Protein and Expression specific QTL overlaps

Last updated: 2019-06-14

Checks: 6 0

Knit directory: apaQTL/analysis/

This reproducible R Markdown analysis was created with workflowr (version 1.3.0). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.

R Markdown file: up-to-date

Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.

Environment: empty

Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.

Seed: set.seed(20190411)

The command set.seed(20190411) was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.

Session information: recorded

Great job! Recording the operating system, R version, and package versions is critical for reproducibility.

Cache: none

Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.

Repository version: 5010185

Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility. The version displayed above was the version of the Git repository at the time these results were generated.

Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:


Ignored files:
    Ignored:    .DS_Store
    Ignored:    .Rhistory
    Ignored:    .Rproj.user/
    Ignored:    data/.DS_Store
    Ignored:    output/.DS_Store

Untracked files:
    Untracked:  .Rprofile
    Untracked:  ._.DS_Store
    Untracked:  .gitignore
    Untracked:  _workflowr.yml
    Untracked:  analysis/._PASdescriptiveplots.Rmd
    Untracked:  analysis/._cuttoffPercUsage.Rmd
    Untracked:  analysis/QTLexampleplots.Rmd
    Untracked:  analysis/cuttoffPercUsage.Rmd
    Untracked:  analysis/eQTLoverlap.Rmd
    Untracked:  analysis/oldstuffNotNeeded.Rmd
    Untracked:  apaQTL.Rproj
    Untracked:  code/.NascentRNAdtPlotFirstintronicPAS.sh.swp
    Untracked:  code/._ApaQTL_nominalNonnorm.sh
    Untracked:  code/._BothFracDTPlotGeneRegions_normalized.sh
    Untracked:  code/._FC_NucintornUpandDown.sh
    Untracked:  code/._FC_UTR.sh
    Untracked:  code/._FC_intornUpandDownsteamPAS.sh
    Untracked:  code/._FC_newPeaks_olddata.sh
    Untracked:  code/._HMMpermuteTotal.py
    Untracked:  code/._HmmPermute.py
    Untracked:  code/._LC_samplegroups.py
    Untracked:  code/._NascentRNAdtPlot.sh
    Untracked:  code/._NascentRNAdtPlot3UTRPAS.sh
    Untracked:  code/._NascentRNAdtPlotExcludeFirstintronicPAS.sh
    Untracked:  code/._NascentRNAdtPlotNucPAS.sh
    Untracked:  code/._NascentRNAdtPlotTotPAS.sh
    Untracked:  code/._NascentRNAdtPlotintronicPAS.sh
    Untracked:  code/._NascnetRNAdtPlotPAS.sh
    Untracked:  code/._NetSeq_fourthintronDT.sh
    Untracked:  code/._QTL2bed.py
    Untracked:  code/._QTL2bed_withstrand.py
    Untracked:  code/._SnakefilePAS
    Untracked:  code/._SnakefilefiltPAS
    Untracked:  code/._TESplots100bp.sh
    Untracked:  code/._TESplots150bp.sh
    Untracked:  code/._TESplots200bp.sh
    Untracked:  code/._Untitled
    Untracked:  code/._ZipandTabPheno.sh
    Untracked:  code/._aAPAqtl_nominal39ind.sh
    Untracked:  code/._apaQTLCorrectPvalMakeQQ.R
    Untracked:  code/._apaQTL_Nominal.sh
    Untracked:  code/._apaQTL_permuted.sh
    Untracked:  code/._assignNucIntonpeak2intronlocs.sh
    Untracked:  code/._assignTotIntronpeak2intronlocs.sh
    Untracked:  code/._bam2BW_5primemost.sh
    Untracked:  code/._bed2saf.py
    Untracked:  code/._bothFracDTplot1stintron.sh
    Untracked:  code/._bothFracDTplot4thintron.sh
    Untracked:  code/._bothFrac_FC.sh
    Untracked:  code/._callPeaksYL.py
    Untracked:  code/._chooseAnno2SAF.py
    Untracked:  code/._chooseSignalSite
    Untracked:  code/._chooseSignalSite.py
    Untracked:  code/._cluster.json
    Untracked:  code/._clusterPAS.json
    Untracked:  code/._clusterfiltPAS.json
    Untracked:  code/._codingdms2bed.py
    Untracked:  code/._config.yaml
    Untracked:  code/._config2.yaml
    Untracked:  code/._configOLD.yaml
    Untracked:  code/._convertNominal2SNPLOC.py
    Untracked:  code/._convertNumeric.py
    Untracked:  code/._correctNomeqtl.R
    Untracked:  code/._dag.pdf
    Untracked:  code/._eQTLgenestestedapa.py
    Untracked:  code/._encodeRNADTplots.sh
    Untracked:  code/._extractGenotypes.py
    Untracked:  code/._extractseqfromqtlfastq.py
    Untracked:  code/._fc2leafphen.py
    Untracked:  code/._filter5perc.R
    Untracked:  code/._filter5percPheno.py
    Untracked:  code/._filterpeaks.py
    Untracked:  code/._finalPASbed2SAF.py
    Untracked:  code/._fix4su304corr.py
    Untracked:  code/._fix4su604corr.py
    Untracked:  code/._fix4sukalisto.py
    Untracked:  code/._fixExandUnexeQTL
    Untracked:  code/._fixExandUnexeQTL.py
    Untracked:  code/._fixFChead.py
    Untracked:  code/._fixFChead_bothfrac.py
    Untracked:  code/._fixH3k12ac.py
    Untracked:  code/._fixRNAhead4corr.py
    Untracked:  code/._fixRNAkalisto.py
    Untracked:  code/._fixgroupedtranscript.py
    Untracked:  code/._fixhead_netseqfc.py
    Untracked:  code/._getAPAfromanyeQTL.py
    Untracked:  code/._getApapval4eqtl.py
    Untracked:  code/._getApapval4eqtl_unexp.py
    Untracked:  code/._getDownstreamIntronNuclear.py
    Untracked:  code/._getIntronDownstreamPAS.py
    Untracked:  code/._getIntronUpstreamPAS.py
    Untracked:  code/._getQTLalleles.py
    Untracked:  code/._getQTLfastq.sh
    Untracked:  code/._getUpstreamIntronNuclear.py
    Untracked:  code/._grouptranscripts.py
    Untracked:  code/._keep5perMAF.py
    Untracked:  code/._keepSNP_vcf.sh
    Untracked:  code/._make5percPeakbed.py
    Untracked:  code/._makeFileID.py
    Untracked:  code/._makePheno.py
    Untracked:  code/._makeSAFbothfrac5perc.py
    Untracked:  code/._makeSNP2rsidfile.py
    Untracked:  code/._makeeQTLempirical_unexp.py
    Untracked:  code/._makeeQTLempiricaldist.py
    Untracked:  code/._makegencondeTSSfile.py
    Untracked:  code/._mergeAllBam.sh
    Untracked:  code/._mergeBW_norm.sh
    Untracked:  code/._mergeBamNascent.sh
    Untracked:  code/._mergeByFracBam.sh
    Untracked:  code/._mergePeaks.sh
    Untracked:  code/._mnase1stintron.sh
    Untracked:  code/._mnaseDT_fourthintron.sh
    Untracked:  code/._namePeaks.py
    Untracked:  code/._netseqDTplot1stIntron.sh
    Untracked:  code/._netseqFC.sh
    Untracked:  code/._peak2PAS.py
    Untracked:  code/._peakFC.sh
    Untracked:  code/._pheno2countonly.R
    Untracked:  code/._processYRIgen.py
    Untracked:  code/._qtlRegionseq.sh
    Untracked:  code/._qtlsPvalOppFrac.py
    Untracked:  code/._quantassign2parsedpeak.py
    Untracked:  code/._removeXfromHmm.py
    Untracked:  code/._removeloc_pheno.py
    Untracked:  code/._runCorrectNomEqtl.sh
    Untracked:  code/._runHMMpermuteAPAqtls.sh
    Untracked:  code/._runHMMpermuteeQTLS.sh
    Untracked:  code/._runMakeEmpiricaleQTL_unexp.sh
    Untracked:  code/._runMakeeQTLempirical.sh
    Untracked:  code/._run_getApaPval4eqtl.sh
    Untracked:  code/._run_getapafromeQTL.py
    Untracked:  code/._run_getapafromeQTL.sh
    Untracked:  code/._run_getapapval4eqtl_unexp.sh
    Untracked:  code/._run_leafcutterDiffIso.sh
    Untracked:  code/._run_sepUsagephen.sh
    Untracked:  code/._run_sepgenobychrom.sh
    Untracked:  code/._selectNominalPvalues.py
    Untracked:  code/._sepUsagePhen.py
    Untracked:  code/._sepgenobychrom.py
    Untracked:  code/._snakemakePAS.batch
    Untracked:  code/._snakemakefiltPAS.batch
    Untracked:  code/._submit-snakemakePAS.sh
    Untracked:  code/._submit-snakemakefiltPAS.sh
    Untracked:  code/._subsetAPAnotEorPgene.py
    Untracked:  code/._subsetApanoteGene.py
    Untracked:  code/._subsetUnexplainedeQTLs.py
    Untracked:  code/._subset_diffisopheno.py
    Untracked:  code/._subsetpermAPAwithGenelist.py
    Untracked:  code/._subtrachfiveprimeUTR.sh
    Untracked:  code/._subtractExons.sh
    Untracked:  code/._subtractfiveprimeUTR.sh
    Untracked:  code/._tabixSNPS.sh
    Untracked:  code/._utrdms2saf.py
    Untracked:  code/.snakemake/
    Untracked:  code/APAqtl_nominal.err
    Untracked:  code/APAqtl_nominal.out
    Untracked:  code/APAqtl_nominal_39.err
    Untracked:  code/APAqtl_nominal_39.out
    Untracked:  code/APAqtl_nominal_nonNorm.err
    Untracked:  code/APAqtl_nominal_nonNorm.out
    Untracked:  code/APAqtl_permuted.err
    Untracked:  code/APAqtl_permuted.out
    Untracked:  code/ApaQTL_nominalNonnorm.sh
    Untracked:  code/BothFracDTPlot1stintron.err
    Untracked:  code/BothFracDTPlot1stintron.out
    Untracked:  code/BothFracDTPlot4stintron.err
    Untracked:  code/BothFracDTPlot4stintron.out
    Untracked:  code/BothFracDTPlotGeneRegions.err
    Untracked:  code/BothFracDTPlotGeneRegions.out
    Untracked:  code/BothFracDTPlotGeneRegions_norm.err
    Untracked:  code/BothFracDTPlotGeneRegions_norm.out
    Untracked:  code/BothFracDTPlotGeneRegions_normalized.sh
    Untracked:  code/DistPAS2Sig.py
    Untracked:  code/EncodeRNADTPlotGeneRegions.err
    Untracked:  code/EncodeRNADTPlotGeneRegions.out
    Untracked:  code/FC_NucintornUpandDown.sh
    Untracked:  code/FC_NucintronPASupandDown.err
    Untracked:  code/FC_NucintronPASupandDown.out
    Untracked:  code/FC_UTR.err
    Untracked:  code/FC_UTR.out
    Untracked:  code/FC_UTR.sh
    Untracked:  code/FC_intornUpandDownsteamPAS.sh
    Untracked:  code/FC_intronPASupandDown.err
    Untracked:  code/FC_intronPASupandDown.out
    Untracked:  code/FC_newPAS_olddata.err
    Untracked:  code/FC_newPAS_olddata.out
    Untracked:  code/FC_newPeaks_olddata.sh
    Untracked:  code/HMMpermuteTotal.py
    Untracked:  code/HmmPermute.p
    Untracked:  code/HmmPermute.py
    Untracked:  code/LC_samplegroups.py
    Untracked:  code/NascentDTPlotGeneRegions.err
    Untracked:  code/NascentDTPlotGeneRegions.out
    Untracked:  code/NascentDTPlotPAS.err
    Untracked:  code/NascentDTPlotPAS.out
    Untracked:  code/NascentDTPlotPAS_3utr.err
    Untracked:  code/NascentDTPlotPAS_3utr.out
    Untracked:  code/NascentDTPlotPAS_firstintron.err
    Untracked:  code/NascentDTPlotPAS_firstintron.out
    Untracked:  code/NascentDTPlotPAS_intron.err
    Untracked:  code/NascentDTPlotPAS_intron.out
    Untracked:  code/NascentDTPlotPAS_nuc.err
    Untracked:  code/NascentDTPlotPAS_nuc.out
    Untracked:  code/NascentDTPlotPAS_tot.err
    Untracked:  code/NascentDTPlotPAS_tot.out
    Untracked:  code/NascentRNAdtPlot.sh
    Untracked:  code/NascentRNAdtPlot3UTRPAS.sh
    Untracked:  code/NascentRNAdtPlotExcludeFirstintronicPAS.sh
    Untracked:  code/NascentRNAdtPlotFirstintronicPAS.sh
    Untracked:  code/NascentRNAdtPlotNucPAS.sh
    Untracked:  code/NascentRNAdtPlotTotPAS.sh
    Untracked:  code/NascentRNAdtPlotintronicPAS.sh
    Untracked:  code/NascnetRNAdtPlotPAS.sh
    Untracked:  code/NetSeq_fourthintronDT.sh
    Untracked:  code/QTL2bed.py
    Untracked:  code/QTL2bed_withstrand.py
    Untracked:  code/README.md
    Untracked:  code/Rplots.pdf
    Untracked:  code/TESplots100bp.err
    Untracked:  code/TESplots100bp.out
    Untracked:  code/TESplots100bp.sh
    Untracked:  code/TESplots150bp.err
    Untracked:  code/TESplots150bp.out
    Untracked:  code/TESplots150bp.sh
    Untracked:  code/TESplots200bp.err
    Untracked:  code/TESplots200bp.out
    Untracked:  code/TESplots200bp.sh
    Untracked:  code/Untitled
    Untracked:  code/Upstream100Bases_general.py
    Untracked:  code/ZipandTabPheno.sh
    Untracked:  code/aAPAqtl_nominal39ind.sh
    Untracked:  code/apaQTLCorrectPvalMakeQQ_4pc.R
    Untracked:  code/apaQTL_Nominal_4pc.sh
    Untracked:  code/apaQTL_permuted.4pc.sh
    Untracked:  code/apafacetboxplots.R
    Untracked:  code/apaqtlfacetboxplots.R
    Untracked:  code/assignNucIntonpeak2intronlocs.sh
    Untracked:  code/assignPeak2Intronicregion.err
    Untracked:  code/assignPeak2Intronicregion.out
    Untracked:  code/assignTotIntronpeak2intronlocs.sh
    Untracked:  code/assigntotPeak2Intronicregion.err
    Untracked:  code/assigntotPeak2Intronicregion.out
    Untracked:  code/bam2BW_5primemost.sh
    Untracked:  code/bam2bw.err
    Untracked:  code/bam2bw.out
    Untracked:  code/bam2bw_5primemost.err
    Untracked:  code/bam2bw_5primemost.out
    Untracked:  code/bothFracDTplot1stintron.sh
    Untracked:  code/bothFracDTplot4thintron.sh
    Untracked:  code/bothFrac_FC.err
    Untracked:  code/bothFrac_FC.out
    Untracked:  code/bothFrac_FC.sh
    Untracked:  code/codingdms2bed.py
    Untracked:  code/convertNominal2SNPLOC.py
    Untracked:  code/correctNomeqtl.R
    Untracked:  code/dag.pdf
    Untracked:  code/dagPAS.pdf
    Untracked:  code/dagfiltPAS.pdf
    Untracked:  code/eQTLgenestestedapa.py
    Untracked:  code/encodeRNADTplots.sh
    Untracked:  code/extractGenotypes.py
    Untracked:  code/extractseqfromqtlfastq.py
    Untracked:  code/fc2leafphen.py
    Untracked:  code/finalPASbed2SAF.py
    Untracked:  code/findbuginpeaks.R
    Untracked:  code/fix4su304corr.py
    Untracked:  code/fix4su604corr.py
    Untracked:  code/fix4sukalisto.py
    Untracked:  code/fixExandUnexeQTL
    Untracked:  code/fixExandUnexeQTL.py
    Untracked:  code/fixFChead_bothfrac.py
    Untracked:  code/fixFChead_summary.py
    Untracked:  code/fixH3k12ac.py
    Untracked:  code/fixRNAhead4corr.py
    Untracked:  code/fixRNAkalisto.py
    Untracked:  code/fixgroupedtranscript.py
    Untracked:  code/fixhead_netseqfc.py
    Untracked:  code/genotypesYRI.gen.proc.keep.vcf.log
    Untracked:  code/genotypesYRI.gen.proc.keep.vcf.recode.vcf
    Untracked:  code/get100upPAS.py
    Untracked:  code/getAPAfromanyeQTL.py
    Untracked:  code/getApapval4eqtl.py
    Untracked:  code/getApapval4eqtl_unexp.py
    Untracked:  code/getDownstreamIntronNuclear.py
    Untracked:  code/getIntronDownstreamPAS.py
    Untracked:  code/getIntronUpstreamPAS.py
    Untracked:  code/getQTLalleles.py
    Untracked:  code/getQTLfastq.sh
    Untracked:  code/getSeq100up.sh
    Untracked:  code/getUpstreamIntronNuclear.py
    Untracked:  code/getseq100up.err
    Untracked:  code/getseq100up.out
    Untracked:  code/grouptranscripts.err
    Untracked:  code/grouptranscripts.out
    Untracked:  code/grouptranscripts.py
    Untracked:  code/keep5perMAF.py
    Untracked:  code/keepSNP_vcf.sh
    Untracked:  code/log/
    Untracked:  code/makeSAFbothfrac5perc.py
    Untracked:  code/makeSNP2rsidfile.py
    Untracked:  code/makeeQTLempirical_unexp.py
    Untracked:  code/makeeQTLempiricaldist.py
    Untracked:  code/makegencondeTSSfile.py
    Untracked:  code/mergeBW_norm.sh
    Untracked:  code/mergeBWnorm.err
    Untracked:  code/mergeBWnorm.out
    Untracked:  code/mergeBamNacent.err
    Untracked:  code/mergeBamNacent.out
    Untracked:  code/mergeBamNascent.sh
    Untracked:  code/mnase1stintron.sh
    Untracked:  code/mnaseDTPlot1stintron.err
    Untracked:  code/mnaseDTPlot1stintron.out
    Untracked:  code/mnaseDTPlot4thintron.err
    Untracked:  code/mnaseDTPlot4thintron.out
    Untracked:  code/mnaseDT_fourthintron.sh
    Untracked:  code/netDTPlot4thintron.out
    Untracked:  code/netseqDTplot1stIntron.sh
    Untracked:  code/netseqFC.err
    Untracked:  code/netseqFC.out
    Untracked:  code/netseqFC.sh
    Untracked:  code/neyDTPlot4thintron.err
    Untracked:  code/processYRIgen.py
    Untracked:  code/qtlFacetBoxplots.err
    Untracked:  code/qtlFacetBoxplots.out
    Untracked:  code/qtlRegionseq.sh
    Untracked:  code/qtlsPvalOppFrac.py
    Untracked:  code/removeXfromHmm.py
    Untracked:  code/removeloc_pheno.py
    Untracked:  code/runCorrectNomEqtl.sh
    Untracked:  code/runCorrectNomeqtl.err
    Untracked:  code/runCorrectNomeqtl.out
    Untracked:  code/runHMMpermute.err
    Untracked:  code/runHMMpermute.out
    Untracked:  code/runHMMpermuteAPAqtls.sh
    Untracked:  code/runHMMpermuteeQTLS.sh
    Untracked:  code/runHMMpermuteeQTLs.err
    Untracked:  code/runHMMpermuteeQTLs.out
    Untracked:  code/runMakeEmpiricaleQTL_unexp.sh
    Untracked:  code/runMakeEmpiricaleQTLs.err
    Untracked:  code/runMakeEmpiricaleQTLs.out
    Untracked:  code/runMakeEmpiricaleQTLsunex.err
    Untracked:  code/runMakeEmpiricaleQTLsunex.out
    Untracked:  code/runMakeeQTLempirical.sh
    Untracked:  code/run_DistPAS2Sig.err
    Untracked:  code/run_DistPAS2Sig.out
    Untracked:  code/run_distPAS2Sig.sh
    Untracked:  code/run_getAPAfromanyeQTL.err
    Untracked:  code/run_getAPAfromanyeQTL.out
    Untracked:  code/run_getApaPval4eQTLs.err
    Untracked:  code/run_getApaPval4eQTLs.out
    Untracked:  code/run_getApaPval4eQTLsunexplained.err
    Untracked:  code/run_getApaPval4eQTLsunexplained.out
    Untracked:  code/run_getApaPval4eqtl.sh
    Untracked:  code/run_getapafromeQTL.sh
    Untracked:  code/run_getapapval4eqtl_unexp.sh
    Untracked:  code/run_leafcutterDiffIso.sh
    Untracked:  code/run_leafcutter_ds.err
    Untracked:  code/run_leafcutter_ds.out
    Untracked:  code/run_qtlFacetBoxplots.sh
    Untracked:  code/run_sepUsagephen.sh
    Untracked:  code/run_sepgenobychrom.err
    Untracked:  code/run_sepgenobychrom.out
    Untracked:  code/run_sepgenobychrom.sh
    Untracked:  code/run_sepusage.err
    Untracked:  code/run_sepusage.out
    Untracked:  code/selectNominalPvalues.py
    Untracked:  code/sepUsagePhen.py
    Untracked:  code/sepgenobychrom.py
    Untracked:  code/seqQTLfastq.err
    Untracked:  code/seqQTLfastq.out
    Untracked:  code/seqQTLregion.err
    Untracked:  code/seqQTLregion.out
    Untracked:  code/snakePASlog.out
    Untracked:  code/snakefiltPASlog.out
    Untracked:  code/subsetAPAnotEorPgene.py
    Untracked:  code/subsetApanoteGene.py
    Untracked:  code/subsetUnexplainedeQTLs.py
    Untracked:  code/subset_diffisopheno.py
    Untracked:  code/subsetpermAPAwithGenelist.py
    Untracked:  code/subtract5UTR.err
    Untracked:  code/subtract5UTR.out
    Untracked:  code/subtractExons.err
    Untracked:  code/subtractExons.out
    Untracked:  code/subtractExons.sh
    Untracked:  code/subtractfiveprimeUTR.sh
    Untracked:  code/tabixSNPS.sh
    Untracked:  code/tabixSNPs.err
    Untracked:  code/tabixSNPs.out
    Untracked:  code/transcriptdm2bed.py
    Untracked:  code/utrdms2saf.py
    Untracked:  code/vcf_keepsnps.err
    Untracked:  code/vcf_keepsnps.out
    Untracked:  code/zipandtabPhen.err
    Untracked:  code/zipandtabPhen.out
    Untracked:  data/._.DS_Store
    Untracked:  data/ApaByEgene/
    Untracked:  data/ApaByPgene/
    Untracked:  data/Battle_pQTL/
    Untracked:  data/CompareOldandNew/
    Untracked:  data/DTmatrix/
    Untracked:  data/DiffIso/
    Untracked:  data/EncodeRNA/
    Untracked:  data/ExampleQTLPlots/
    Untracked:  data/GeuvadisRNA/
    Untracked:  data/HMMqtls/
    Untracked:  data/Li_eQTLs/
    Untracked:  data/NascentRNA/
    Untracked:  data/PAS/
    Untracked:  data/QTLGenotypes/
    Untracked:  data/QTLoverlap/
    Untracked:  data/QTLoverlap_nonNorm/
    Untracked:  data/README.md
    Untracked:  data/RNAseq/
    Untracked:  data/Reads2UTR/
    Untracked:  data/SignalSiteFiles/
    Untracked:  data/ThirtyNineIndQtl_nominal/
    Untracked:  data/apaQTLNominal/
    Untracked:  data/apaQTLNominal_4pc/
    Untracked:  data/apaQTLPermuted/
    Untracked:  data/apaQTLPermuted_4pc/
    Untracked:  data/apaQTLs/
    Untracked:  data/assignedPeaks/
    Untracked:  data/bam/
    Untracked:  data/bam_clean/
    Untracked:  data/bam_waspfilt/
    Untracked:  data/bed_10up/
    Untracked:  data/bed_clean/
    Untracked:  data/bed_clean_sort/
    Untracked:  data/bed_waspfilter/
    Untracked:  data/bedsort_waspfilter/
    Untracked:  data/bothFrac_FC/
    Untracked:  data/bw_norm/
    Untracked:  data/eQTLs/
    Untracked:  data/exampleQTLs/
    Untracked:  data/fastq/
    Untracked:  data/filterPeaks/
    Untracked:  data/fourSU/
    Untracked:  data/h3k27ac/
    Untracked:  data/highdiffsiggenes.txt
    Untracked:  data/inclusivePeaks/
    Untracked:  data/inclusivePeaks_FC/
    Untracked:  data/intronRNAratio/
    Untracked:  data/intron_analysis/
    Untracked:  data/mergedBG/
    Untracked:  data/mergedBW_byfrac/
    Untracked:  data/mergedBW_norm/
    Untracked:  data/mergedBam/
    Untracked:  data/mergedbyFracBam/
    Untracked:  data/motifdistrupt/
    Untracked:  data/netseq/
    Untracked:  data/nonNorm_pheno/
    Untracked:  data/nuc_10up/
    Untracked:  data/nuc_10upclean/
    Untracked:  data/overlapeQTL_try2/
    Untracked:  data/overlapeQTLs/
    Untracked:  data/peakCoverage/
    Untracked:  data/peaks_5perc/
    Untracked:  data/phenotype/
    Untracked:  data/phenotype_5perc/
    Untracked:  data/sigDiffGenes.txt
    Untracked:  data/sort/
    Untracked:  data/sort_clean/
    Untracked:  data/sort_waspfilter/
    Untracked:  nohup.out
    Untracked:  output/._.DS_Store
    Untracked:  output/._meanCorrelationPhenotypes.svg
    Untracked:  output/dtPlots/
    Untracked:  output/fastqc/
    Untracked:  output/meanCorrelationPhenotypes.svg

Unstaged changes:
    Modified:   analysis/Readdistagainstfeatures.Rmd
    Modified:   analysis/intonRNAratio.Rmd
    Modified:   analysis/nascentRNA.Rmd
    Modified:   analysis/overlapapaqtlsandeqtls.Rmd
    Modified:   code/BothFracDTPlotGeneRegions.sh
    Modified:   code/Snakefile
    Deleted:    code/Upstream10Bases_general.py
    Modified:   code/apaQTLCorrectPvalMakeQQ.R
    Modified:   code/apaQTL_Nominal.sh
    Modified:   code/apaQTL_permuted.sh
    Modified:   code/apaQTLsnake.err
    Modified:   code/bam2bw.sh
    Modified:   code/bed2saf.py
    Modified:   code/cluster.json
    Modified:   code/clusterfiltPAS.json
    Modified:   code/config.yaml
    Modified:   code/environment.yaml
    Modified:   code/makePheno.py
    Deleted:    code/test.txt

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	5010185	brimittleman	2019-06-14	wflow_publish(c(“analysis/index.Rmd”, “analysis/pQTLandeQTLoverlap.Rmd”))
html	15962c8	brimittleman	2019-06-14	Build site.
Rmd	b38964e	brimittleman	2019-06-14	add pqtl overlap

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 1.3.0
Run ?workflowr for help getting started

This analysis will be similar to the explained and unexplained eQTL analysis available here. I downloaded the protein and expression specific QTLs from Battle et al. 2015. This information is in supplimentary table s2.

First I need to convert the ENSG ids.

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

psQTL=read.table("../data/Battle_pQTL/psQTLGenes.txt", header = T, stringsAsFactors = F, col.names="gene_id") %>% inner_join(geneNames, by="gene_id") %>% select(GeneName)

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

esQTL=read.table("../data/Battle_pQTL/esQTLGenes.txt", header = T, stringsAsFactors = F, col.names="gene_id") %>% inner_join(geneNames, by="gene_id") %>% select(GeneName)
write.table(esQTL, file="../data/Battle_pQTL/esQTLGeneNames.txt", row.names = F, col.names = F, quote = F, sep="\t")

Now I cat use the subsetpermAPAwithGenelist.py code to subset my results:

mkdir ../data/ApaByPgene
python subsetpermAPAwithGenelist.py ../data/Battle_pQTL/psQTLGeneNames.txt Total ../data/ApaByPgene/TotalApaPSGenes.txt

python subsetpermAPAwithGenelist.py ../data/Battle_pQTL/esQTLGenes.txt Total ../data/ApaByPgene/TotalApaESGenes.txt

python subsetpermAPAwithGenelist.py ../data/Battle_pQTL/psQTLGeneNames.txt Nuclear ../data/ApaByPgene/NuclearApaPSGenes.txt

python subsetpermAPAwithGenelist.py ../data/Battle_pQTL/esQTLGenes.txt Nuclear ../data/ApaByPgene/NuclearApaESGenes.txt

I also need those not in eQTL or pQTL:

python subsetAPAnotEorPgene.py Total ../data/ApaByPgene/TotalApaNOTPorEGenes.txt
python subsetAPAnotEorPgene.py Nuclear ../data/ApaByPgene/NuclearApaNOTPorEGenes.txt

Total:

tot.notEorP=read.table("../data/ApaByPgene/TotalApaNOTPorEGenes.txt",stringsAsFactors = F,col.names = c("pid", "nvar", "shape1", "shape2", "dummy", "sid", "dist", "npval", "slope", "ppval", "bpval"))
tot.PS=read.table("../data/ApaByPgene/TotalApaPSGenes.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.PS=na.omit(tot.PS)
tot.notEorP=na.omit(tot.notEorP)
tot.ES=na.omit(tot.ES)
tot.un=na.omit(tot.un)

qqplot(-log10(runif(nrow(tot.notEorP))), -log10(tot.notEorP$bpval), xlab="-log10(Uniform)", ylab="-log10(beta pval)", main="Total Apa")
points(sort(-log10(runif(nrow(tot.PS)))), sort(-log10(tot.PS$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("either eGenes or pGenes", "pGenes", "eGenes"),col=c("black", "red","blue"), pch=16,bty = 'n')

Version	Author	Date
15962c8	brimittleman	2019-06-14

Nuclear:

nuc.notEorP=read.table("../data/ApaByPgene/NuclearApaNOTPorEGenes.txt",stringsAsFactors = F,col.names = c("pid", "nvar", "shape1", "shape2", "dummy", "sid", "dist", "npval", "slope", "ppval", "bpval"))
nuc.PS=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.PS=na.omit(nuc.PS)
nuc.notEorP=na.omit(nuc.notEorP)
nuc.ES=na.omit(nuc.ES)

nuc_allE=as.data.frame(rbind(nuc.ex,nuc.un))

qqplot(-log10(runif(nrow(nuc.notEorP))), -log10(nuc.notEorP$bpval), xlab="-log10(Uniform)", ylab="-log10(beta pval)", main="Nuclear Apa")
points(sort(-log10(runif(nrow(nuc.PS)))), sort(-log10(nuc.PS$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("either eGenes or pGenes", "pGenes", "eGenes"),col=c("black", "red","blue","green"), pch=16,bty = 'n')

Version	Author	Date
15962c8	brimittleman	2019-06-14

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_1.3.0 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_1.0.0       cellranger_1.1.0 pillar_1.3.1     compiler_3.5.1  
 [5] git2r_0.25.2     plyr_1.8.4       tools_3.5.1      digest_0.6.18   
 [9] lubridate_1.7.4  jsonlite_1.6     evaluate_0.12    nlme_3.1-137    
[13] gtable_0.2.0     lattice_0.20-38  pkgconfig_2.0.2  rlang_0.3.1     
[17] cli_1.0.1        rstudioapi_0.10  yaml_2.2.0       haven_1.1.2     
[21] withr_2.1.2      xml2_1.2.0       httr_1.3.1       knitr_1.20      
[25] hms_0.4.2        generics_0.0.2   fs_1.2.6         rprojroot_1.3-2 
[29] grid_3.5.1       tidyselect_0.2.5 glue_1.3.0       R6_2.3.0        
[33] readxl_1.1.0     rmarkdown_1.10   modelr_0.1.2     magrittr_1.5    
[37] whisker_0.3-2    backports_1.1.2  scales_1.0.0     htmltools_0.3.6 
[41] rvest_0.3.2      assertthat_0.2.0 colorspace_1.3-2 stringi_1.2.4   
[45] lazyeval_0.2.1   munsell_0.5.0    broom_0.5.1      crayon_1.3.4

Protein and Expression specific QTL overlaps

Briana Mittleman

6/14/2019