Last updated: 2020-01-26
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Knit directory: Comparative_APA/analysis/
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Unstaged changes:
Modified: analysis/ExploredAPA.Rmd
Modified: analysis/OppositeMap.Rmd
Modified: analysis/annotationInfo.Rmd
Modified: analysis/comp2apaQTLPAS.Rmd
Modified: analysis/correlationPhenos.Rmd
Modified: analysis/dAPAandapaQTL_DF.Rmd
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Modified: analysis/investigatePantro5.Rmd
Modified: analysis/multiMap.Rmd
Modified: analysis/speciesSpecific.Rmd
Modified: analysis/speciesSpecific_DF.Rmd
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File | Version | Author | Date | Message |
---|---|---|---|---|
Rmd | ac6b6b5 | brimittleman | 2020-01-26 | add overlap with all eQTLs |
html | 181523d | brimittleman | 2020-01-06 | Build site. |
Rmd | 3bc05f3 | brimittleman | 2020-01-06 | add empirical pvalues |
html | e5dff29 | brimittleman | 2020-01-06 | Build site. |
Rmd | 767ca26 | brimittleman | 2020-01-06 | add eQTL enrichment for eQTLs |
html | c633e63 | brimittleman | 2020-01-06 | Build site. |
Rmd | 5e85704 | brimittleman | 2020-01-06 | add overlap with eQTLs |
library(tidyverse)
── Attaching packages ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse 1.2.1 ──
✔ ggplot2 3.1.1 ✔ purrr 0.3.2
✔ tibble 2.1.1 ✔ dplyr 0.8.0.1
✔ tidyr 0.8.3 ✔ stringr 1.3.1
✔ readr 1.3.1 ✔ forcats 0.3.0
── Conflicts ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
library(workflowr)
This is workflowr version 1.5.0
Run ?workflowr for help getting started
In this analysis I will look at the overlap between DE genes and eQTLs identified in Li et al 2016. This is similar to the anaylsis I did for dAPA and I will use this as a way to benchmark those results.
explained=read.table("../data/Li_eqtls/explainedEgenes.txt",col.names = c("Gene.name"),stringsAsFactors = F)
unexplained=read.table("../data/Li_eqtls/UnexplainedEgenes.txt",col.names = c("Gene.name"),stringsAsFactors = F)
allEQTL= explained %>% full_join(unexplained)
Joining, by = "Gene.name"
nameID=read.table("../../genome_anotation_data/ensemble_to_genename.txt",sep="\t", header = T, stringsAsFactors = F)
DEgenes=read.table("../data/DiffExpression/DE_genes.txt", header = F,col.names = c("Gene_stable_ID"),stringsAsFactors = F) %>% inner_join(nameID, by="Gene_stable_ID") %>% dplyr::select(Gene.name)
DE_explained=DEgenes %>% inner_join(explained, by="Gene.name")
DE_unexplained=DEgenes %>% inner_join(unexplained, by="Gene.name")
neither=DEgenes %>% anti_join(explained, by="Gene.name") %>% anti_join(unexplained, by="Gene.name")
cat=c("Explained", "Unexaplained", "Neither")
num=c(nrow(DE_explained), nrow(DE_unexplained), nrow(neither))
DEqtl=as.data.frame(cbind(cat,num))
DEqtl$cat=factor(DEqtl$cat, levels=c("Explained","Unexaplained", "Neither"), ordered=T)
DEqtl$num=as.numeric(as.character(DEqtl$num ))
ggplot(DEqtl,aes(x=cat, y=num)) +geom_bar(stat="identity") + geom_text(aes(label=num), vjust=1.6, color="white", size=3.5) + labs(title="Differential Expression and human eQTL", y="Number of genes", x="Overlap")
Version | Author | Date |
---|---|---|
c633e63 | brimittleman | 2020-01-06 |
Proportion:
DEqtlProp=DEqtl %>% mutate(Prop=num/nrow(DEgenes))
ggplot(DEqtlProp,aes(x=cat, y=Prop)) +geom_bar(stat="identity") + geom_text(aes(label=round(Prop,digits = 3)), vjust=1.6, color="white", size=3.5) + labs(title="Differential Expression and human eQTL", y="Proportion of DE genes", x="Overlap")
Version | Author | Date |
---|---|---|
c633e63 | brimittleman | 2020-01-06 |
Look for enrichment:
permuteGenes <- function(InputGenes, nGenes, nTests){
#InputGenes=NuclearAPAtested_genes
#nGenes=nrow(sigNuclear_genes)
#nTests=100
explained=read.table("../data/Li_eqtls/explainedEgenes.txt",col.names = c("genes"),stringsAsFactors = F)
unexplained=read.table("../data/Li_eqtls/UnexplainedEgenes.txt",col.names = c("genes"),stringsAsFactors = F)
explainedOverlap=c()
unexplainedOverlap=c()
neitherOverlap=c()
for (n in 1:nTests){
genesTest=sample(InputGenes, nGenes)
overlapE=intersect(genesTest, explained$genes)
overlapUN=intersect(genesTest, unexplained$genes)
diffs <- Reduce(setdiff,list(A = genesTest, B = explained$genes,C = unexplained$genes))
explainedOverlap= c(explainedOverlap, length(overlapE))
unexplainedOverlap=c(unexplainedOverlap,length(overlapUN))
neitherOverlap=c(neitherOverlap, length(diffs))
}
DF=as.data.frame(cbind(explainedOverlap,unexplainedOverlap,neitherOverlap))
return(DF)
}
I need to have all of the genes tested for eGenes.
DEtestedgenes=read.table("../data/DiffExpression/DE_Testedgenes.txt", header = F,col.names = c("Gene_stable_ID"),stringsAsFactors = F) %>% inner_join(nameID, by="Gene_stable_ID") %>% dplyr::select(Gene.name)
Perform permutations 1000 times
Expression_1000tests=permuteGenes(DEtestedgenes$Gene.name, nrow(DEgenes),1000 )
EEx=Expression_1000tests %>% filter(explainedOverlap>=nrow(DE_explained)) %>% nrow() / 1000
EUnEx=Expression_1000tests %>% filter(unexplainedOverlap>=nrow(DE_unexplained)) %>% nrow() / 1000
Plot as histograms
Explained
ggplot(Expression_1000tests,aes(x=explainedOverlap)) + geom_histogram(stat="count") + geom_vline(xintercept =nrow(DE_explained), col="red" )+labs(x="Number of Overlaps", title="DE overlap with explained eGenes") + annotate("text", x = 275, y = 30, label = paste("EmpPvalue=", EEx), col="red")
Warning: Ignoring unknown parameters: binwidth, bins, pad
Unexplained
ggplot(Expression_1000tests,aes(x=unexplainedOverlap)) + geom_histogram(stat="count") + geom_vline(xintercept =nrow(DE_unexplained), col="red" ) +labs(x="Number of Overlaps", title="DE overlap with unexplained eGenes")+ annotate("text", x = 200, y = 30, label = paste("EmpPvalue=", EUnEx), col="red")
Warning: Ignoring unknown parameters: binwidth, bins, pad
All eQTLs
allEQTL
DE_all=DEgenes %>% inner_join(allEQTL, by="Gene.name")
permuteGenesAll <- function(InputGenes, nGenes, nTests){
#InputGenes=DEtestedgenes$Gene.name
#nGenes=nrow(DEgenes)
#nTests=10000
qtls=DE_all
qtlOverlap=c()
for (n in 1:nTests){
genesTest=sample(InputGenes, nGenes)
overlapqtl=intersect(genesTest, qtls$Gene.name)
qtlOverlap= c(qtlOverlap, length(overlapqtl))
}
DF=as.data.frame(cbind(qtlOverlap))
return(DF)
}
overlapAll=permuteGenesAll(DEtestedgenes$Gene.name, nrow(DEgenes),10000)
actual=length(intersect(DEgenes$Gene.name,allEQTL$Gene.name ))
empricalpval=overlapAll %>% filter(qtlOverlap >= actual) %>% nrow() / 10000
ggplot(overlapAll,aes(x=qtlOverlap)) + geom_histogram(stat="count") + geom_vline(xintercept =actual, col="red" ) +labs(x="Number of Overlaps", title="eGene with eQTL Genes")+ annotate("text", x = 525, y = 400, label = "Actual Overlap", col="red")
Warning: Ignoring unknown parameters: binwidth, bins, pad
sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)
Matrix products: default
BLAS/LAPACK: /software/openblas-0.2.19-el7-x86_64/lib/libopenblas_haswellp-r0.2.19.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] workflowr_1.5.0 forcats_0.3.0 stringr_1.3.1 dplyr_0.8.0.1
[5] purrr_0.3.2 readr_1.3.1 tidyr_0.8.3 tibble_2.1.1
[9] ggplot2_3.1.1 tidyverse_1.2.1
loaded via a namespace (and not attached):
[1] Rcpp_1.0.2 cellranger_1.1.0 plyr_1.8.4 compiler_3.5.1
[5] pillar_1.3.1 later_0.7.5 git2r_0.26.1 tools_3.5.1
[9] digest_0.6.18 lubridate_1.7.4 jsonlite_1.6 evaluate_0.12
[13] nlme_3.1-137 gtable_0.2.0 lattice_0.20-38 pkgconfig_2.0.2
[17] rlang_0.4.0 cli_1.1.0 rstudioapi_0.10 yaml_2.2.0
[21] haven_1.1.2 withr_2.1.2 xml2_1.2.0 httr_1.3.1
[25] knitr_1.20 hms_0.4.2 generics_0.0.2 fs_1.3.1
[29] rprojroot_1.3-2 grid_3.5.1 tidyselect_0.2.5 glue_1.3.0
[33] R6_2.3.0 readxl_1.1.0 rmarkdown_1.10 modelr_0.1.2
[37] magrittr_1.5 whisker_0.3-2 backports_1.1.2 scales_1.0.0
[41] promises_1.0.1 htmltools_0.3.6 rvest_0.3.2 assertthat_0.2.0
[45] colorspace_1.3-2 httpuv_1.4.5 labeling_0.3 stringi_1.2.4
[49] lazyeval_0.2.1 munsell_0.5.0 broom_0.5.1 crayon_1.3.4