GObayesC Report

Last updated: 2023-12-12

Checks: 7 0

Knit directory: dgrp-starve/

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Ignored files:
    Ignored:    .snakemake/
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    Untracked:  snake/code/method/bayesHome.R
    Untracked:  snake/code/method/multiplotGO.Rmd
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Unstaged changes:
    Modified:   analysis/Method/BayesC.Rmd
    Modified:   analysis/bigGO.Rmd
    Modified:   snake/code/method/bayesGO.R
    Modified:   snake/code/method/goFish.R
    Modified:   snake/code/method/varbvs.R

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File	Version	Author	Date	Message
Rmd	f1b715f	nklimko	2023-12-12	wflow_publish(“analysis/pippin.Rmd”)
html	43af6b9	nklimko	2023-12-05	Build site.
Rmd	d1987b3	nklimko	2023-12-05	wflow_publish(“analysis/pippin.Rmd”)

load('snake/data/topTables.Rdata')

options(knitr.kable.NA = '')

Summary

We wanted to ensure that the genes of interest found multiple times across GO terms were significant in our models by looking at their posterior inclusion probability in each subset. The cutoff for associated genes was set to 0.5 while the cutoff for non-associated genes was set to 0.7. We then tallied the filtered genes as subsets of their individual distribution and then altogether to find genes that appeared scarcely in both.

Our findings here are mostly consistent with initial findings. Notably, the Adipokinetic hormone Receptor(AkhR) is a top hit while the hormone itself(Akh) is not found in either sex.

Female Genes

kable(fGO_top, caption= 'GO genes',  'simple') %>%
  kable_styling(full_width = FALSE, position = "float_left")

Warning in kable_styling(., full_width = FALSE, position = "float_left"):
Please specify format in kable. kableExtra can customize either HTML or LaTeX
outputs. See https://haozhu233.github.io/kableExtra/ for details.

GO genes
gene	count	name
FBgn0025595	8	AkhR
FBgn0000575	7	emc
FBgn0262738	4	norpA
FBgn0003205	4	Ras85D
FBgn0003731	4	Egfr
FBgn0003463	3	sog
FBgn0003719	3	tld
FBgn0036449	3	bmm

kable(fNON_top, caption= 'non-GO genes', 'simple') %>%
  kable_styling(full_width = FALSE, position = "float_right")

Warning in kable_styling(., full_width = FALSE, position = "float_right"):
Please specify format in kable. kableExtra can customize either HTML or LaTeX
outputs. See https://haozhu233.github.io/kableExtra/ for details.

non-GO genes
gene	count	name
FBgn0025595	8	AkhR
FBgn0000575	7	emc
FBgn0262738	4	norpA
FBgn0003731	4	Egfr
FBgn0003463	3	sog

kable(fALL_topGenes, caption = 'Top Female Genes', "simple")

Top Female Genes
gene	count	name
FBgn0025595	16	AkhR
FBgn0000575	14	emc
FBgn0262738	8	norpA
FBgn0003731	8	Egfr
FBgn0003463	6	sog
FBgn0003205	4	Ras85D
FBgn0004635	4	rho
FBgn0039114	4	Lsd-1
FBgn0003218	4	rdgB
FBgn0026207	3	mbo
FBgn0003719	3	tld
FBgn0036449	3	bmm

Male Genes

kable(mGO_top, caption= 'GO genes',  'simple') %>%
  kable_styling(full_width = FALSE, position = "float_left")

Warning in kable_styling(., full_width = FALSE, position = "float_left"):
Please specify format in kable. kableExtra can customize either HTML or LaTeX
outputs. See https://haozhu233.github.io/kableExtra/ for details.

GO genes
gene	count	name
FBgn0261873	9	sdt
FBgn0261854	6	aPKC
FBgn0025595	6	AkhR
FBgn0026192	5	par-6
FBgn0265778	5	PDZ-GEF
FBgn0036046	5	Ilp2
FBgn0086687	4	Desat1
FBgn0011661	3	Moe
FBgn0036449	3	bmm
FBgn0000163	3	baz
FBgn0003205	3	Ras85D

kable(mNON_top, caption= 'non-GO genes', 'simple') %>%
  kable_styling(full_width = FALSE, position = "float_right")

Warning in kable_styling(., full_width = FALSE, position = "float_right"):
Please specify format in kable. kableExtra can customize either HTML or LaTeX
outputs. See https://haozhu233.github.io/kableExtra/ for details.

non-GO genes
gene	count	name
FBgn0261873	9	sdt
FBgn0025595	6	AkhR
FBgn0265778	5	PDZ-GEF

kable(mALL_topGenes, caption = 'Top Female Genes', "simple")

Top Female Genes
gene	count	name
FBgn0261873	18	sdt
FBgn0025595	12	AkhR
FBgn0265778	10	PDZ-GEF
FBgn0261854	6	aPKC
FBgn0036046	6	Ilp2
FBgn0086687	6	Desat1
FBgn0026192	5	par-6
FBgn0032264	4	Lip4
FBgn0020386	4	Pdk1
FBgn0033205	4	CG2064
FBgn0011661	3	Moe
FBgn0036449	3	bmm
FBgn0000163	3	baz
FBgn0003205	3	Ras85D

PIP Plots

Below are the PIP plots from the top GO terms separated by sex. These were made on the full model( all 198 lines, no CV) rather than cross validation for prediction. The left column contains PIP plots for the distribution associated with the GO-related genes, while the right column contains PIP plot for all other genes. Each row is a GO term.

Female Posterior Inclusion Of Probability Plots

sex <- 'f'
plotList <- list.files(path=paste0('snake/data/go/26_pip/sex', sex), full.names = TRUE)

ggF <- lapply(plotList, readRDS)

for(i in 1:(length(ggF)/2)){
  b <- 2*i
  a <- b - 1
  print(plot_grid(ggF[[a]], ggF[[b]], ncol=2))
}

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Male Posterior Inclusion Of Probability Plots

sex <- 'm'
plotList <- list.files(path=paste0('snake/data/go/26_pip/sex', sex), full.names = TRUE)

ggM <- lapply(plotList, readRDS)

for(i in 1:(length(ggM)/2)){
  b <- 2*i
  a <- b - 1
  print(plot_grid(ggM[[a]], ggM[[b]], ncol=2))
}

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sessionInfo()

R version 4.1.2 (2021-11-01)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Rocky Linux 8.5 (Green Obsidian)

Matrix products: default
BLAS/LAPACK: /opt/ohpc/pub/libs/gnu9/openblas/0.3.7/lib/libopenblasp-r0.3.7.so

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       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] kableExtra_1.3.4   knitr_1.43         reshape2_1.4.4     melt_1.10.0       
 [5] ggcorrplot_0.1.4.1 lubridate_1.9.3    forcats_1.0.0      stringr_1.5.0     
 [9] purrr_1.0.1        readr_2.1.4        tidyr_1.3.0        tibble_3.2.1      
[13] tidyverse_2.0.0    scales_1.2.1       viridis_0.6.4      viridisLite_0.4.2 
[17] qqman_0.1.9        cowplot_1.1.1      ggplot2_3.4.4      data.table_1.14.8 
[21] dplyr_1.1.3        workflowr_1.7.1   

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.11       svglite_2.1.2     getPass_0.2-2     ps_1.7.5         
 [5] rprojroot_2.0.3   digest_0.6.33     utf8_1.2.3        plyr_1.8.9       
 [9] R6_2.5.1          evaluate_0.21     highr_0.10        httr_1.4.7       
[13] pillar_1.9.0      rlang_1.1.1       rstudioapi_0.15.0 whisker_0.4.1    
[17] callr_3.7.3       jquerylib_0.1.4   rmarkdown_2.23    labeling_0.4.3   
[21] webshot_0.5.5     munsell_0.5.0     compiler_4.1.2    httpuv_1.6.12    
[25] xfun_0.39         systemfonts_1.0.5 pkgconfig_2.0.3   htmltools_0.5.5  
[29] tidyselect_1.2.0  gridExtra_2.3     fansi_1.0.4       calibrate_1.7.7  
[33] tzdb_0.4.0        withr_2.5.0       later_1.3.1       MASS_7.3-60      
[37] grid_4.1.2        jsonlite_1.8.7    gtable_0.3.4      lifecycle_1.0.3  
[41] git2r_0.32.0      magrittr_2.0.3    cli_3.6.1         stringi_1.7.12   
[45] cachem_1.0.8      farver_2.1.1      fs_1.6.3          promises_1.2.0.1 
[49] xml2_1.3.3        bslib_0.5.0       generics_0.1.3    vctrs_0.6.4      
[53] tools_4.1.2       glue_1.6.2        hms_1.1.3         processx_3.8.2   
[57] fastmap_1.1.1     yaml_2.3.7        timechange_0.2.0  colorspace_2.1-0 
[61] rvest_1.0.3       sass_0.4.7