RiboQTL QQplot

Last updated: 2020-03-10

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Knit directory: apaQTL/analysis/

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Unstaged changes:
    Modified:   analysis/NuclearSpecIncludeNotTested.Rmd
    Modified:   analysis/PASdescriptiveplots.Rmd
    Modified:   analysis/Readdistagainstfeatures.Rmd
    Modified:   analysis/TSS.Rmd
    Modified:   analysis/apabyeQTLstatus.Rmd
    Modified:   analysis/decayAndStability.Rmd
    Modified:   analysis/miRNAdisrupt.Rmd
    Modified:   analysis/nascenttranscription.Rmd
    Modified:   analysis/nucSpecinEQTLs.Rmd
    Modified:   analysis/overlapapaqtlsandeqtls.Rmd
    Modified:   analysis/pQTLexampleplot.Rmd
    Modified:   analysis/splicesitestrength.Rmd
    Modified:   analysis/version15bpfilter.Rmd
    Modified:   code/DistPAS2Sig.py
    Modified:   code/Script4NuclearQTLexamples.sh
    Modified:   code/Script4TotalQTLexamples.sh
    Modified:   code/apaQTLsnake.err
    Modified:   code/environment.yaml
    Modified:   code/run_qtlFacetBoxplots.sh
    Deleted:    code/test.txt
    Deleted:    reads_graphs.Rmd

Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.

These are the previous versions of the R Markdown and HTML files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view them.

File	Version	Author	Date	Message
Rmd	6719a59	brimittleman	2020-03-10	add mixed plot
html	71f66d2	brimittleman	2020-02-28	Build site.
Rmd	e5dbb2f	brimittleman	2020-02-28	add all lines in 1
html	f19db64	brimittleman	2020-02-28	Build site.
Rmd	2969449	brimittleman	2020-02-28	add all lines in 1
html	11ea802	brimittleman	2020-02-27	Build site.
Rmd	7449f09	brimittleman	2020-02-27	add figure spec
html	1ca62a2	brimittleman	2020-02-20	Build site.
Rmd	662a604	brimittleman	2020-02-20	add riboqq and PM coloc

In the paper I have qqPlots where I took the apaQTL data and subset it by QTL sets. I never did this for riboQTLs. I will get the riboQTLs from Battle et al and remake the plot including these.

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()

geneNames=read.table("../../genome_anotation_data/ensemble_to_genename.txt", sep="\t", col.names = c('ENSG', 'GeneName', 'source' ),stringsAsFactors = F, header = T)

riboRes=read.table("../data/Battle_pQTL/riboQTLs_battle.txt", header = T,stringsAsFactors = F) %>% inner_join(geneNames,by="ENSG") 

exPe=read.table("../data/Li_eQTLs/explainedEgenes.txt", col.names = "GeneName")
UexPe=read.table("../data/Li_eQTLs/UnexplainedEgenes.txt",col.names = "GeneName")

allE=exPe %>% full_join(UexPe,by="GeneName")

Warning: Column `GeneName` joining factors with different levels, coercing
to character vector

riboRes$bh=p.adjust(riboRes$perm.p.values, method="fdr")

riboRes_sig= riboRes %>% filter(-log10(bh)>=1)

riboGenes=riboRes_sig %>% select(GeneName) %>% anti_join(allE)

Joining, by = "GeneName"

write.table(riboGenes, file="../data/Battle_pQTL/RiboQTLGeneNames.txt", row.names = F, col.names = F, quote = F, sep="\t")

mkdir ../data/ApaByRgene

python subsetpermAPAwithGenelist.py ../data/Battle_pQTL/RiboQTLGeneNames.txt Nuclear ../data/ApaByRgene/NuclearApaRGenes.txt

python subsetpermAPAwithGenelist.py ../data/Battle_pQTL/RiboQTLGeneNames.txt Total ../data/ApaByRgene/TotalApaRGenes.txt

python subsetAPAnotEorR.py Nuclear ../data/ApaByRgene/NotRorE_nuclear.txt
python subsetAPAnotEorR.py Total ../data/ApaByRgene/NotRorE_total.txt

tot.notEorR=read.table("../data/ApaByRgene/NotRorE_total.txt",stringsAsFactors = F,col.names = c("pid", "nvar", "shape1", "shape2", "dummy", "sid", "dist", "npval", "slope", "ppval", "bpval"))
tot.RS=read.table("../data/ApaByRgene/TotalApaRGenes.txt",stringsAsFactors = F,col.names = c("pid", "nvar", "shape1", "shape2", "dummy", "sid", "dist", "npval", "slope", "ppval", "bpval"))
tot.ES=read.table("../data/ApaByPgene/TotalApaESGenes.txt",stringsAsFactors = F, col.names = c("pid", "nvar", "shape1", "shape2", "dummy", "sid", "dist", "npval", "slope", "ppval", "bpval") )
tot.ex=read.table("../data/ApaByEgene/TotalApaexplainedeGenes.txt",stringsAsFactors = F,col.names = c("pid", "nvar", "shape1", "shape2", "dummy", "sid", "dist", "npval", "slope", "ppval", "bpval"))
tot.un=read.table("../data/ApaByEgene/TotalApaUnexplainedeGenes.txt",stringsAsFactors = F, col.names = c("pid", "nvar", "shape1", "shape2", "dummy", "sid", "dist", "npval", "slope", "ppval", "bpval") )

tot_allE=as.data.frame(rbind(tot.ex,tot.un))
tot.RS=na.omit(tot.RS)
tot.notEorR=na.omit(tot.notEorR)
tot.ES=na.omit(tot.ES)
tot.un=na.omit(tot.un)

qqplot(-log10(runif(nrow(tot.notEorR))), -log10(tot.notEorR$bpval), xlab="-log10(Uniform)", ylab="-log10(beta pval)", main="Total Apa")
points(sort(-log10(runif(nrow(tot.RS)))), sort(-log10(tot.RS$bpval)),col= alpha("Red"))
points(sort(-log10(runif(nrow(tot_allE)))), sort(-log10(tot_allE$bpval)),col= alpha("blue"))
abline(0,1)

legend("topleft", legend=c("Neither eGenes nor rGenes", "rGenes", "eGenes"),col=c("black", "red","blue"), pch=16,bty = 'n')

Version	Author	Date
1ca62a2	brimittleman	2020-02-20

wilcox.test(tot.RS$bpval,tot.notEorR$bpval,alternative="less")


    Wilcoxon rank sum test with continuity correction

data:  tot.RS$bpval and tot.notEorR$bpval
W = 9336600, p-value = 0.0001811
alternative hypothesis: true location shift is less than 0

wilcox.test(tot_allE$bpval,tot.notEorR$bpval,alternative="less")


    Wilcoxon rank sum test with continuity correction

data:  tot_allE$bpval and tot.notEorR$bpval
W = 43090000, p-value = 1.878e-11
alternative hypothesis: true location shift is less than 0

wilcox.test(tot.RS$bpval,tot_allE$bpval,alternative="less")


    Wilcoxon rank sum test with continuity correction

data:  tot.RS$bpval and tot_allE$bpval
W = 1554300, p-value = 0.3891
alternative hypothesis: true location shift is less than 0

nuc.notEorR=read.table("../data/ApaByRgene/NotRorE_nuclear.txt",stringsAsFactors = F,col.names = c("pid", "nvar", "shape1", "shape2", "dummy", "sid", "dist", "npval", "slope", "ppval", "bpval"))
nuc.RS=read.table("../data/ApaByRgene/NuclearApaRGenes.txt",stringsAsFactors = F,col.names = c("pid", "nvar", "shape1", "shape2", "dummy", "sid", "dist", "npval", "slope", "ppval", "bpval"))
nuc.P=read.table("../data/ApaByPgene/NuclearApaPSGenes.txt",stringsAsFactors = F,col.names = c("pid", "nvar", "shape1", "shape2", "dummy", "sid", "dist", "npval", "slope", "ppval", "bpval"))
nuc.ES=read.table("../data/ApaByPgene/NuclearApaESGenes.txt",stringsAsFactors = F, col.names = c("pid", "nvar", "shape1", "shape2", "dummy", "sid", "dist", "npval", "slope", "ppval", "bpval") )
nuc.ex=read.table("../data/ApaByEgene/NuclearApaexplainedeGenes.txt",stringsAsFactors = F,col.names = c("pid", "nvar", "shape1", "shape2", "dummy", "sid", "dist", "npval", "slope", "ppval", "bpval"))
nuc.un=read.table("../data/ApaByEgene/NuclearApaUnexplainedeGenes.txt",stringsAsFactors = F, col.names = c("pid", "nvar", "shape1", "shape2", "dummy", "sid", "dist", "npval", "slope", "ppval", "bpval") )

nuc.un=na.omit(nuc.un)
nuc.RS=na.omit(nuc.RS)
#nuc.notERorP=na.omit(nuc.notERorP)
nuc.P=na.omit(nuc.P)
nuc.notEorR=na.omit(nuc.notEorR)
nuc.ES=na.omit(nuc.ES)
nuc_allE=as.data.frame(rbind(nuc.ex,nuc.un))

qqplot(-log10(runif(nrow(nuc.notEorR))), -log10(nuc.notEorR$bpval), xlab="-log10(Uniform)", ylab="-log10(beta pval)", main="Nuclear Apa")
points(sort(-log10(runif(nrow(nuc.RS)))), sort(-log10(nuc.RS$bpval)),col= alpha("Red"))
points(sort(-log10(runif(nrow(nuc_allE)))), sort(-log10(nuc_allE$bpval)),col= alpha("blue"))
abline(0,1)

legend("topleft", legend=c("Neither eGenes nor rGenes", "rGenes", "eGenes"),col=c("black", "red","blue","green"), pch=16,bty = 'n')

Version	Author	Date
1ca62a2	brimittleman	2020-02-20

wilcox.test(nuc.RS$bpval,nuc.notEorR$bpval,alternative="less")


    Wilcoxon rank sum test with continuity correction

data:  nuc.RS$bpval and nuc.notEorR$bpval
W = 13007000, p-value = 0.01029
alternative hypothesis: true location shift is less than 0

wilcox.test(nuc_allE$bpval,nuc.notEorR$bpval,alternative="less")


    Wilcoxon rank sum test with continuity correction

data:  nuc_allE$bpval and nuc.notEorR$bpval
W = 57056000, p-value = 6.194e-13
alternative hypothesis: true location shift is less than 0

wilcox.test(nuc.RS$bpval,nuc_allE$bpval,alternative="less")


    Wilcoxon rank sum test with continuity correction

data:  nuc.RS$bpval and nuc_allE$bpval
W = 2189300, p-value = 0.8658
alternative hypothesis: true location shift is less than 0

No QTL at all.

python subsetNootherQTL.py Nuclear ../data/ApaByRgene/NotANY_nuclear.txt

notany_nuc=read.table("../data/ApaByRgene/NotANY_nuclear.txt",stringsAsFactors = F, col.names = c("pid", "nvar", "shape1", "shape2", "dummy", "sid", "dist", "npval", "slope", "ppval", "bpval") )
notany_nuc=na.omit(notany_nuc)

qqplot(-log10(runif(nrow(notany_nuc))), -log10(notany_nuc$bpval), xlab="-log10(Uniform)", ylab="-log10(beta pval)", main="Nuclear Apa")
points(sort(-log10(runif(nrow(nuc.RS)))), sort(-log10(nuc.RS$bpval)),col= alpha("Red"))
points(sort(-log10(runif(nrow(nuc.P)))), sort(-log10(nuc.P$bpval)),col= alpha("Blue"))
abline(0,1)

legend("topleft", legend=c("No Molecular QTL","rGenes", "pGenes"),col=c("black", "red","Blue"), pch=16,bty = 'n')

Version	Author	Date
71f66d2	brimittleman	2020-02-28
f19db64	brimittleman	2020-02-28

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] forcats_0.3.0   stringr_1.3.1   dplyr_0.8.0.1   purrr_0.3.2    
[5] readr_1.3.1     tidyr_0.8.3     tibble_2.1.1    ggplot2_3.1.1  
[9] 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     workflowr_1.6.0 
 [9] tools_3.5.1      digest_0.6.18    lubridate_1.7.4  jsonlite_1.6    
[13] evaluate_0.12    nlme_3.1-137     gtable_0.2.0     lattice_0.20-38 
[17] pkgconfig_2.0.2  rlang_0.4.0      cli_1.1.0        rstudioapi_0.10 
[21] yaml_2.2.0       haven_1.1.2      withr_2.1.2      xml2_1.2.0      
[25] httr_1.3.1       knitr_1.20       hms_0.4.2        generics_0.0.2  
[29] fs_1.3.1         rprojroot_1.3-2  grid_3.5.1       tidyselect_0.2.5
[33] glue_1.3.0       R6_2.3.0         readxl_1.1.0     rmarkdown_1.10  
[37] modelr_0.1.2     magrittr_1.5     whisker_0.3-2    backports_1.1.2 
[41] scales_1.0.0     promises_1.0.1   htmltools_0.3.6  rvest_0.3.2     
[45] assertthat_0.2.0 colorspace_1.3-2 httpuv_1.4.5     stringi_1.2.4   
[49] lazyeval_0.2.1   munsell_0.5.0    broom_0.5.1      crayon_1.3.4

RiboQTL QQplot

Briana Mittleman

2/20/2020