Gene set analysis misuse examples
Mark Ziemann & Kaumadi Wijesooriya
2022-01-18
Source: https://github.com/markziemann/SurveyEnrichmentMethods
Intro
This script is designed to generate the results of the manuscript figure 4.
Panels A-D are generated with “example1.Rmd” and “example1-7.Rmd” are required for panel E.
Here are the datasets considered.
| Dataset | SRA accesion | genes in annotation set | genes detected | genes differentially expressed |
|---|---|---|---|---|
| 1. | SRP128998 | 39297 | 15635 | 3472 |
| 2. | SRP038101 | 39297 | 13926 | 3589 |
| 3. | SRP096178 | 39297 | 15477 | 9488 |
| 4. | SRP038101 | 39297 | 15607 | 5150 |
| 5. | SRP247621 | 39297 | 14288 | 230 |
| 6. | SRP253951 | 39297 | 15182 | 8588 |
| 7. | SRP068733 | 39297 | 14255 | 7365 |
suppressPackageStartupMessages({
library("kableExtra")
library("beeswarm")
})Execute the examples
Here I’m running the scripts to analyse each of the example datasets shown in the above table.
rmarkdown::render("example1.Rmd")##
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## label: session## output file: example1.knit.md## /home/mdz/anaconda3/bin/pandoc +RTS -K512m -RTS example1.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output example1.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --self-contained --variable bs3=TRUE --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --variable theme=bootstrap --include-in-header /tmp/Rtmp5Mw6Xi/rmarkdown-str2ce4703fcca335.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --variable code_folding=hide --variable code_menu=1##
## Output created: example1.htmlrmarkdown::render("example2.Rmd")##
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## label: session## output file: example2.knit.md## /home/mdz/anaconda3/bin/pandoc +RTS -K512m -RTS example2.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output example2.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --self-contained --variable bs3=TRUE --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --variable theme=bootstrap --include-in-header /tmp/Rtmp5Mw6Xi/rmarkdown-str2ce4707dc4266a.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --variable code_folding=hide --variable code_menu=1##
## Output created: example2.htmlrmarkdown::render("example3.Rmd")##
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## label: session## output file: example3.knit.md## /home/mdz/anaconda3/bin/pandoc +RTS -K512m -RTS example3.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output example3.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --self-contained --variable bs3=TRUE --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --variable theme=bootstrap --include-in-header /tmp/Rtmp5Mw6Xi/rmarkdown-str2ce4705f5bdb3d.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --variable code_folding=hide --variable code_menu=1##
## Output created: example3.htmlrmarkdown::render("example4.Rmd")##
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## label: session## output file: example4.knit.md## /home/mdz/anaconda3/bin/pandoc +RTS -K512m -RTS example4.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output example4.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --self-contained --variable bs3=TRUE --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --variable theme=bootstrap --include-in-header /tmp/Rtmp5Mw6Xi/rmarkdown-str2ce4704df7f6a3.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --variable code_folding=hide --variable code_menu=1##
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## label: session## output file: example5.knit.md## /home/mdz/anaconda3/bin/pandoc +RTS -K512m -RTS example5.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output example5.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --self-contained --variable bs3=TRUE --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --variable theme=bootstrap --include-in-header /tmp/Rtmp5Mw6Xi/rmarkdown-str2ce4706ba973ce.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --variable code_folding=hide --variable code_menu=1##
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## label: session## output file: example6.knit.md## /home/mdz/anaconda3/bin/pandoc +RTS -K512m -RTS example6.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output example6.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --self-contained --variable bs3=TRUE --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --variable theme=bootstrap --include-in-header /tmp/Rtmp5Mw6Xi/rmarkdown-str2ce470611eddd5.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --variable code_folding=hide --variable code_menu=1##
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## label: session## output file: example7.knit.md## /home/mdz/anaconda3/bin/pandoc +RTS -K512m -RTS example7.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output example7.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --self-contained --variable bs3=TRUE --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --variable theme=bootstrap --include-in-header /tmp/Rtmp5Mw6Xi/rmarkdown-str2ce470388905c3.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --variable code_folding=hide --variable code_menu=1##
## Output created: example7.htmlSummarise
Here I’m summarising the results of the five example data sets.
exdat=NULL
ex1dat <- readRDS("ex1dat.rds")
ex2dat <- readRDS("ex2dat.rds")
ex3dat <- readRDS("ex3dat.rds")
ex4dat <- readRDS("ex4dat.rds")
ex5dat <- readRDS("ex5dat.rds")
ex6dat <- readRDS("ex6dat.rds")
ex7dat <- readRDS("ex7dat.rds")
exdat <- rbind(ex1dat,ex2dat,ex3dat,ex4dat,ex5dat,ex6dat,ex7dat)
rownames(exdat) <- c("SRP128998", "SRP038101", "SRP096178","SRP038101","SRP247621","SRP253951","SRP068733")
exdat %>% kbl(caption="jaccard index values across seven RNA-seq studies") %>% kable_paper("hover", full_width = F)| FCS vs ORA | FCS: FDR vs nominal | ORA: FDR vs nominal | ORA vs ORA* | ORA vs ORA*nom | |
|---|---|---|---|---|---|
| SRP128998 | 0.6494118 | 0.7454874 | 0.5625000 | 0.4391785 | 0.3781965 |
| SRP038101 | 0.5360624 | 0.7978056 | 0.5513834 | 0.3631040 | 0.3297872 |
| SRP096178 | 0.6645963 | 0.6984479 | 0.5470297 | 0.4019608 | 0.3178295 |
| SRP038101 | 0.6292135 | 0.7652174 | 0.5547445 | 0.4209524 | 0.3745763 |
| SRP247621 | 0.4826087 | 0.5890052 | 0.3085106 | 0.1779242 | 0.1508380 |
| SRP253951 | 0.5710900 | 0.7806691 | 0.5094340 | 0.4003350 | 0.3588589 |
| SRP068733 | 0.5877863 | 0.6168675 | 0.5079365 | 0.2017094 | 0.1604140 |
means <- colMeans(exdat)
medians <- apply(exdat,2,median)
sds <- apply(exdat,2,sd)
summstats <- rbind(means,medians,sds)
summstats %>% kbl(caption="summary statistics of different enrichment analysis comparisons") %>% kable_paper("hover", full_width = F)| FCS vs ORA | FCS: FDR vs nominal | ORA: FDR vs nominal | ORA vs ORA* | ORA vs ORA*nom | |
|---|---|---|---|---|---|
| means | 0.5886813 | 0.7133572 | 0.5059341 | 0.3435949 | 0.2957858 |
| medians | 0.5877863 | 0.7454874 | 0.5470297 | 0.4003350 | 0.3297872 |
| sds | 0.0650955 | 0.0820368 | 0.0897487 | 0.1077847 | 0.0982811 |
Here let’s plot the jaccard scores. First as a boxplot and then overlay the dataset studies over the top.
cols <- c("#CC79A7","#56B4E9","#E69F00","#F0E442","#009E73","#0072B2","#D55E00")
coll <- list(cols, cols, cols, cols, cols)
par(mar=c(5,10,3,1))
boxplot(list(exdat[,5],exdat[,4],exdat[,3],exdat[,2],exdat[,1]),names = rev(colnames(exdat)),horizontal = TRUE, las=1 , col="white", cex=1.5,pch=19, xlab = "Jaccard index")
beeswarm(list(exdat[,5],exdat[,4],exdat[,3],exdat[,2],exdat[,1]),labels = rev(colnames(exdat)),horizontal = TRUE, las=1 , pwcol = coll,cex=1.5,pch=19, xlab = "Jaccard index",add = TRUE)
legend("bottomright", legend=c("SRP128998", "SRP038101", "SRP096178","SRP038101","SRP247621","SRP253951","SRP068733"), pch=19, col=cols, cex=1,pt.cex = 1.5)
pdf("images/jacbox1.pdf",width=5,height=4)
par(mar=c(5,9,3,2))
boxplot(list(exdat[,5],exdat[,4],exdat[,3],exdat[,2],exdat[,1]),names = rev(colnames(exdat)),horizontal = TRUE, las=1 , col="white", cex=1.5,pch=19, xlab = "Jaccard index")
beeswarm(list(exdat[,5],exdat[,4],exdat[,3],exdat[,2],exdat[,1]),labels = rev(colnames(exdat)),horizontal = TRUE, las=1 , pwcol = coll,cex=1.5,pch=19, xlab = "Jaccard index",add = TRUE)
legend("topleft", legend=c("SRP128998", "SRP038101", "SRP096178","SRP038101","SRP247621","SRP253951","SRP068733"), pch=19, col=cols, cex=1,pt.cex = 1.5)
dev.off()## png
## 2png("images/jacbox1.png")
par(mar=c(5,9,3,1))
boxplot(list(exdat[,5],exdat[,4],exdat[,3],exdat[,2],exdat[,1]),names = rev(colnames(exdat)),horizontal = TRUE, las=1 , col="white", cex=1.5,pch=19, xlab = "Jaccard index")
beeswarm(list(exdat[,5],exdat[,4],exdat[,3],exdat[,2],exdat[,1]),labels = rev(colnames(exdat)),horizontal = TRUE, las=1 , pwcol = coll,cex=1.5,pch=19, xlab = "Jaccard index",add = TRUE)
legend("bottomright", legend=c("SRP128998", "SRP038101", "SRP096178","SRP038101","SRP247621","SRP253951","SRP068733"), pch=19, col=cols, cex=1.2,pt.cex = 1.5)
dev.off()## png
## 2Now plot as a simple bargraph
mymean <- colMeans(exdat)
mysd <- apply(exdat,2,sd)
par(mar=c(5,10,3,1))
barplot(rev(colMeans(exdat)),xlab="mean Jaccard index",horiz = TRUE, las =1, xlim=c(0,.7) )
pdf("images/jacbar1.pdf",width=4,height=4)
par(mar=c(5,10,3,1))
barplot(rev(colMeans(exdat)),xlab="mean Jaccard index",horiz = TRUE, las =1, xlim=c(0,.7) )
dev.off()## png
## 2png("images/jacbar1.png")
par(mar=c(5,10,3,1))
barplot(rev(colMeans(exdat)),xlab="mean Jaccard index",horiz = TRUE, las =1, xlim=c(0,.7) )
dev.off()## png
## 2Session information
sessionInfo()## R version 4.1.2 (2021-11-01)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.3 LTS
##
## Matrix products: default
## BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0
##
## locale:
## [1] LC_CTYPE=en_AU.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_AU.UTF-8 LC_COLLATE=en_AU.UTF-8
## [5] LC_MONETARY=en_AU.UTF-8 LC_MESSAGES=en_AU.UTF-8
## [7] LC_PAPER=en_AU.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_AU.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] parallel stats4 stats graphics grDevices utils datasets
## [8] methods base
##
## other attached packages:
## [1] beeswarm_0.4.0 eulerr_6.1.1
## [3] kableExtra_1.3.4 mitch_1.4.1
## [5] clusterProfiler_4.0.5 DESeq2_1.32.0
## [7] SummarizedExperiment_1.22.0 Biobase_2.52.0
## [9] MatrixGenerics_1.4.3 matrixStats_0.61.0
## [11] GenomicRanges_1.44.0 GenomeInfoDb_1.28.4
## [13] IRanges_2.26.0 S4Vectors_0.30.2
## [15] BiocGenerics_0.38.0 getDEE2_1.2.0
##
## loaded via a namespace (and not attached):
## [1] shadowtext_0.1.1 fastmatch_1.1-3 systemfonts_1.0.3
## [4] plyr_1.8.6 igraph_1.2.11 lazyeval_0.2.2
## [7] polylabelr_0.2.0 splines_4.1.2 BiocParallel_1.26.2
## [10] ggplot2_3.3.5 digest_0.6.29 yulab.utils_0.0.4
## [13] htmltools_0.5.2 GOSemSim_2.18.1 viridis_0.6.2
## [16] GO.db_3.13.0 fansi_1.0.0 magrittr_2.0.1
## [19] memoise_2.0.1 Biostrings_2.60.2 annotate_1.70.0
## [22] graphlayouts_0.8.0 svglite_2.0.0 enrichplot_1.12.3
## [25] colorspace_2.0-2 rvest_1.0.2 blob_1.2.2
## [28] ggrepel_0.9.1 xfun_0.29 dplyr_1.0.7
## [31] crayon_1.4.2 RCurl_1.98-1.5 jsonlite_1.7.2
## [34] scatterpie_0.1.7 genefilter_1.74.1 survival_3.2-13
## [37] ape_5.6-1 glue_1.6.0 polyclip_1.10-0
## [40] gtable_0.3.0 zlibbioc_1.38.0 XVector_0.32.0
## [43] webshot_0.5.2 htm2txt_2.1.1 DelayedArray_0.18.0
## [46] scales_1.1.1 DOSE_3.18.3 DBI_1.1.2
## [49] GGally_2.1.2 Rcpp_1.0.7 viridisLite_0.4.0
## [52] xtable_1.8-4 gridGraphics_0.5-1 tidytree_0.3.7
## [55] bit_4.0.4 htmlwidgets_1.5.4 httr_1.4.2
## [58] fgsea_1.18.0 gplots_3.1.1 RColorBrewer_1.1-2
## [61] ellipsis_0.3.2 pkgconfig_2.0.3 reshape_0.8.8
## [64] XML_3.99-0.8 farver_2.1.0 sass_0.4.0
## [67] locfit_1.5-9.4 utf8_1.2.2 ggplotify_0.1.0
## [70] tidyselect_1.1.1 rlang_0.4.12 reshape2_1.4.4
## [73] later_1.3.0 AnnotationDbi_1.54.1 munsell_0.5.0
## [76] tools_4.1.2 cachem_1.0.6 downloader_0.4
## [79] generics_0.1.1 RSQLite_2.2.9 evaluate_0.14
## [82] stringr_1.4.0 fastmap_1.1.0 yaml_2.2.1
## [85] ggtree_3.0.4 knitr_1.37 bit64_4.0.5
## [88] tidygraph_1.2.0 caTools_1.18.2 purrr_0.3.4
## [91] KEGGREST_1.32.0 ggraph_2.0.5 nlme_3.1-153
## [94] mime_0.12 aplot_0.1.2 xml2_1.3.3
## [97] DO.db_2.9 rstudioapi_0.13 compiler_4.1.2
## [100] png_0.1-7 treeio_1.16.2 tibble_3.1.6
## [103] tweenr_1.0.2 geneplotter_1.70.0 bslib_0.3.1
## [106] stringi_1.7.6 highr_0.9 lattice_0.20-45
## [109] Matrix_1.4-0 vctrs_0.3.8 pillar_1.6.4
## [112] lifecycle_1.0.1 jquerylib_0.1.4 data.table_1.14.2
## [115] cowplot_1.1.1 bitops_1.0-7 httpuv_1.6.5
## [118] patchwork_1.1.1 qvalue_2.24.0 R6_2.5.1
## [121] promises_1.2.0.1 KernSmooth_2.23-20 echarts4r_0.4.3
## [124] gridExtra_2.3 gtools_3.9.2 MASS_7.3-54
## [127] assertthat_0.2.1 GenomeInfoDbData_1.2.6 grid_4.1.2
## [130] ggfun_0.0.4 tidyr_1.1.4 rmarkdown_2.11
## [133] ggforce_0.3.3 shiny_1.7.1