
+and outputs the average abundances of the taxa.
get_top_taxa(dat, taxon_level = "genus")
A MultiAssayExperiment
object specially formatted as an
+animalcules output.
Character string indicating the level of taxonomy to
+aggregate the counts data. Must be the name of a column in
+MultiAssayExperiment::rowData(dat)
.
A data.frame
in_dat <- system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS()
+#> Error in system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS(): could not find function "%>%"
+out <- get_top_taxa(in_dat, "genus")
+#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'assays': object 'in_dat' not found
+out
+#> Error in eval(expr, envir, enclos): object 'out' not found
+
+
+ All functions+ + |
+ |
---|---|
+ + | +Clean up taxon names in a MultiAssayExperiment |
+
+ + | +Filter a MultiAssayExperiment to a top percentage of taxa and label the rest +as "Other" |
+
+ + | +Create a long data.frame from a MultiAssayExperiment counts object |
+
+ + | +Documentation |
+
+ + | +Create a table summarizing reads aggregated by grouping variables on a unit |
+
+ + | +Obtain a data.frame of ordered taxa abundances at a given level |
+
+ + | +Parse a MultiExperimentAssay object and extract the elements as data.frames |
+
+ + | +Plot an alluvial diagram of microbial relative abundance |
+
+ + | +Plot a spaghetti volatility plot of microbial abundance for a given taxon |
+
+ + | +Plot a stacked area chart of microbial relative abundance |
+
+ + | +Plot a stacked bar chart of microbial relative abundance |
+
+ + | +Compute Generalized Estimating Equations (GEEs) |
+
+ + | +Conduct a multivariate Hotelling's T-squared test |
+
parse_MAE_SE.Rd
This function takes an animalcules-formatted MultiAssayExperiment
+object and parses it to extract a named assay alongside the taxonomy and
+metadata.
parse_MAE_SE(dat, which_assay = NULL, type = "MAE")
Either a MultiAssayExperiment
or a
+SummarizedExperiment
object.
Character string. This refers to the assay to be extracted
+from the MultiAssayExperiment object if type = "MAE"
. Does not need
+to be specified if type = "SE"
. Default is NULL
.
One of "MAE" denoting a MultiAssayExperiment
or "SE"
+denoting a SummarizedExperiment
.
Returns a list of 3 named data.frame elements, `counts`, `sam`, and + `tax` denoting the counts data, sample metadata table, and taxonomy table, + respectively.
+in_dat <- system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS()
+#> Error in system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS(): could not find function "%>%"
+out <- parse_MAE_SE(in_dat)
+#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'assays': object 'in_dat' not found
+head(out$tax)
+#> Error in eval(expr, envir, enclos): object 'out' not found
+head(out$sam)
+#> Error in eval(expr, envir, enclos): object 'out' not found
+head(out$counts)
+#> Error in eval(expr, envir, enclos): object 'out' not found
+
+out2 <- parse_MAE_SE(in_dat[["MicrobeGenetics"]],
+ which_assay = "MGX", type = "SE")
+#> Error in eval(expr, envir, enclos): object 'in_dat' not found
+
+
plot_alluvial.Rd
This function takes a MultiAssayExperiment
object and returns a
+alluvial diagram of microbe relative abundances. The function takes a single
+covariate as an optional variable by which to create a grid of multiple
+plots.
plot_alluvial(
+ dat,
+ taxon_level,
+ covariate_1 = NULL,
+ covariate_time,
+ palette_input = NULL,
+ title = paste("Relative abundance at", taxon_level, "level"),
+ subtitle = NULL
+)
A MultiAssayExperiment
object specially formatted as an
+animalcules output.
Character string indicating the level of taxonomy to
+aggregate the counts data. Must be the name of a column in
+MultiAssayExperiment::rowData(dat)
.
Character string giving the name of a column in
+MultiAssayExperiment::colData(dat)
on which to create multiple
+plots. The default is NULL
.
Character string giving the name of the discrete +time-based covariate in the metadata to group abundances by.
A character vector of colors that is at minimum the same
+length of the number of taxa (specified with taxon_level
).
+The default is NULL
and relies on ggplot2
's default scheme.
A character string providing the plot title.
A character string providing the plot subtitle. The default
+is NULL
.
A ggplot2
plot.
If further manipulation of specific parameters is desired, users can add
+ggplot2
function calls to the output of the function.
in_dat <- system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS()
+#> Error in system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS(): could not find function "%>%"
+plot_alluvial(in_dat, taxon_level = "family", covariate_1 = "Group", covariate_time = "Month",
+ palette_input = rainbow(25))
+#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'assays': object 'in_dat' not found
+
+
plot_spaghetti.Rd
This function takes a MultiAssayExperiment
object and returns a
+spaghetti plot of microbial abundance delineated by a unit, such as
+a subject.
plot_spaghetti(
+ dat,
+ covariate_time,
+ covariate_1 = NULL,
+ unit_var,
+ taxon_level,
+ which_taxon,
+ palette_input = NULL,
+ title = "Spaghetti Plot",
+ subtitle = NULL
+)
A MultiAssayExperiment
object specially formatted as an
+animalcules output.
Character string giving the name of the discrete +time-based covariate in the metadata to group abundances by.
Character string, the name of the covariate in `dat`
+by which to color and group samples. Default is NULL
.
Character string, the name of the column delineating the +unit on which the microbial abundances are changing over time. This is +likely something akin to a subject that repeated measurements are made on.
Character string indicating the level of taxonomy to
+aggregate the counts data. Must be the name of a column in
+MultiAssayExperiment::rowData(dat)
.
Character string, the name of the taxon to plot at the +specified taxon level.
A character vector of colors that is at minimum the same
+length of the number of taxa (specified with taxon_level
).
+The default is NULL
and relies on ggplot2
's default scheme.
A character string providing the plot title.
A character string providing the plot subtitle. The default
+is NULL
.
A ggplot2
plot.
If further manipulation of specific parameters is desired, users can add
+ggplot2
function calls to the output of the function.
in_dat <- system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS()
+#> Error in system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS(): could not find function "%>%"
+all_taxa <- get_top_taxa(in_dat, "phylum")
+#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'assays': object 'in_dat' not found
+plot_spaghetti(in_dat, taxon_level = "phylum", covariate_1 = "Group", covariate_time = "Month",
+ unit_var = "Subject", which_taxon = all_taxa$taxon[1],
+ palette_input = rainbow(25))
+#> Error in eval(expr, envir, enclos): object 'in_dat' not found
+
+
plot_stacked_area.Rd
This function takes a MultiAssayExperiment
object and returns a
+stacked area chart of microbe relative abundances. The function takes a single
+covariate as an optional variable by which to create a grid of multiple
+plots.
plot_stacked_area(
+ dat,
+ taxon_level,
+ covariate_1 = NULL,
+ covariate_time,
+ palette_input = NULL,
+ title = paste("Relative abundance at", taxon_level, "level"),
+ subtitle = NULL
+)
A MultiAssayExperiment
object specially formatted as an
+animalcules output.
Character string indicating the level of taxonomy to
+aggregate the counts data. Must be the name of a column in
+MultiAssayExperiment::rowData(dat)
.
Character string giving the name of a column in
+MultiAssayExperiment::colData(dat)
on which to create multiple
+plots. The default is NULL
.
Character string giving the name of the discrete +time-based covariate in the metadata to group abundances by.
A character vector of colors that is at minimum the same
+length of the number of taxa (specified with taxon_level
).
+The default is NULL
and relies on ggplot2
's default scheme.
A character string providing the plot title.
A character string providing the plot subtitle. The default
+is NULL
.
A ggplot2
plot.
If further manipulation of specific parameters is desired, users can add
+ggplot2
function calls to the output of the function.
in_dat <- system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS()
+#> Error in system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS(): could not find function "%>%"
+plot_stacked_area(in_dat, taxon_level = "phylum", covariate_1 = "Group",
+ covariate_time = "Month",
+ palette_input = rainbow(25))
+#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'assays': object 'in_dat' not found
+
+
plot_stacked_bar.Rd
This function takes a MultiAssayExperiment
object and returns a
+stacked bar plot of microbe relative abundances. The function takes a single
+covariate as an optional variable by which to create multiple gridded plots.
plot_stacked_bar(
+ dat,
+ taxon_level,
+ covariate_1 = NULL,
+ covariate_time,
+ palette_input = NULL,
+ title = paste("Relative abundance at", taxon_level, "level"),
+ subtitle = NULL
+)
A MultiAssayExperiment
object specially formatted as an
+animalcules output.
Character string indicating the level of taxonomy to
+aggregate the counts data. Must be the name of a column in
+MultiAssayExperiment::rowData(dat)
.
Character string giving the name of a column in
+MultiAssayExperiment::colData(dat)
on which to create multiple
+plots. The default is NULL
.
Character string giving the name of the discrete +time-based covariate in the metadata to group abundances by.
A character vector of colors that is at minimum the same
+length of the number of taxa (specified with taxon_level
).
+The default is NULL
and relies on ggplot2
's default scheme.
A character string providing the plot title.
A character string providing the plot subtitle. The default
+is NULL
.
A ggplot2
plot.
If further manipulation of specific parameters is desired, users can add
+ggplot2
function calls to the output of the function.
in_dat <- system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS()
+#> Error in system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS(): could not find function "%>%"
+plot_stacked_bar(in_dat, taxon_level = "family", covariate_1 = "Group",
+ covariate_time = "Month",
+ palette_input = rainbow(25))
+#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'assays': object 'in_dat' not found
+
+
run_gee_model.Rd
Run an independent GEE model for each taxa with relative abundance +Works well with small data - multiple subpoints/subjects across clusters
+run_gee_model(
+ dat,
+ taxon_level = "genus",
+ unit_var,
+ fixed_cov,
+ corstr = "ar1",
+ plot_out = FALSE,
+ plotsave_loc = ".",
+ plot_terms = NULL,
+ ...
+)
Source +https://data.library.virginia.edu/getting-started-with-generalized-estimating-equations/
+fixed_cov is a vector
+in_dat <- system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS()
+#> Error in system.file("extdata/MAE_small.RDS", package = "LegATo") %>% readRDS(): could not find function "%>%"
+out <- run_gee_model(in_dat, taxon_level = "genus", unit_var = "Subject",
+ fixed_cov = c("HairLength", "Age", "Group", "Sex"), corstr = "ar1")
+#> Error in eval(expr, envir, enclos): object 'in_dat' not found
+head(out)
+#> Error in eval(expr, envir, enclos): object 'out' not found
+
+
test_hotelling_t2.Rd
This function takes an animalcules-formatted MultiAssayExperiment
+object and runs a multivariate Hotelling's T-squared test. The test expects
+a comparison of two distinct groups, and compares the abundances of the top microbes at a
+given taxon level between the groups. This function allows both paired and unpaired
+tests. Both test the null hypothesis that the population
+mean vectors are equal, with the alternative being that they are unequal.
test_hotelling_t2(
+ dat,
+ test_index = NULL,
+ taxon_level = "genus",
+ num_taxa,
+ grouping_var,
+ paired = FALSE,
+ pairing_var = NULL,
+ unit_var = NULL,
+ save_table_loc = "."
+)
A MultiAssayExperiment object specially formatted as an animalcules output.
Any argument used for subsetting the input dat
,
+can be a character, logical, integer, list or List vector. Default is NULL
.
Character string, default is "genus"
.
The number of most abundant taxa to test. Needs to be small enough to +avoid n > p issues where n is the smallest number of samples or units in a given group, +and p is the number of microbes to be tested.
Character string, the name of a DICHOTOMOUS grouping variable in the
+metadata of dat
.
Logical indicating whether a paired test should be conducted.
+Default is FALSE
for an unpaired test.
Character string giving the variable containing pairing information.
+The variable should be in integer form. Must be supplied if paired = TRUE
,
+otherwise the default is NULL.
Character string giving the variable containing the identifiers
+for the unit on which multiple measurements were conducted, e.g. subjects. Default is
+NULL
; must be supplied if paired = FALSE
.
A character string giving the folder path to save t.test results. +Note that these are only conducted if the Hotelling's T-test value is <0.05. +Defaults to the current working directory.
A list of the elements "df1", "df2", "crit_F", "F_stat" and "pvalue" giving the +results of the test.
+The Hotelling's t-squared statistic (t2) is a generalization of +Student's t-statistic that is used in multivariate hypothesis testing +to test the means of different populations.
+Note that any entries or pairs with missing values are excluded.
+Referenced articles in the implementation of tests:
+https://online.stat.psu.edu/stat505/lesson/7/7.1/7.1.14
+https://online.stat.psu.edu/stat505/lesson/7/7.1/7.1.15
+https://online.stat.psu.edu/stat505/lesson/7/7.1/7.1.4
+https://online.stat.psu.edu/stat505/lesson/7/7.1/7.1.9
+dat <- system.file("extdata", "MAE.RDS", package = "LegATo") %>%
+readRDS()
+#> Error in system.file("extdata", "MAE.RDS", package = "LegATo") %>% readRDS(): could not find function "%>%"
+dat_0.05 <- filter_animalcules_MAE(dat, 0.05)
+#> Error in eval(expr, envir, enclos): object 'dat' not found
+out1 <- test_hotelling_t2(dat = dat_0.05,
+ test_index = which(dat_0.05$MothChild == "Infant" &
+ dat_0.05$timepoint == 6),
+ taxon_level = "genus",
+ # To avoid n < p, use top 5-6 species
+ num_taxa = 6,
+ paired = TRUE,
+ grouping_var = "HIVStatus",
+ pairing_var = "pairing")
+#> Error in eval(expr, envir, enclos): object 'dat_0.05' not found
+out1
+#> Error in eval(expr, envir, enclos): object 'out1' not found
+
+out <- test_hotelling_t2(dat = dat_0.05,
+ test_index = which(dat_0.05$MothChild == "Mother" &
+ dat_0.05$timepoint == 0),
+ taxon_level = "genus",
+ # To avoid n < p, use top 5-6 species
+ num_taxa = 12,
+ grouping_var = "HIVStatus",
+ unit_var = "Subject",
+ paired = FALSE)
+#> Error in eval(expr, envir, enclos): object 'dat_0.05' not found
+out
+#> Error in eval(expr, envir, enclos): object 'out' not found
+
+