PMC Survey QC Analysis
Mark Ziemann & Kaumadi Wijesooriya
2021-09-01
Intro
Here we are performing an analysis of 200 articles which is randomly selected from 1500 PMC articles.
knitr::opts_chunk$set(fig.width=7, fig.height=5)
library("wordcloud")## Loading required package: RColorBrewerlibrary("RColorBrewer")
library("wordcloud2")
library("reutils")
library("XML")
library("kableExtra")
library("Biobase")## Loading required package: BiocGenerics## Loading required package: parallel##
## Attaching package: 'BiocGenerics'## The following objects are masked from 'package:parallel':
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## clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
## clusterExport, clusterMap, parApply, parCapply, parLapply,
## parLapplyLB, parRapply, parSapply, parSapplyLB## The following objects are masked from 'package:stats':
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## IQR, mad, sd, var, xtabs## The following objects are masked from 'package:base':
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## anyDuplicated, append, as.data.frame, basename, cbind, colnames,
## dirname, do.call, duplicated, eval, evalq, Filter, Find, get, grep,
## grepl, intersect, is.unsorted, lapply, Map, mapply, match, mget,
## order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
## rbind, Reduce, rownames, sapply, setdiff, sort, table, tapply,
## union, unique, unsplit, which.max, which.min## Welcome to Bioconductor
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## Vignettes contain introductory material; view with
## 'browseVignettes()'. To cite Bioconductor, see
## 'citation("Biobase")', and for packages 'citation("pkgname")'.##
## Attaching package: 'Biobase'## The following object is masked from 'package:reutils':
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## contentlibrary("vioplot")## Loading required package: sm## Warning in fun(libname, pkgname): couldn't connect to display ":0"## Package 'sm', version 2.2-5.6: type help(sm) for summary information## Loading required package: zoo##
## Attaching package: 'zoo'## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numericOverview of included and excluded analyses
x <- read.table("data/QC-analysis2.tsv",header=TRUE,fill=TRUE,sep="\t")
head(x)## Pubmed.Central.ID Article.number Allocated Journal
## 1 PMC6493771 691 - PLoS Comput Biol
## 2 PMC6442023 462 - Front Pharmacol
## 3 PMC6384238 213 - Front Oncol
## 4 PMC6594459 1172 - Ann Oncol
## 5 PMC6649552 1407 - Cell Cycle
## 6 PMC6478283 637 - PLoS One
## Omics.type Organism
## 1 EXCLUDE EXCLUDE
## 2 RNA-seq Homo sapiens, Rattus norvegicus
## 3 Gene expression array, RNA-seq Homo sapiens
## 4 Database Homo sapiens
## 5 RNA-seq Mus musculus
## 6 Database Homo sapiens
## Gene.set.library GS.version Statistical.test.used
## 1 EXCLUDE EXCLUDE EXCLUDE
## 2 GEO No GSEA
## 3 GO, KEGG No Not stated
## 4 MSigDB No GSEA
## 5 GO, KEGG No Not stated
## 6 KEGG, Reactome, PID, DisGeNET, GO No Not stated
## FDR.Correction App.used App.Version Code.availability
## 1 EXCLUDE EXCLUDE EXCLUDE EXCLUDE
## 2 No GSEA Yes <NA>
## 3 Yes clusterProfiler No <NA>
## 4 No GSEA Yes <NA>
## 5 No DAVID No <NA>
## 6 No ToppGene No <NA>
## Background.gene.set Assumptions.violated Gene.lists.provided
## 1 EXCLUDE EXCLUDE EXCLUDE
## 2 <NA> FDR No
## 3 Not stated Background Yes
## 4 <NA> FDR No
## 5 Not stated Background, FDR No
## 6 Not stated Background, FDR Yes
## Separated.up.and.down Parameters
## 1 - -
## 2 - rank=no, algo=no, weight=no
## 3 - -
## 4 - rank=yes, algo=yes, weight=no
## 5 Combined -
## 6 - -colnames(x)## [1] "Pubmed.Central.ID" "Article.number" "Allocated"
## [4] "Journal" "Omics.type" "Organism"
## [7] "Gene.set.library" "GS.version" "Statistical.test.used"
## [10] "FDR.Correction" "App.used" "App.Version"
## [13] "Code.availability" "Background.gene.set" "Assumptions.violated"
## [16] "Gene.lists.provided" "Separated.up.and.down" "Parameters"dim(x)## [1] 249 18exclude <- subset(x,x$GS.version=="EXCLUDE")
nrow(exclude)## [1] 14length(unique(exclude$Pubmed.Central.ID))## [1] 14x <- subset(x,x$GS.version!="EXCLUDE")
nrow(x)## [1] 235length(unique(x$Pubmed.Central.ID))## [1] 186Journal
journal <- x$Journal
journal_split <- strsplit(journal,", ")
journal <- unlist(journal_split)
res <- table(journal)
res <- res[order(res)]
length(res)## [1] 96res## journal
## 3 Biotech Am J Physiol Gastrointest Liver Physiol
## 1 1
## Animals (Basel) Ann Oncol
## 1 1
## Appl Environ Microbiol Biosci Rep
## 1 1
## BMC Infect Dis BMC Med Genet
## 1 1
## BMC Med Genomics BMC Musculoskelet Disord
## 1 1
## Cancer Control Cancers (Basel)
## 1 1
## Cell Cycle Cell Death Discov
## 1 1
## Cells Chin Med
## 1 1
## Commun Biol Endocrinology
## 1 1
## FEBS Open Bio Genome Biol Evol
## 1 1
## Genomics Inform Heliyon
## 1 1
## Hepatology Int J Endocrinol
## 1 1
## Int J Nanomedicine Int J Ophthalmol
## 1 1
## J Assist Reprod Genet J Bacteriol
## 1 1
## J Cancer J Cardiovasc Dev Dis
## 1 1
## J Diabetes Investig J Immunother Cancer
## 1 1
## J Invest Dermatol J Ovarian Res
## 1 1
## J Res Med Sci J Transl Med
## 1 1
## J Virol Medicine (Baltimore)
## 1 1
## Mol Breed Mol Ther Nucleic Acids
## 1 1
## Neurobiol Dis Nutrients
## 1 1
## Radiat Res Respir Res
## 1 1
## Stem Cells Int Thyroid
## 1 1
## Toxicol Sci Virology
## 1 1
## World J Gastrointest Oncol Am J Transl Res
## 1 2
## Arch Med Sci BMC Genet
## 2 2
## Cell Commun Signal Cell Death Dis
## 2 2
## Clin Cancer Res Clin Epigenetics
## 2 2
## Clin Proteomics Diabetes Metab Syndr Obes
## 2 2
## Dis Markers Epigenetics
## 2 2
## Front Neurosci Front Physiol
## 2 2
## Genes (Basel) J Hematol Oncol
## 2 2
## Med Sci Monit Metabolomics
## 2 2
## Mol Med Rice (N Y)
## 2 2
## Transl Psychiatry Viruses
## 2 2
## Biol Open BMC Bioinformatics
## 3 3
## BMC Cancer Cancer Cell Int
## 3 3
## Front Immunol Int J Mol Sci
## 3 3
## J Clin Med Mol Autism
## 3 3
## Aging (Albany NY) Exp Ther Med
## 4 4
## Front Oncol Front Pharmacol
## 4 4
## Metabolites Mol Med Rep
## 4 4
## Oncotarget RNA Biol
## 4 4
## Cancer Manag Res Biomed Res Int
## 5 6
## Onco Targets Ther Oncol Rep
## 6 7
## Front Genet BMC Genomics
## 8 9
## Oncol Lett PeerJ
## 9 11
## Sci Rep PLoS One
## 12 15par(mar=c(1,1,1,1))
#names(res) <- gsub("Gene expression array","RNA array",names(res))
wordcloud(words = names(res), freq = res, min.freq = 1,
max.words=200, random.order=FALSE, rot.per=0.35,
colors=brewer.pal(8, "Dark2"))## Warning in wordcloud(words = names(res), freq = res, min.freq = 1, max.words =
## 200, : Cell Commun Signal could not be fit on page. It will not be plotted.## Warning in wordcloud(words = names(res), freq = res, min.freq = 1, max.words =
## 200, : Am J Physiol Gastrointest Liver Physiol could not be fit on page. It will
## not be plotted.## Warning in wordcloud(words = names(res), freq = res, min.freq = 1, max.words =
## 200, : Appl Environ Microbiol could not be fit on page. It will not be plotted.## Warning in wordcloud(words = names(res), freq = res, min.freq = 1, max.words
## = 200, : BMC Musculoskelet Disord could not be fit on page. It will not be
## plotted.## Warning in wordcloud(words = names(res), freq = res, min.freq = 1, max.words =
## 200, : Cancers (Basel) could not be fit on page. It will not be plotted.## Warning in wordcloud(words = names(res), freq = res, min.freq = 1, max.words =
## 200, : Int J Nanomedicine could not be fit on page. It will not be plotted.## Warning in wordcloud(words = names(res), freq = res, min.freq = 1, max.words =
## 200, : Int J Ophthalmol could not be fit on page. It will not be plotted.## Warning in wordcloud(words = names(res), freq = res, min.freq = 1, max.words =
## 200, : J Assist Reprod Genet could not be fit on page. It will not be plotted.## Warning in wordcloud(words = names(res), freq = res, min.freq = 1, max.words =
## 200, : J Cardiovasc Dev Dis could not be fit on page. It will not be plotted.## Warning in wordcloud(words = names(res), freq = res, min.freq = 1, max.words =
## 200, : J Diabetes Investig could not be fit on page. It will not be plotted.## Warning in wordcloud(words = names(res), freq = res, min.freq = 1, max.words =
## 200, : J Immunother Cancer could not be fit on page. It will not be plotted.## Warning in wordcloud(words = names(res), freq = res, min.freq = 1, max.words =
## 200, : J Invest Dermatol could not be fit on page. It will not be plotted.## Warning in wordcloud(words = names(res), freq = res, min.freq = 1, max.words =
## 200, : J Ovarian Res could not be fit on page. It will not be plotted.## Warning in wordcloud(words = names(res), freq = res, min.freq = 1, max.words =
## 200, : Medicine (Baltimore) could not be fit on page. It will not be plotted.## Warning in wordcloud(words = names(res), freq = res, min.freq = 1, max.words =
## 200, : Mol Ther Nucleic Acids could not be fit on page. It will not be plotted.## Warning in wordcloud(words = names(res), freq = res, min.freq = 1, max.words =
## 200, : Neurobiol Dis could not be fit on page. It will not be plotted.## Warning in wordcloud(words = names(res), freq = res, min.freq = 1, max.words =
## 200, : Nutrients could not be fit on page. It will not be plotted.## Warning in wordcloud(words = names(res), freq = res, min.freq = 1, max.words =
## 200, : Respir Res could not be fit on page. It will not be plotted.## Warning in wordcloud(words = names(res), freq = res, min.freq = 1, max.words =
## 200, : Stem Cells Int could not be fit on page. It will not be plotted.## Warning in wordcloud(words = names(res), freq = res, min.freq = 1, max.words =
## 200, : Virology could not be fit on page. It will not be plotted.## Warning in wordcloud(words = names(res), freq = res, min.freq = 1, max.words
## = 200, : World J Gastrointest Oncol could not be fit on page. It will not be
## plotted.
par(mar=c(5,12,3,5))
barplot(tail(res,20),horiz=TRUE,las=1,cex.names = 0.7, xlab="no. analyses",
main = "Journal", xlim=c(0,17))
grid()
other <- sum(res[1:(nrow(res)-10)])
res2 <- c(other,tail(res,9))
names(res2)[1] <- "Other"
par(mar=c(5,12,3,5))
barplot(res2,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Journal", xlim=c(0,165))
text(y = (1:length(res2)*1.2)-1.2 , x = res2 + 7, label = res2, pos = 3, cex = 1, col = "black")
dir.create("images")## Warning in dir.create("images"): 'images' already existspng("images/journals2.png",width=400,height=300)
par(mar=c(5,12,3,3))
barplot(res2,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Journal", xlim=c(0,170))
text(y = (1:length(res2)*1.2)-1.2 , x = res2 + 10, label = res2, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2pdf("images/journals2.pdf",width=4,height=4)
par(mar=c(5,9,3,2))
barplot(res2,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Journal", xlim=c(0,180))
text(y = (1:length(res2)*1.2)-1.2 , x = res2 + 15, label = res2, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2Omics type
omics <- x$Omics.type
omics_split <- strsplit(omics,", ")
omics <- unlist(omics_split)
res <- table(omics)
res <- res[order(res)]
length(res)## [1] 18res## omics
## Metgenomics miRNA-seq
## 1 1
## NanoString gene expression PCR Array
## 1 1
## PPI scRNA-seq
## 1 1
## DNA methylation sequencing miRNA array
## 2 2
## CNV array Genotyping array
## 3 5
## Protein array DNA methylation array
## 6 7
## Genome sequencing Proteomics
## 10 14
## Metabolomics Database
## 15 19
## RNA-seq Gene expression array
## 70 91par(mar=c(1,1,1,1))
names(res) <- gsub("Gene expression array","RNA array",names(res))
wordcloud(words = names(res), freq = res, min.freq = 1,
max.words=200, random.order=FALSE, rot.per=0.35,
colors=brewer.pal(8, "Dark2"))
par(mar=c(5,12,3,5))
barplot(tail(res,20),horiz=TRUE,las=1,cex.names = 0.7, xlab="no. analyses",
main = "Omics type", xlim=c(0,100))
grid()
names(res) <- gsub("RNA array","Gene expression array",names(res))
other <- sum(res[1:(nrow(res)-10)])
res2 <- c(other,tail(res,9))
names(res2)[1] <- "Other"
par(mar=c(5,12,3,5))
barplot(res2,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Omics type", xlim=c(0,100))
text(y = (1:length(res2)*1.2)-1.2 , x = res2+5, label = res2, pos = 3, cex = 1, col = "black")
png("images/omics2.png",width=400,height=300)
par(mar=c(5,12,3,3))
barplot(res2,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Omics type", xlim=c(0,100))
text(y = (1:length(res2)*1.2)-1.2 , x = res2 + 6, label = res2, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2pdf("images/omics2.pdf",width=4,height=4)
par(mar=c(5,10,3,2))
barplot(res2,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Omics type", xlim=c(0,110))
text(y = (1:length(res2)*1.2)-1.2 , x = res2 + 10, label = res2, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2Organism
org <- x$Organism
org_split <- strsplit(org,", ")
org <- unlist(org_split)
res <- table(org)
res <- res[order(res)]
length(res)## [1] 31res## org
## Acropora cervicornis Aedes aegypti Ananas comosus
## 1 1 1
## Anas platyrhynchos Bos grunniens Brassica napus
## 1 1 1
## Candida albicans Canis lupus familiaris Clostridium scindens
## 1 1 1
## Coturnix japonica Moschus berezovskii Mycobacterium smegmatis
## 1 1 1
## Oreochromis niloticus Oryctolagus cuniculus Pygoscelis antarcticus
## 1 1 1
## Pygoscelis papua Salvelinus alpinus Suaeda salsa
## 1 1 1
## Triticum aestivum Vicia faba Bemisia tabaci
## 1 1 2
## Mauremys reevesii Mizuhopecten yessoensis Pagrus major
## 2 2 2
## Sclerotinia sclerotiorum Oryza sativa Bos taurus
## 2 5 7
## Sus scrofa Rattus norvegicus Mus musculus
## 7 10 24
## Homo sapiens
## 157par(mar=c(1,1,1,1))
names(res) <- gsub("Homo sapiens","human",names(res))
wordcloud(words = names(res), freq = res, min.freq = 1,
max.words=200, random.order=FALSE, rot.per=0.35,
colors=brewer.pal(8, "Dark2"), scale=c(4,.5))
par(mar=c(5,12,3,5))
names(res) <- gsub("human","Homo sapiens",names(res))
barplot(tail(res,20),horiz=TRUE,las=1,cex.names = 0.7, xlab="no. analyses",
main = "Organism", xlim=c(0,200))
grid()
other <- sum(res[1:(nrow(res)-10)])
res2 <- c(other,tail(res,9))
names(res2)[1] <- "Other"
par(mar=c(5,12,3,5))
barplot(res2,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Organism", xlim=c(0,200))
text(y = (1:length(res2)*1.2)-1.2 , x = res2+7, label = res2, pos = 3, cex = 1, col = "black")
png("images/organisms2.png",width=400,height=300)
par(mar=c(5,12,3,3))
barplot(res2,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Organism", xlim=c(0,200))
text(y = (1:length(res2)*1.2)-1.2 , x = res2 + 15, label = res2, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2pdf("images/organisms2.pdf",width=4,height=4)
par(mar=c(5,11,3,2))
barplot(res2,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Organism", xlim=c(0,200))
text(y = (1:length(res2)*1.2)-1.2 , x = res2 + 25, label = res2, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2Gene set library
GSL <-x$Gene.set.library
GSL_split <- strsplit(GSL,", ")
GSL <- unlist(GSL_split)
res <- table(GSL)
res <- res[order(res)]
length(res)## [1] 26which(names(res)=="Not stated")/sum(res)*100## [1] 6.325301res## GSL
## ChemRICH COG CYTOBAND
## 1 1 1
## DisGeNET GEO Human Metabolome Database
## 1 1 1
## Ingenuity Knowledge base InterPro Jensen Diseases database
## 1 1 1
## MetaCore Metascape OMIM
## 1 1 1
## Pathway commons PID SIGNOR
## 1 1 1
## TRANSFAC Vectorbase JASPAR
## 1 1 2
## MetaboAnalyst BioCarta Not stated
## 2 3 14
## Reactome MSigDB Ingenuity Knowledge Base
## 16 20 23
## KEGG GO
## 114 121par(mar=c(1,1,1,1))
names(res) <- gsub("Homo sapiens","human",names(res))
wordcloud(words = names(res), freq = res, min.freq = 1,
max.words=200, random.order=FALSE, rot.per=0.35,
colors=brewer.pal(8, "Dark2"))
par(mar=c(5,12,3,5))
barplot(tail(res,20),horiz=TRUE,las=1,cex.names = 0.7, xlab="no. analyses",
main = "Gene set library", xlim=c(0,140))
grid()
other <- sum(res[1:(nrow(res)-10)])
res2 <- c(other,tail(res,9))
names(res2)[1] <- "Other"
par(mar=c(5,12,3,5))
barplot(res2,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Gene set library", xlim=c(0,140))
text(y = (1:length(res2)*1.2)-1.2 , x = res2+7, label = res2, pos = 3, cex = 1, col = "black")
png("images/genesetlib2.png",width=400,height=300)
par(mar=c(5,12,3,3))
barplot(res2,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Gene set library", xlim=c(0,150))
text(y = (1:length(res2)*1.2)-1.2 , x = res2 + 15, label = res2, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2pdf("images/genesetlib2.pdf",width=4,height=4)
par(mar=c(5,11,3,2))
barplot(res2,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Gene set library", xlim=c(0,150))
text(y = (1:length(res2)*1.2)-1.2 , x = res2 + 16, label = res2, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2Gene set version
GSV <-x$GS.version
res <- table(GSV)
res## GSV
## No Yes
## 217 18res[1]/sum(res)*100## No
## 92.34043par(mar=c(14,12,3,10))
barplot(tail(res,20),horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Gene set version defined", xlim=c(0,250))
text(y = (1:length(res)*1.2) - 0.75 , x = res+15, label = res, pos = 3, cex = 1, col = "black")
png("images/genesetvers2.png",width=300,height=150)
par(mar=c(5,5,3,3))
barplot(res,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Gene set version defined", xlim=c(0,250))
text(y = (1:length(res)*1.2)-1.2 , x = res + 20, label = res, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2pdf("images/genesetvers2.pdf",width=3,height=2)
par(mar=c(5,4,3,2))
barplot(res,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Gene set version defined", xlim=c(0,260))
text(y = (1:length(res)*1.2)-1.2 , x = res + 25, label = res, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2Statistical test used
test <-x$Statistical.test.used
test <- strsplit(test,", ")
test <- unlist(test)
res <- table(test)
res <- res[order(res)]
res[which(names(res)=="Not stated")] / sum(res) * 100## Not stated
## 56.30252length(res)## [1] 12res## test
## Binomial EASE GSVA
## 1 1 1
## Kruskal-Wallis modified Chi-squared MSEA
## 1 1 1
## Kolmogorov–Smirnov No test Fisher
## 2 14 24
## GSEA Hypergeometric Not stated
## 29 29 134par(mar=c(1,1,1,1))
wordcloud(words = names(res), freq = res, min.freq = 1,
max.words=200, random.order=FALSE, rot.per=0.35,
colors=brewer.pal(8, "Dark2"))
par(mar=c(5,12,3,5))
barplot(tail(res,20),horiz=TRUE,las=1,cex.names = 0.7, xlab="no. analyses",
main = "Test used", xlim=c(0,150))
grid()
other <- sum(res[1:(nrow(res)-10)])
res2 <- c(other,tail(res,9))
names(res2)[1] <- "Other"
par(mar=c(5,12,3,5))
barplot(res2,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Test used", xlim=c(0,150))
text(y = (1:length(res2)*1.2)-1.1 , x = res2+10, label = res2, pos = 3, cex = 1, col = "black")
png("images/stattest2.png",width=400,height=300)
par(mar=c(5,12,3,3))
barplot(res2,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Test used", xlim=c(0,160))
text(y = (1:length(res2)*1.2)-1.2 , x = res2 + 15, label = res2, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2pdf("images/stattest2.pdf",width=4,height=4)
par(mar=c(5,11,3,2))
barplot(res2,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Test used", xlim=c(0,170))## Warning in axis(if (horiz) 2 else 1, at = at.l, labels = names.arg, lty =
## axis.lty, : conversion failure on 'Kolmogorov–Smirnov' in 'mbcsToSbcs': dot
## substituted for <e2>## Warning in axis(if (horiz) 2 else 1, at = at.l, labels = names.arg, lty =
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## substituted for <80>## Warning in axis(if (horiz) 2 else 1, at = at.l, labels = names.arg, lty =
## axis.lty, : conversion failure on 'Kolmogorov–Smirnov' in 'mbcsToSbcs': dot
## substituted for <93>## Warning in axis(if (horiz) 2 else 1, at = at.l, labels = names.arg, lty =
## axis.lty, : conversion failure on 'Kolmogorov–Smirnov' in 'mbcsToSbcs': dot
## substituted for <e2>## Warning in axis(if (horiz) 2 else 1, at = at.l, labels = names.arg, lty =
## axis.lty, : conversion failure on 'Kolmogorov–Smirnov' in 'mbcsToSbcs': dot
## substituted for <80>## Warning in axis(if (horiz) 2 else 1, at = at.l, labels = names.arg, lty =
## axis.lty, : conversion failure on 'Kolmogorov–Smirnov' in 'mbcsToSbcs': dot
## substituted for <93>text(y = (1:length(res2)*1.2)-1.2 , x = res2 + 20, label = res2, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2FDR Correction
fdr <-x$FDR.Correction
fdr <- strsplit(fdr,", ")
fdr <- unlist(fdr)
res <- table(fdr)
res <- res[order(res)]
res[which(names(res)!="Yes")]/sum(res)*100## fdr
## Not stated No test No
## 3.846154 5.982906 39.316239res## fdr
## Not stated No test No Yes
## 9 14 92 119par(mar=c(1,1,1,5))
wordcloud(words = names(res), freq = res, min.freq = 1,
max.words=200, random.order=FALSE, rot.per=0.35,
colors=brewer.pal(8, "Dark2"))
par(mar=c(10,12,3,5))
barplot(tail(res,20),horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "FDR correction performed", xlim=c(0,150))
text(y = (1:length(res)*1.2) - 0.8 , x = res+10, label = res, pos = 3, cex = 1, col = "black")
png("images/fdr2.png",width=300,height=200)
par(mar=c(5,8,3,3))
barplot(res,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "FDR correction performed", xlim=c(0,160))
text(y = (1:length(res)*1.2)-1.2 , x = res + 15, label = res, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2pdf("images/fdr2.pdf",width=3,height=3)
par(mar=c(5,5,3,2))
barplot(res,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "FDR correction performed", xlim=c(0,160))
text(y = (1:length(res)*1.2)-1.0 , x = res + 15, label = res, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2App used
App <-x$App.used
App_split <- strsplit(App,", ")
App <- unlist(App_split)
res <- table(App)
res <- res[order(res)]
res[which(names(res)=="Not stated")]/sum(res)*100## Not stated
## 6.382979length(res)## [1] 50res## App
## anamiR ChemRICH
## 1 1
## Custom MATLAB script Cytoscape (No plugin stated)
## 1 1
## EggNOG fgsea
## 1 1
## FunRich g:GOSt
## 1 1
## GAGE GENCLIP
## 1 1
## GeneCodis GO: TermFinder
## 1 1
## GO::TermFinder GSVA
## 1 1
## KSEA Limma
## 1 1
## Metascape Molecule Annotation System
## 1 1
## MSEA NetworkAnalyst
## 1 1
## Pascal PathVisio
## 1 1
## R script ReactomePA
## 1 1
## SNP2GO R package topGO
## 1 1
## ToppGene webMeV
## 1 1
## agriGO BiNGO
## 2 2
## g:Profiler MetaCore
## 2 2
## STRING Custom R script
## 2 3
## GOrilla KAAS
## 3 3
## Mummichog Blast2GO
## 3 4
## WebGestalt ClueGO/Cytoscape
## 4 5
## Enrichr GOseq
## 5 5
## MetaboAnalyst KOBAS
## 7 9
## clusterProfiler PANTHER
## 10 10
## Not stated Ingenuity Pathway Analysis
## 15 26
## GSEA DAVID
## 30 55par(mar=c(1,1,1,1))
wordcloud(words = names(res), freq = res, min.freq = 1,
max.words=200, random.order=FALSE, rot.per=0.35,
colors=brewer.pal(8, "Dark2"))
par(mar=c(5,12,3,5))
barplot(tail(res,20),horiz=TRUE,las=1,cex.names = 0.7, xlab="no. analyses",
main = "App used", xlim=c(0,60))
grid()
other <- sum(res[1:(nrow(res)-10)])
res2 <- c(other,tail(res,9))
names(res2)[1] <- "Other"
par(mar=c(5,12,3,5))
barplot(res2,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "App used", xlim=c(0,80))
text(y = (1:length(res2)*1.2)-1.1 , x = res2+5, label = res2, pos = 3, cex = 1, col = "black")
png("images/app2.png",width=400,height=300)
par(mar=c(5,12,3,3))
barplot(res2,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "App used", xlim=c(0,80))
text(y = (1:length(res2)*1.2)-1.2 , x = res2 + 5, label = res2, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2pdf("images/app2.pdf",width=4,height=4)
par(mar=c(5,12,3,2))
barplot(res2,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "App used", xlim=c(0,80))
text(y = (1:length(res2)*1.2)-1.2 , x = res2 + 10, label = res2, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2App version
APV <-x$App.Version
res <- table(APV)
res## APV
## No Yes
## 167 68res[1]/sum(res)*100## No
## 71.06383par(mar=c(14,12,3,5))
barplot(tail(res,20),horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "App version defined", xlim=c(0,200))
text(y = (1:length(res)*1.2) - 0.75 , x = res+15, label = res, pos = 3, cex = 1, col = "black")
png("images/appvers2.png",width=300,height=150)
par(mar=c(5,5,3,3))
barplot(res,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "App version defined", xlim=c(0,200))
text(y = (1:length(res)*1.2)-1.2 , x = res + 15, label = res, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2pdf("images/appvers2.pdf",width=3,height=2)
par(mar=c(5,4,3,2))
barplot(res,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "App version defined", xlim=c(0,200))
text(y = (1:length(res)*1.2)-1.2 , x = res + 19, label = res, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2Code available
code <-x$Code.availability
res <- table(code)
res## code
## No Yes
## 44 3res[1]/sum(res)*100## No
## 93.61702par(mar=c(14,12,3,5))
barplot(tail(res,20),horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Code availability", xlim=c(0,50))
text(y = (1:length(res)*1.2) - 0.75 , x = res+2, label = res, pos = 3, cex = 1, col = "black")
png("images/code2.png",width=300,height=150)
par(mar=c(5,5,3,3))
barplot(res,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Code availability", xlim=c(0,50))
text(y = (1:length(res)*1.2)-1.2 , x = res + 3, label = res, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2pdf("images/code2.pdf",width=3,height=2)
par(mar=c(5,4,3,2))
barplot(res,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Code availability", xlim=c(0,55))
text(y = (1:length(res)*1.2)-1.2 , x = res + 5, label = res, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2Background gene set
BG <-x$Background.gene.set
BG <- gsub("Yes","Yes, correct",BG)
res <- table(BG)
res## BG
## No Not stated Stated, but incorrect
## 5 178 6
## Yes, correct
## 8sum(res[which(names(res)!="Yes")])/sum(res)*100## [1] 100par(mar=c(10,12,3,5))
barplot(tail(res,20),horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Background list specification", xlim=c(0,200))
text(y = (1:length(res)*1.2) - 0.85 , x = res+10, label = res, pos = 3, cex = 1, col = "black")
png("images/bg2.png",width=300,height=200)
par(mar=c(5,9,3,2))
barplot(res,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Background list specified", xlim=c(0,220))
text(y = (1:length(res)*1.2)-1.1 , x = res + 18, label = res, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2pdf("images/bg2.pdf",width=4,height=3)
par(mar=c(5,10,3,2))
barplot(res,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Background list specified", xlim=c(0,220))
text(y = (1:length(res)*1.2)-1.1 , x = res + 20, label = res, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2Gene lists provided
GL <-x$Gene.lists.provided
res <- table(GL)
res## GL
## No Yes
## 142 93sum(res[which(names(res)!="Yes")])/sum(res)*100## [1] 60.42553par(mar=c(14,12,3,5))
barplot(tail(res,20),horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Gene lists provided", xlim=c(0,160))
text(y = (1:length(res)*1.2) - 0.75 , x = res+8, label = res, pos = 3, cex = 1, col = "black")
png("images/genelists2.png",width=300,height=150)
par(mar=c(5,5,3,3))
barplot(res,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Gene lists provided", xlim=c(0,160))
text(y = (1:length(res)*1.2)-1.2 , x = res + 9, label = res, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2pdf("images/genelists2.pdf",width=3,height=2)
par(mar=c(5,4,3,2))
barplot(res,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Gene lists provided", xlim=c(0,170))
text(y = (1:length(res)*1.2)-1.25 , x = res + 15, label = res, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2Methodological flaws
ok <- nrow(subset(x,Assumptions.violated=="No"))
ok## [1] 35bad <- nrow(subset(x,Assumptions.violated!="No"))
bad## [1] 200ok/sum(bad,ok)*100## [1] 14.89362ass <-x$Assumptions.violated
ass <- gsub("^No$","None",ass)
ass <- strsplit(ass,", ")
ass <- unlist(ass)
res <- table(ass)
res <- res[order(res)]
res## ass
## Misinterpreted FDR values Inference without test No data shown
## 2 11 13
## None FDR Background
## 35 94 179par(mar=c(1,1,1,1))
wordcloud(words = names(res), freq = res, min.freq = 1,
max.words=200, random.order=FALSE, rot.per=0.35,
colors=brewer.pal(8, "Dark2"))
par(mar=c(8,12,3,5))
barplot(tail(res,20),horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Methodological flaws", xlim=c(0,200))
text(y = (1:length(res)*1.2) - 0.9 , x = res+8, label = res, pos = 3, cex = 1, col = "black")
png("images/assumptions2.png",width=400,height=250)
par(mar=c(5,12,3,2))
barplot(res,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Methodological flaws", xlim=c(0,220))
text(y = (1:length(res)*1.2)-1.1 , x = res + 18, label = res, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2pdf("images/assumptions2.pdf",width=4,height=3)
par(mar=c(5,11,3,2))
barplot(res,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Methodological flaws", xlim=c(0,230))
text(y = (1:length(res)*1.2)-1.2 , x = res + 25, label = res, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2Separated or combined
comb <-x$Separated.up.and.down
res <- table(comb)
res## comb
## - Combined Not stated Separated
## 126 76 5 28sum(res[which(names(res)!="Separated")])/sum(res)*100## [1] 88.08511res <- res[which(names(res)!="-")]
par(mar=c(10,12,3,5))
barplot(tail(res,20),horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Separated or combined ORA (differential expression)", xlim=c(0,90))
grid()
text(y = (1:length(res)*1.2) - 0.9 , x = res+5, label = res, pos = 3, cex = 1, col = "black")
png("images/comb2.png",width=300,height=200)
par(mar=c(5,8,3,2))
barplot(res,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Separated or combined ORA", xlim=c(0,100))
text(y = (1:length(res)*1.2)-1.1 , x = res + 5, label = res, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2pdf("images/comb2.pdf",width=3,height=2.5)
par(mar=c(5,5,3,2))
barplot(res,horiz=TRUE,las=1,cex.names = 1, xlab="no. analyses",
main = "Separated or combined ORA", xlim=c(0,100))
text(y = (1:length(res)*1.2)-1.1 , x = res + 10, label = res, pos = 3, cex = 1, col = "black")
dev.off()## png
## 2GSEA parameters
param <-x$Parameters
param <- param[which(param!="-")]
param <- gsub(" ","",param)
str(param)## chr [1:28] "rank=no,algo=no,weight=no" "rank=yes,algo=yes,weight=no" ...rankspec <- sapply(strsplit(param,","),"[[",1)
rankspec <- gsub("rank=","",rankspec)
rankspec <- table(rankspec)
rankspec## rankspec
## no yes
## 16 12algospec <- sapply(strsplit(param,","),"[[",2)
algospec <- gsub("algo=","",algospec)
algospec <- table(algospec)
algospec## algospec
## no yes
## 19 9weightspec <- sapply(strsplit(param,","),"[[",3)
weightspec <- gsub("weight=","",weightspec)
weightspec <- table(weightspec)
weightspec## weightspec
## no yes
## 24 4par(mar=c(10,12,3,4))
params <- rbind(rankspec,algospec,weightspec)
rownames(params) <- c("rank method", "test type", "weight type")
colnames(params) <- c("not stated", "stated")
barplot(t(params),horiz=TRUE,las=1,xlim=c(0,30),legend = colnames(params),
main="GSEA parameter reporting", xlab="no. analyses",
args.legend = list(x = "topleft", inset = c(0.05, 0.1)))
text(y = (1:nrow(params)*1.2) - 0.7 , x = params[,1]-3, label = params[,1], pos = 3, cex = 1, col = "white")
text(y = (1:nrow(params)*1.2) - 0.7 , x = params[,1]+2, label = params[,2], pos = 3, cex = 1, col = "black")
png("images/gseaparam2.png",width=350,height=250)
par(mar=c(5,8,3,2))
params <- rbind(rankspec,algospec,weightspec)
rownames(params) <- c("rank method", "test type", "weight type")
colnames(params) <- c("not stated", "stated")
barplot(t(params),horiz=TRUE,las=1,xlim=c(0,30),legend = colnames(params),
main="GSEA parameter reporting", xlab="no. analyses",
args.legend = list(x = "topleft", inset = c(0.05, 0.1)))
text(y = (1:nrow(params)*1.2) - 0.7 , x = params[,1]-3, label = params[,1], pos = 3, cex = 1, col = "white")
text(y = (1:nrow(params)*1.2) - 0.7 , x = params[,1]+2, label = params[,2], pos = 3, cex = 1, col = "black")
dev.off()## png
## 2pdf("images/gseaparam2.pdf",width=4.5,height=3)
par(mar=c(5,6,3,2))
barplot(t(params),horiz=TRUE,las=1,xlim=c(0,30),legend = colnames(params),
main="GSEA parameter reporting", xlab="no. analyses",
args.legend = list(x = "topleft", bg="white",inset = c(0.05, 0.1)))
text(y = (1:nrow(params)*1.2) - 0.8 , x = params[,1]-3, label = params[,1], pos = 3, cex = 1, col = "white")
text(y = (1:nrow(params)*1.2) - 0.8 , x = params[,1]+2, label = params[,2], pos = 3, cex = 1, col = "black")
dev.off()## png
## 2Score
Here I am proposing a scoring scheme. If there is information missing from the article, or basic mistakes are made, then a point is deducted. If the article goes over and above the basic reproducibility, then they are awarded a point.
Gene set library origin not stated = -1
Gene set library version not stated = -1
Stat test not stated = -1
No stat test conducted = -1
No FDR correction conducted = -1
App used not stated = -1
App version not stated = -1
Background list not defined = -1
Inappropriate background list used = -1
Code availability = +1
Gene lists provided = +1
score <- function(r){
r[is.na(r)] <- 0
SCORE=0
# gene set lib
if(r["Gene.set.library"]=="Not stated"){
SCORE=SCORE-1
}
# GS version
if(r["GS.version"]=="No"){
SCORE=SCORE-1
}
# stat test
if(r["Statistical.test.used"]=="No test"){
SCORE=SCORE-1
}
if(r["Statistical.test.used"]=="Not stated"){
SCORE=SCORE-1
}
# FDR
if(r["FDR.Correction"]!="Yes"){
SCORE=SCORE-1
}
# app used
if(r["App.used"]=="Not stated"){
SCORE=SCORE-1
}
# App version
if(r["App.Version"]=="No"){
SCORE=SCORE-1
}
# Code availability
if(r["Code.availability"]=="Yes"){
SCORE=SCORE+1
}
# Background
if(r["Background.gene.set"]=="Not stated"){
SCORE=SCORE-1
}
if(r["Background.gene.set"]=="No"){
SCORE=SCORE-1
}
if(r["Background.gene.set"]=="Stated, but incorrect"){
SCORE=SCORE-1
}
# gene list
if(r["Gene.lists.provided"]=="Yes"){
SCORE=SCORE+1
}
return(SCORE)
}
scores <- apply(X = x,MARGIN = 1, FUN = score)
barplot(table(scores), xlab="analysis score",ylab="frequency")
x$scores <- scores
length(which(scores>0))## [1] 1mean(x$scores)## [1] -3.276596sd(x$scores)## [1] 1.442667median(x$scores)## [1] -3Journal rank
jmetrics <- read.table("scimagojr_2020.csv",sep=";",header=TRUE,dec = ",")
jmetrics$Title <- toupper(jmetrics$Title)
head(jmetrics,3)## Rank Sourceid Title Type
## 1 1 28773 CA-A CANCER JOURNAL FOR CLINICIANS journal
## 2 2 19434 MMWR RECOMMENDATIONS AND REPORTS journal
## 3 3 20315 NATURE REVIEWS MOLECULAR CELL BIOLOGY journal
## Issn SJR SJR.Best.Quartile H.index Total.Docs...2020.
## 1 15424863, 00079235 62.937 Q1 168 47
## 2 10575987, 15458601 40.949 Q1 143 10
## 3 14710072, 14710080 37.461 Q1 431 115
## Total.Docs...3years. Total.Refs. Total.Cites..3years. Citable.Docs...3years.
## 1 119 3452 15499 80
## 2 9 1292 492 9
## 3 338 8439 10844 167
## Cites...Doc...2years. Ref....Doc. Country Region
## 1 126.34 73.45 United States Northern America
## 2 50.00 129.20 United States Northern America
## 3 32.83 73.38 United Kingdom Western Europe
## Publisher Coverage
## 1 Wiley-Blackwell 1950-2020
## 2 Centers for Disease Control and Prevention (CDC) 1990-2020
## 3 Nature Publishing Group 2000-2020
## Categories
## 1 Hematology (Q1); Oncology (Q1)
## 2 Epidemiology (Q1); Health Information Management (Q1); Health (social science) (Q1); Health, Toxicology and Mutagenesis (Q1); Medicine (miscellaneous) (Q1)
## 3 Cell Biology (Q1); Molecular Biology (Q1)dim(jmetrics)## [1] 32952 20nlmcat <- readLines("nlmcatalog_result.txt")
journaltitle <- nlmcat[grep("Title\\(s\\):",nlmcat)]
journaltitle <- gsub("Title\\(s\\): ","",journaltitle)
journaltitle <- gsub("\\.$","",journaltitle)
journaltitle <- toupper(journaltitle)
journalabbrev <- nlmcat[grep("Title Abbreviation:",nlmcat)]
journalabbrev <- sapply(strsplit(journalabbrev,":"),"[[",2)
journalabbrev <- gsub(" $","",journalabbrev)
journalabbrev <- gsub("^ ","",journalabbrev)
jdf <- data.frame(journalabbrev,journaltitle)
mjdf <- merge(jdf,jmetrics,by.x="journaltitle",by.y="Title")
xm <- merge(x,mjdf,by.x="Journal",by.y="journalabbrev",all.x = TRUE)Analysis scores vs Journal rank
tail(xm$Journal)## [1] "Transl Psychiatry" "Transl Psychiatry"
## [3] "Virology" "Viruses"
## [5] "Viruses" "World J Gastrointest Oncol"mylm1 <- lm (xm$scores ~ xm$SJR)
plot(xm$SJR,xm$scores, bty="n",
xlab="SJR",ylab="score",main="Association of analysis scores with journal metrics")
abline(mylm1,col="red")
cor.test(xm$scores,xm$SJR,method="pearson")##
## Pearson's product-moment correlation
##
## data: xm$scores and xm$SJR
## t = -0.30805, df = 174, p-value = 0.7584
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.1706771 0.1250053
## sample estimates:
## cor
## -0.0233465cor.test(xm$scores,xm$SJR,method="spearman")## Warning in cor.test.default(xm$scores, xm$SJR, method = "spearman"): Cannot
## compute exact p-value with ties##
## Spearman's rank correlation rho
##
## data: xm$scores and xm$SJR
## S = 893414, p-value = 0.8257
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
## rho
## 0.01671343Best and worst journals
Minimum of 5 analyses.
xmm <-xm[,c("Journal","scores")]
tab <- table(xmm$Journal)
tab <- tab[which(tab>3)]
xmm <- xmm[which(xmm$Journal %in% names(tab)),]
dim(xmm)## [1] 120 2jres <- aggregate(. ~ Journal, xmm ,mean)
jsd <- aggregate(. ~ Journal, xmm ,sd)
jres$sd <- jsd$scores
jres <- jres[order(jres$scores),]
dim(jres)## [1] 18 3head(jres)## Journal scores sd
## 17 RNA Biol -5.500000 0.5773503
## 5 Exp Ther Med -4.250000 0.9574271
## 7 Front Oncol -4.000000 0.8164966
## 10 Mol Med Rep -4.000000 0.8164966
## 12 Oncol Lett -3.888889 1.5365907
## 2 Biomed Res Int -3.833333 0.4082483par(mar=c(5,12,3,1))
barplot(tail(jres$scores,20),names.arg = tail(jres$Journal,20),horiz=TRUE,las=1,cex.names = 0.7, xlab="mean score",
main = "Highest scoring journals",xlim=c(-4,0))
grid()
par(mar=c(5,12,3,1))
barplot(head(jres$scores,20),names.arg = head(jres$Journal,20),horiz=TRUE,las=1,cex.names = 0.7, xlab="mean score",
main = "Lowest scoring journals",xlim=c(-5,0))
grid()
j <- unique(xmm$Journal)
jscores <- sapply(j,function(jj) {
xmm[which(xmm$Journal == jj ),2]
})
jscores <- jscores[order(unlist(lapply(jscores,mean)))]
par(mar=c(5,12,3,1))
vioplot(tail(jscores,20),horizontal = TRUE,las=1,cex.axis=0.75,main="Highest scoring journals")
par(mar=c(5,12,3,1))
vioplot(head(jscores,20),horizontal = TRUE,las=1,cex.axis=0.75,main="Lowest scoring journals")
Session information
sessionInfo()## R version 4.1.0 (2021-05-18)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.2 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 stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] vioplot_0.3.7 zoo_1.8-9 sm_2.2-5.6
## [4] Biobase_2.52.0 BiocGenerics_0.38.0 kableExtra_1.3.4
## [7] XML_3.99-0.6 reutils_0.2.3 wordcloud2_0.2.1
## [10] wordcloud_2.6 RColorBrewer_1.1-2
##
## loaded via a namespace (and not attached):
## [1] Rcpp_1.0.7 highr_0.9 bslib_0.2.5.1 compiler_4.1.0
## [5] jquerylib_0.1.4 bitops_1.0-7 tools_4.1.0 digest_0.6.27
## [9] lattice_0.20-44 viridisLite_0.4.0 jsonlite_1.7.2 evaluate_0.14
## [13] lifecycle_1.0.0 rlang_0.4.11 rstudioapi_0.13 yaml_2.2.1
## [17] xfun_0.25 fastmap_1.1.0 stringr_1.4.0 httr_1.4.2
## [21] knitr_1.33 xml2_1.3.2 systemfonts_1.0.2 htmlwidgets_1.5.3
## [25] sass_0.4.0 grid_4.1.0 webshot_0.5.2 svglite_2.0.0
## [29] glue_1.4.2 R6_2.5.1 tcltk_4.1.0 rmarkdown_2.10
## [33] magrittr_2.0.1 scales_1.1.1 htmltools_0.5.2 rvest_1.0.1
## [37] colorspace_2.0-2 stringi_1.7.4 RCurl_1.98-1.3 munsell_0.5.0