Last updated: 2022-11-09
Checks: 6 1
Knit directory: dgrp-starve/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | 81037cc | nklimko | 2022-11-09 | html reworking, snp success |
| html | 81037cc | nklimko | 2022-11-09 | html reworking, snp success |
| Rmd | 41de4a8 | nklimko | 2022-11-08 | difMinus success, reframe for all four genotype analysis |
Data was extracted from two tables of eQTL male/female traits.
First, each file was filtered for non-null values
# csvPath dependent upon female/male file
allRaw <- tibble(read.csv(csvPath))
starveRaw <- allRaw %>% select(line,starvation) %>% filter(!is.na(starvation))Two tables, starveF and starveM, were then joined one. Difference and average of each line were calculated and added
#Combine mf
starve <- starveF %>% mutate(m = starveM$m)
#compute difference and average
starve <- starve %>% select(line, f, m) %>% mutate(dif = f - m, avg = (f+m)/2)Lines were manually selected and hard coded into the following extractions.
#print(arrange(starve, starve$dif), n=205)
#print(arrange(starve, starve$avg), n=205)
# Lines with male SR high than female SR
difMinus <- starve %>% filter(dif < 0) %>% arrange(line) %>% select(line)
difMinus <- as.data.table(difMinus)
fwrite(difMinus, "./data/difMinus.txt")
# Lines with largest gap from male SR to female SR
difPlus <- starve %>% filter(dif >= 30) %>% arrange(line) %>% select(line)
difPlus <- as.data.table(difPlus)
fwrite(difPlus, "./data/difPlus.txt")
# Lowest average SR between males and females
avgMinus <- starve %>% filter(avg < 40) %>% arrange(line) %>% select(line)
avgMinus <- as.data.table(avgMinus)
fwrite(avgMinus, "./data/avgMinus.txt")
# Highest average SR between males and females
avgPlus <- starve %>% filter(dif >= 30) %>% arrange(line) %>% select(line)
avgPlus <- as.data.table(avgPlus)
fwrite(avgPlus, "./data/avgPlus.txt")After creating the groups of interest, I
sessionInfo()R version 4.0.3 (2020-10-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)
Matrix products: default
BLAS/LAPACK: /opt/ohpc/pub/Software/openblas_0.3.10/lib/libopenblas_haswellp-r0.3.10.dev.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] data.table_1.14.2 dplyr_1.0.8 tidyr_1.2.0 workflowr_1.7.0
loaded via a namespace (and not attached):
[1] Rcpp_1.0.8.3 bslib_0.3.1 jquerylib_0.1.4 compiler_4.0.3
[5] pillar_1.7.0 later_1.3.0 git2r_0.30.1 tools_4.0.3
[9] getPass_0.2-2 digest_0.6.29 jsonlite_1.8.0 evaluate_0.15
[13] tibble_3.1.6 lifecycle_1.0.1 pkgconfig_2.0.3 rlang_1.0.4
[17] DBI_1.1.2 cli_3.3.0 rstudioapi_0.13 yaml_2.3.5
[21] xfun_0.30 fastmap_1.1.0 httr_1.4.2 stringr_1.4.0
[25] knitr_1.38 generics_0.1.2 sass_0.4.1 fs_1.5.2
[29] vctrs_0.4.1 tidyselect_1.1.2 rprojroot_2.0.3 glue_1.6.2
[33] R6_2.5.1 processx_3.5.3 fansi_1.0.3 rmarkdown_2.16
[37] purrr_0.3.4 callr_3.7.0 magrittr_2.0.3 whisker_0.4
[41] ps_1.6.0 promises_1.2.0.1 htmltools_0.5.2 ellipsis_0.3.2
[45] assertthat_0.2.1 httpuv_1.6.5 utf8_1.2.2 stringi_1.7.6
[49] crayon_1.5.1