apaQTL and PTTqtls

Last updated: 2019-09-06

Checks: 6 1

Knit directory: apaQTL/analysis/

This reproducible R Markdown analysis was created with workflowr (version 1.4.0). 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: objects present

The global environment had objects present when the code in the R Markdown file was run. These objects 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. Use wflow_publish or wflow_build to ensure that the code is always run in an empty environment.

The following objects were defined in the global environment when these results were created:

Name	Class	Size
data	environment	56 bytes
env	environment	56 bytes

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.

File paths: relative

Great job! Using relative paths to the files within your workflowr project makes it easier to run your code on other machines.

Repository version: 5976ed7

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:    docs/.DS_Store
    Ignored:    docs/figure/.DS_Store
    Ignored:    output/.DS_Store

Untracked files:
    Untracked:  .Rprofile
    Untracked:  ._.DS_Store
    Untracked:  .gitignore
    Untracked:  @
    Untracked:  _workflowr.yml
    Untracked:  analysis/._PASdescriptiveplots.Rmd
    Untracked:  analysis/._cuttoffPercUsage.Rmd
    Untracked:  analysis/APApeak_Phenotype_GeneLocAnno.Nuclear.5perc.fc.gz.qqnorm.allChrom
    Untracked:  analysis/APApeak_Phenotype_GeneLocAnno.Total.5perc.fc.gz.qqnorm.allChrom
    Untracked:  analysis/QTLexampleplots.Rmd
    Untracked:  analysis/cuttoffPercUsage.Rmd
    Untracked:  analysis/eQTLoverlap.Rmd
    Untracked:  analysis/interpret verify bam.Rmd
    Untracked:  analysis/interpret_verifybam.Rmd
    Untracked:  analysis/mergeRNA.Rmd
    Untracked:  analysis/oldstuffNotNeeded.Rmd
    Untracked:  analysis/remove_badlines.Rmd
    Untracked:  analysis/totalspec.Rmd
    Untracked:  apaQTL.Rproj
    Untracked:  code/.NascentRNAdtPlotFirstintronicPAS.sh.swp
    Untracked:  code/._ApaQTL_nominalNonnorm.sh
    Untracked:  code/._BothFracDTPlotGeneRegions.sh
    Untracked:  code/._BothFracDTPlotGeneRegions_normalized.sh
    Untracked:  code/._EandPqtl_perm.sh
    Untracked:  code/._EandPqtls.sh
    Untracked:  code/._FC_NucintornUpandDown.sh
    Untracked:  code/._FC_UTR.sh
    Untracked:  code/._FC_intornUpandDownsteamPAS.sh
    Untracked:  code/._FC_nascentseq.sh
    Untracked:  code/._FC_newPeaks_olddata.sh
    Untracked:  code/._HMMpermuteTotal.py
    Untracked:  code/._HmmPermute.py
    Untracked:  code/._IntronicPASDT.sh
    Untracked:  code/._LC_samplegroups.py
    Untracked:  code/._LD_qtl.sh
    Untracked:  code/._LD_snpsproxy.sh
    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/._NomResfromPASSNP.py
    Untracked:  code/._NuclearPAS_5per.bed.py
    Untracked:  code/._PTTfacetboxplots.R
    Untracked:  code/._PrematureQTLNominal.sh
    Untracked:  code/._PrematureQTLPermuted.sh
    Untracked:  code/._QTL2bed.py
    Untracked:  code/._QTL2bed_withstrand.py
    Untracked:  code/._RNAbam2bw.sh
    Untracked:  code/._RNAseqDTplot.sh
    Untracked:  code/._RunRes2PAS.sh
    Untracked:  code/._SAF215upbed.py
    Untracked:  code/._SnakefilePAS
    Untracked:  code/._SnakefilefiltPAS
    Untracked:  code/._TESplots100bp.sh
    Untracked:  code/._TESplots150bp.sh
    Untracked:  code/._TESplots200bp.sh
    Untracked:  code/._TotalPAS_5perc.bed.py
    Untracked:  code/._Untitled
    Untracked:  code/._ZipandTabPheno.sh
    Untracked:  code/._aAPAqtl_nominal39ind.sh
    Untracked:  code/._annotatePacBioPASregion.sh
    Untracked:  code/._annotatedPAS2bed.py
    Untracked:  code/._apaInPandE.py
    Untracked:  code/._apaQTLCorrectPvalMakeQQ.R
    Untracked:  code/._apaQTLCorrectpval_6or7a.R
    Untracked:  code/._apaQTL_Nominal.sh
    Untracked:  code/._apaQTL_nominalv67.sh
    Untracked:  code/._apaQTL_permuted.sh
    Untracked:  code/._apaQTL_permuted_test6A7A.sh
    Untracked:  code/._apainRibo.py
    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/._changeRibonomQTLres2genename.py
    Untracked:  code/._changenomQTLres2geneName.py
    Untracked:  code/._chooseAnno2PAS_pacbio.py
    Untracked:  code/._chooseAnno2SAF.py
    Untracked:  code/._chooseSignalSite
    Untracked:  code/._chooseSignalSite.py
    Untracked:  code/._closestannotated.sh
    Untracked:  code/._closestannotated_byfrac.sh
    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/._convertNominal2SNPloc2Versions.py
    Untracked:  code/._convertNumeric.py
    Untracked:  code/._correctNomeqtl.R
    Untracked:  code/._createPlinkSampfile.py
    Untracked:  code/._dag.pdf
    Untracked:  code/._eQTL_switch2snploc.py
    Untracked:  code/._eQTLgenestestedapa.py
    Untracked:  code/._encodeRNADTplots.sh
    Untracked:  code/._extractGenotypes.py
    Untracked:  code/._extractseqfromqtlfastq.py
    Untracked:  code/._fc2leafphen.py
    Untracked:  code/._fc_filteredPAS6and7As.sh
    Untracked:  code/._fifteenBPupstreamPAS.py
    Untracked:  code/._fiftyBPupstreamPAS.py
    Untracked:  code/._filter5perc.R
    Untracked:  code/._filter5percPheno.py
    Untracked:  code/._filterLDsnps.py
    Untracked:  code/._filterMPPAS.py
    Untracked:  code/._filterMPPAS_15.py
    Untracked:  code/._filterMPPAS_15_7As.py
    Untracked:  code/._filterMPPAS_50.py
    Untracked:  code/._filterSAFforMP.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/._fixFChead_short.py
    Untracked:  code/._fixH3k12ac.py
    Untracked:  code/._fixPASregionSNPs.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/._getApapval4eqtl_version67.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/._intersectVCFandupPAS.sh
    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/._mapSSsnps2PAS.sh
    Untracked:  code/._mergRNABam.sh
    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/._nucQTLGWAS.py
    Untracked:  code/._nucSpecQTLineData.py
    Untracked:  code/._nucSpeceffectsize.py
    Untracked:  code/._pQTLsotherdata.py
    Untracked:  code/._pacbioDT.sh
    Untracked:  code/._pacbioIntronicDT.sh
    Untracked:  code/._parseBestbamid.py
    Untracked:  code/._peak2PAS.py
    Untracked:  code/._peakFC.sh
    Untracked:  code/._pheno2countonly.R
    Untracked:  code/._phenoQTLfromlist.py
    Untracked:  code/._processYRIgen.py
    Untracked:  code/._pttQTLsinapaQTL.py
    Untracked:  code/._qtlRegionseq.sh
    Untracked:  code/._qtlsPvalOppFrac.py
    Untracked:  code/._quantassign2parsedpeak.py
    Untracked:  code/._removeXfromHmm.py
    Untracked:  code/._removeloc_pheno.py
    Untracked:  code/._riboQTL.sh
    Untracked:  code/._runCorrectNomEqtl.sh
    Untracked:  code/._runHMMpermuteAPAqtls.sh
    Untracked:  code/._runHMMpermuteeQTLS.sh
    Untracked:  code/._runMakeEmpiricaleQTL_unexp.sh
    Untracked:  code/._runMakeeQTLempirical.sh
    Untracked:  code/._run_bam2bw_all3prime.sh
    Untracked:  code/._run_bam2bw_extra3.sh
    Untracked:  code/._run_bestbamid.sj
    Untracked:  code/._run_filtersnpLD.sh
    Untracked:  code/._run_getAPAfromeQTL_version6.7.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_prxySNP.sh
    Untracked:  code/._run_pttfacetboxplot.sh
    Untracked:  code/._run_sepUsagephen.sh
    Untracked:  code/._run_sepgenobychrom.sh
    Untracked:  code/._run_verifybam.sh
    Untracked:  code/._selectNominalPvalues.py
    Untracked:  code/._sepUsagePhen.py
    Untracked:  code/._sepgenobychrom.py
    Untracked:  code/._snakemakePAS.batch
    Untracked:  code/._snakemakefiltPAS.batch
    Untracked:  code/._sortindexRNAbam.sh
    Untracked:  code/._submit-snakemakePAS.sh
    Untracked:  code/._submit-snakemakefiltPAS.sh
    Untracked:  code/._subsetAPAnotEorPgene.py
    Untracked:  code/._subsetAPAnotEorPgene_2versions.py
    Untracked:  code/._subsetApanoteGene.py
    Untracked:  code/._subsetApanoteGene_2versions.py
    Untracked:  code/._subsetUnexplainedeQTLs.py
    Untracked:  code/._subsetVCF_SS.sh
    Untracked:  code/._subsetVCF_noSSregions.sh
    Untracked:  code/._subsetVCF_upstreamPAS.sh
    Untracked:  code/._subset_diffisopheno.py
    Untracked:  code/._subsetpermAPAwithGenelist.py
    Untracked:  code/._subsetpermAPAwithGenelist_2versions.py
    Untracked:  code/._subsetvcf_otherreg.sh
    Untracked:  code/._subsetvcf_permSS.sh
    Untracked:  code/._subtrachfiveprimeUTR.sh
    Untracked:  code/._subtractExons.sh
    Untracked:  code/._subtractfiveprimeUTR.sh
    Untracked:  code/._tabixSNPS.sh
    Untracked:  code/._tenBPupstreamPAS.py
    Untracked:  code/._testVerifyBam.sh
    Untracked:  code/._totSeceffectsize.py
    Untracked:  code/._twentyBPupstreamPAS.py
    Untracked:  code/._utrdms2saf.py
    Untracked:  code/._vcf2bed.py
    Untracked:  code/._verifyBam18517N.sh
    Untracked:  code/._verifyBam18517T.sh
    Untracked:  code/._verifyBam19128N.sh
    Untracked:  code/._verifyBam19128T.sh
    Untracked:  code/._wrap_verifybam.sh
    Untracked:  code/._writePTTexamplecode.py
    Untracked:  code/._writePTTexamplecode.sh
    Untracked:  code/.pversion
    Untracked:  code/.snakemake/
    Untracked:  code/1
    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_nominal_versions67.err
    Untracked:  code/APAqtl_nominal_versions67.out
    Untracked:  code/APAqtl_permuted.err
    Untracked:  code/APAqtl_permuted.out
    Untracked:  code/APAqtl_permuted_versions67.err
    Untracked:  code/APAqtl_permuted_versions67.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/EandPqtl.err
    Untracked:  code/EandPqtl.out
    Untracked:  code/EandPqtl_perm.sh
    Untracked:  code/EandPqtls.sh
    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_nascent.err
    Untracked:  code/FC_nascentout
    Untracked:  code/FC_nascentseq.sh
    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/IntronicPASDT.err
    Untracked:  code/IntronicPASDT.out
    Untracked:  code/IntronicPASDT.sh
    Untracked:  code/LC_samplegroups.py
    Untracked:  code/LD_qtl.sh
    Untracked:  code/LD_snpsproxy.sh
    Untracked:  code/LD_vcftools.hap.out
    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/NomResfromPASSNP.py
    Untracked:  code/NuclearPAS_5per.bed.py
    Untracked:  code/Nuclear_example.err
    Untracked:  code/Nuclear_example.out
    Untracked:  code/PACbioDT.err
    Untracked:  code/PACbioDT.out
    Untracked:  code/PACbioDTitronic.err
    Untracked:  code/PACbioDTitronic.out
    Untracked:  code/PTTfacetboxplots.R
    Untracked:  code/PrematureQTLNominal.sh
    Untracked:  code/PrematureQTLPermuted.sh
    Untracked:  code/Prematureqtl_nominal.err
    Untracked:  code/Prematureqtl_nominal.out
    Untracked:  code/Prematureqtl_permuted.err
    Untracked:  code/Prematureqtl_permuted.out
    Untracked:  code/QTL2bed.py
    Untracked:  code/QTL2bed_withstrand.py
    Untracked:  code/README.md
    Untracked:  code/RNABam2BW.err
    Untracked:  code/RNABam2BW.out
    Untracked:  code/RNAbam2bw.sh
    Untracked:  code/RNAseqDTPlotGeneRegions.err
    Untracked:  code/RNAseqDTPlotGeneRegions.out
    Untracked:  code/RNAseqDTplot.sh
    Untracked:  code/Rplots.pdf
    Untracked:  code/RunRes2PAS.sh
    Untracked:  code/SAF215upbed.py
    Untracked:  code/SAF215upbed_gen.py
    Untracked:  code/Script4NuclearPTTqtlexamples.sh
    Untracked:  code/Script4NuclearQTLexamples.sh
    Untracked:  code/Script4TotalPTTqtlexamples.sh
    Untracked:  code/Script4TotalQTLexamples.sh
    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/TotalPAS_5perc.bed.py
    Untracked:  code/Total_example.err
    Untracked:  code/Total_example.out
    Untracked:  code/Untitled
    Untracked:  code/Upstream100Bases_general.py
    Untracked:  code/YRI_LCL.vcf.gz
    Untracked:  code/YRI_LCL_chr1.vcf.gz.log
    Untracked:  code/YRI_LCL_chr1.vcf.gz.recode.vcf
    Untracked:  code/ZipandTabPheno.sh
    Untracked:  code/aAPAqtl_nominal39ind.sh
    Untracked:  code/annotatePacBioPASregion.sh
    Untracked:  code/annotatedPAS2bed.py
    Untracked:  code/annotatedPASregion.err
    Untracked:  code/annotatedPASregion.out
    Untracked:  code/apaInPandE.py
    Untracked:  code/apaQTLCorrectPvalMakeQQ_4pc.R
    Untracked:  code/apaQTLCorrectpval_6or7a.R
    Untracked:  code/apaQTL_Nominal_4pc.sh
    Untracked:  code/apaQTL_nominalv67.sh
    Untracked:  code/apaQTL_permuted.4pc.sh
    Untracked:  code/apaQTL_permuted_test6A7A.sh
    Untracked:  code/apafacetboxplots.R
    Untracked:  code/apainRibo.py
    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/binary_fileset.log
    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/callSHscripts.txt
    Untracked:  code/changePermQTLres2geneName.py
    Untracked:  code/changeRibonomQTLres2genename.py
    Untracked:  code/changenomQTLres2geneName.py
    Untracked:  code/chooseAnno2PAS_pacbio.py
    Untracked:  code/closestannotated.err
    Untracked:  code/closestannotated.out
    Untracked:  code/closestannotated.sh
    Untracked:  code/closestannotated_byfrac.sh
    Untracked:  code/closestannotatedbyfrac.err
    Untracked:  code/closestannotatedbyfrac.out
    Untracked:  code/codingdms2bed.py
    Untracked:  code/convertNominal2SNPLOC.py
    Untracked:  code/convertNominal2SNPloc2Versions.py
    Untracked:  code/correctNomeqtl.R
    Untracked:  code/createPlinkSampfile.py
    Untracked:  code/dag.pdf
    Untracked:  code/dagPAS.pdf
    Untracked:  code/dagfiltPAS.pdf
    Untracked:  code/eQTL_switch2snploc.py
    Untracked:  code/eQTLgenestestedapa.py
    Untracked:  code/encodeRNADTplots.sh
    Untracked:  code/environmentLeaf.yaml
    Untracked:  code/extractGenotypes.py
    Untracked:  code/extractseqfromqtlfastq.py
    Untracked:  code/fc2leafphen.py
    Untracked:  code/fc_filteredPAS6and7As.sh
    Untracked:  code/fifteenBPupstreamPAS.py
    Untracked:  code/fiftyBPupstreamPAS.py
    Untracked:  code/filterLDsnps.py
    Untracked:  code/filterMPPAS.py
    Untracked:  code/filterMPPAS_15.py
    Untracked:  code/filterMPPAS_15_7As.py
    Untracked:  code/filterMPPAS_50.py
    Untracked:  code/filterSAFforMP.py
    Untracked:  code/filterSAFforMP_gen.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_short.py
    Untracked:  code/fixFChead_summary.py
    Untracked:  code/fixH3k12ac.py
    Untracked:  code/fixPASregionSNPs.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/getApapval4eqtl_version67.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/intersectPAS_ssSNPS.err
    Untracked:  code/intersectPAS_ssSNPS.out
    Untracked:  code/intersectVCFPAS.err
    Untracked:  code/intersectVCFPAS.out
    Untracked:  code/intersectVCFandupPAS.sh
    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/mapSSsnps2PAS.sh
    Untracked:  code/mergRNABam.sh
    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/mergeRNAbam.err
    Untracked:  code/mergeRNAbam.out
    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/nucQTLGWAS.py
    Untracked:  code/nucQTLGWAS_withLD.py
    Untracked:  code/nucSpecQTLineData.py
    Untracked:  code/nucSpeceffectsize.py
    Untracked:  code/pQTLsotherdata.py
    Untracked:  code/pacbioDT.sh
    Untracked:  code/pacbioIntronicDT.sh
    Untracked:  code/parseBestbamid.py
    Untracked:  code/phenoQTLfromlist.py
    Untracked:  code/plink.log
    Untracked:  code/processYRIgen.py
    Untracked:  code/prxySNP.err
    Untracked:  code/prxySNP.out
    Untracked:  code/pttFacetBoxplots.err
    Untracked:  code/pttFacetBoxplots.out
    Untracked:  code/pttQTLsinapaQTL.py
    Untracked:  code/pullTwoMechData.py
    Untracked:  code/qtlFacetBoxplots.err
    Untracked:  code/qtlFacetBoxplots.out
    Untracked:  code/qtlRegionseq.sh
    Untracked:  code/qtlsPvalOppFrac.py
    Untracked:  code/rLD_vcftools.hap.err
    Untracked:  code/removeXfromHmm.py
    Untracked:  code/removeloc_pheno.py
    Untracked:  code/riboQTL.sh
    Untracked:  code/riboqtl.err
    Untracked:  code/riboqtl.out
    Untracked:  code/runBestBamID.err
    Untracked:  code/runCorrectNomEqtl.sh
    Untracked:  code/runCorrectNomeqtl.err
    Untracked:  code/runCorrectNomeqtl.out
    Untracked:  code/runFilterLD.err
    Untracked:  code/runFilterLD.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_bam2bw.err
    Untracked:  code/run_bam2bw.out
    Untracked:  code/run_bam2bw_all3prime.sh
    Untracked:  code/run_bam2bw_extra3.sh
    Untracked:  code/run_bam2bwexta.err
    Untracked:  code/run_bam2bwexta.out
    Untracked:  code/run_bestbamid.sh
    Untracked:  code/run_distPAS2Sig.sh
    Untracked:  code/run_filtersnpLD.sh
    Untracked:  code/run_getAPAfromanyeQTL.err
    Untracked:  code/run_getAPAfromanyeQTL.out
    Untracked:  code/run_getAPAfromeQTL_version6.7.sh
    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_prxySNP.sh
    Untracked:  code/run_pttfacetboxplot.sh
    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/run_verifybam.err
    Untracked:  code/run_verifybam.out
    Untracked:  code/run_verifybam.sh
    Untracked:  code/run_verifybam128N.err
    Untracked:  code/run_verifybam128N.out
    Untracked:  code/run_verifybam128T.err
    Untracked:  code/run_verifybam128T.out
    Untracked:  code/run_verifybam517N.err
    Untracked:  code/run_verifybam517N.out
    Untracked:  code/run_verifybam517T.err
    Untracked:  code/run_verifybam517T.out
    Untracked:  code/run_verifybam_fullVCF.sh
    Untracked:  code/runprxySNP.err
    Untracked:  code/runprxySNP.out
    Untracked:  code/runres2pas.err
    Untracked:  code/runres2pas.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/sortindexRNABam.err
    Untracked:  code/sortindexRNABam.out
    Untracked:  code/sortindexRNAbam.sh
    Untracked:  code/subsetAPAnotEorPgene.py
    Untracked:  code/subsetAPAnotEorPgene_2versions.py
    Untracked:  code/subsetApanoteGene.py
    Untracked:  code/subsetApanoteGene_2versions.py
    Untracked:  code/subsetUnexplainedeQTLs.py
    Untracked:  code/subsetVCF_SS.sh
    Untracked:  code/subsetVCF_noSSregions.sh
    Untracked:  code/subsetVCF_upstreamPAS.sh
    Untracked:  code/subset_diffisopheno.py
    Untracked:  code/subsetpermAPAwithGenelist.py
    Untracked:  code/subsetpermAPAwithGenelist_2versions.py
    Untracked:  code/subsetvcf_SS.err
    Untracked:  code/subsetvcf_SS.out
    Untracked:  code/subsetvcf_noSS.err
    Untracked:  code/subsetvcf_noSS.out
    Untracked:  code/subsetvcf_otherreg.sh
    Untracked:  code/subsetvcf_pas.err
    Untracked:  code/subsetvcf_pas.out
    Untracked:  code/subsetvcf_perm.err
    Untracked:  code/subsetvcf_perm.out
    Untracked:  code/subsetvcf_permSS.sh
    Untracked:  code/subsetvcf_rand.err
    Untracked:  code/subsetvcf_rand.out
    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/tenBPupstreamPAS.py
    Untracked:  code/testVerifyBam.sh
    Untracked:  code/test_verifybam.err
    Untracked:  code/test_verifybam.out
    Untracked:  code/totSeceffectsize.py
    Untracked:  code/transcriptdm2bed.py
    Untracked:  code/twentyBPupstreamPAS.py
    Untracked:  code/utrdms2saf.py
    Untracked:  code/vcf2bed.py
    Untracked:  code/vcf_keepsnps.err
    Untracked:  code/vcf_keepsnps.out
    Untracked:  code/verifyBam18517N.sh
    Untracked:  code/verifyBam18517T.sh
    Untracked:  code/verifyBam19128N.sh
    Untracked:  code/verifyBam19128T.sh
    Untracked:  code/wrap_verifybam.err
    Untracked:  code/wrap_verifybam.out
    Untracked:  code/wrap_verifybam.sh
    Untracked:  code/wrap_verifybam_full.sh
    Untracked:  code/writeExampleQTLcode.py
    Untracked:  code/writePTTexamplecode.py
    Untracked:  code/zipandtabPhen.err
    Untracked:  code/zipandtabPhen.out
    Untracked:  data/._.DS_Store
    Untracked:  data/._MetaDataSequencing.txt
    Untracked:  data/AnnotatedPAS/
    Untracked:  data/ApaByEgene/
    Untracked:  data/ApaByPgene/
    Untracked:  data/BadLines/
    Untracked:  data/Battle_pQTL/
    Untracked:  data/CheckSums/
    Untracked:  data/CompareOldandNew/
    Untracked:  data/DTmatrix/
    Untracked:  data/DiffIso/
    Untracked:  data/EncodeRNA/
    Untracked:  data/ExampleQTLPlots/
    Untracked:  data/FlaggedPAS/
    Untracked:  data/GWAS_overlap/
    Untracked:  data/GeuvadisRNA/
    Untracked:  data/HMMqtls/
    Untracked:  data/Li_eQTLs/
    Untracked:  data/NascentRNA/
    Untracked:  data/NucSpeceQTLeffect/
    Untracked:  data/PAS/
    Untracked:  data/PAS_postFlag/
    Untracked:  data/PolyA_DB/
    Untracked:  data/PreTerm_pheno/
    Untracked:  data/PrematureQTLNominal/
    Untracked:  data/PrematureQTLPermuted/
    Untracked:  data/QTLGenotypes/
    Untracked:  data/QTLoverlap/
    Untracked:  data/QTLoverlap_nonNorm/
    Untracked:  data/README.md
    Untracked:  data/RNAseq/
    Untracked:  data/Reads2UTR/
    Untracked:  data/SNPinSS/
    Untracked:  data/SignalSiteFiles/
    Untracked:  data/TF_motifdisruption/
    Untracked:  data/ThirtyNineIndQtl_nominal/
    Untracked:  data/Version15bp6As/
    Untracked:  data/Version15bp7As/
    Untracked:  data/apaQTLNominal/
    Untracked:  data/apaQTLNominal_4pc/
    Untracked:  data/apaQTLPermuted/
    Untracked:  data/apaQTLPermuted_4pc/
    Untracked:  data/apaQTLs/
    Untracked:  data/assignedPeaks/
    Untracked:  data/assignedPeaks_15Up/
    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/
    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/locusZoom/
    Untracked:  data/mergedBG/
    Untracked:  data/mergedBW_byfrac/
    Untracked:  data/mergedBW_norm/
    Untracked:  data/mergedBam/
    Untracked:  data/mergedbyFracBam/
    Untracked:  data/molPhenos/
    Untracked:  data/molQTLs/
    Untracked:  data/motifdistrupt/
    Untracked:  data/netseq/
    Untracked:  data/nonNorm_pheno/
    Untracked:  data/nuc_10up/
    Untracked:  data/nuc_10upclean/
    Untracked:  data/oldPASfiles/
    Untracked:  data/overlapeQTL_try2/
    Untracked:  data/overlapeQTLs/
    Untracked:  data/pQTLoverlap/
    Untracked:  data/pacbio/
    Untracked:  data/peakCoverage/
    Untracked:  data/peaks_5perc/
    Untracked:  data/phenotype/
    Untracked:  data/phenotype_5perc/
    Untracked:  data/pttQTL/
    Untracked:  data/pttQTLplots/
    Untracked:  data/sigDiffGenes.txt
    Untracked:  data/sort/
    Untracked:  data/sort_clean/
    Untracked:  data/sort_waspfilter/
    Untracked:  data/twoMech/
    Untracked:  data/verifyBAM/
    Untracked:  data/verifyBAM_full/
    Untracked:  docs/._.DS_Store
    Untracked:  docs/figure/._.DS_Store
    Untracked:  nohup.out
    Untracked:  output/._.DS_Store
    Untracked:  output/._meanCorrelationPhenotypes.svg
    Untracked:  output/dtPlots/
    Untracked:  output/fastqc/
    Untracked:  output/meanCorrelationPhenotypes.svg
    Untracked:  run_verifybam517N.err
    Untracked:  run_verifybam517N.out

Unstaged changes:
    Modified:   analysis/Readdistagainstfeatures.Rmd
    Modified:   analysis/overlapapaqtlsandeqtls.Rmd
    Modified:   analysis/version15bpfilter.Rmd
    Modified:   code/BothFracDTPlotGeneRegions.sh
    Modified:   code/Snakefile
    Modified:   code/SnakefilefiltPAS
    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
    Modified:   code/mergeAllBam.sh
    Modified:   code/mergeByFracBam.sh
    Modified:   code/mergePeaks.sh
    Modified:   code/peakFC.sh
    Modified:   code/snakemake.batch
    Modified:   code/snakemakePAS.batch
    Modified:   code/snakemakefiltPAS.batch
    Modified:   code/submit-snakemake.sh
    Modified:   code/submit-snakemakePAS.sh
    Modified:   code/submit-snakemakefiltPAS.sh
    Deleted:    code/test.txt
    Modified:   data/MetaDataSequencing.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
html	00fe2b4	brimittleman	2019-07-26	Build site.
Rmd	cee6ce0	brimittleman	2019-07-26	get pvalues form <-16 tests
html	33a700a	brimittleman	2019-07-25	Build site.
Rmd	f3e3e16	brimittleman	2019-07-25	small edits from paper writing and add gwas analysis
html	272b0b4	brimittleman	2019-07-08	Build site.
Rmd	b1e6dd1	brimittleman	2019-07-08	update ptt analysis

I am interesting in understanding the PTTqtls a bit more. I want to ask if pttQTLs are apaQTLs. I will ask if the PTTqtl genes are also apaQTL genes.

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 1.4.0
Run ?workflowr for help getting started

PTT

totptt=read.table("../data/PrematureQTLPermuted/Total_preterminationPheno.txt.gz.qqnorm_AllChrBH.txt", stringsAsFactors = F, header = T) %>% filter(-log10(bh)>1) %>% separate(pid,into = c("chr", "start", "end", "geneID"), sep=":") %>% separate(geneID, into=c("gene", "Frac"),sep="_") %>% select(gene) %>% unique()

totpttQTL=read.table("../data/PrematureQTLPermuted/Total_preterminationPheno.txt.gz.qqnorm_AllChrBH.txt", stringsAsFactors = F, header = T) %>% filter(-log10(bh)>1)
write.table(totpttQTL, file="../data/pttQTL/TotalPttQTL.txt", col.names = T, row.names = F, quote = F, sep="\t")

nucptt=read.table("../data/PrematureQTLPermuted/Nuclear_preterminationPheno.txt.gz.qqnorm_AllChrBH.txt", stringsAsFactors = F, header = T) %>% filter(-log10(bh)>1) %>% separate(pid,into = c("chr", "start", "end", "geneID"), sep=":") %>% separate(geneID, into=c("gene", "Frac"),sep="_") %>% select(gene) %>% unique()


nucpttQTL=read.table("../data/PrematureQTLPermuted/Nuclear_preterminationPheno.txt.gz.qqnorm_AllChrBH.txt", stringsAsFactors = F, header = T) %>% filter(-log10(bh)>1)
write.table(nucpttQTL, file="../data/pttQTL/NuclearPttQTL.txt", col.names = T, row.names = F, quote = F, sep="\t")

APA

nucAPA=read.table("../data/apaQTLs/NuclearapaQTLGenes.txt", col.names = c("gene"),stringsAsFactors = F)
totAPA=read.table("../data/apaQTLs/TotalapaQTLGenes.txt", col.names = c("gene"),stringsAsFactors = F)

totptt %>% inner_join(totAPA,by="gene") %>% nrow()

[1] 20

totptt %>% anti_join(totAPA,by="gene") %>% nrow()

[1] 4

nucptt %>% inner_join(nucAPA,by="gene") %>% nrow()

[1] 54

nucptt %>% anti_join(nucAPA,by="gene") %>% nrow()

[1] 15

There are 8 total ptt genes that are not apaQTL genes and there are 15 nuclear ptt genes that are not apaQTL genes.

Look at the distribution. To do this I will pull out the ptt associations from the apa data.

I will right a script that takes a the fraction, pulls the ptt associations into 2 files, one for the associations and one for the non associations.

python pttQTLsinapaQTL.py Total
python pttQTLsinapaQTL.py Nuclear

names=c('pid' ,'nvar' ,'shape1' ,'shape2', 'dummy' ,'sid', 'dist', 'npval', 'slope', 'ppval' ,'bpval', 'bh')
totapaPTT=read.table("../data/pttQTL/Totalapa_TotalPttQTL.txt", col.names = names, stringsAsFactors = F)
totapaNotPTT=read.table("../data/pttQTL/Totalapa_NOT_TotalPttQTL.txt", col.names = names, stringsAsFactors = F)

qqplot(-log10(runif(nrow(totapaNotPTT))), -log10(totapaNotPTT$bpval),ylab="-log10 expression permuted pvalue", xlab="Uniform expectation", main="Total PTT genes in Total apaQTL")
points(sort(-log10(runif(nrow(totapaPTT)))), sort(-log10(totapaPTT$bpval)),col= alpha("Red"))
abline(0,1)
legend("topleft", legend=c("ptt gene", "All other genes"),col=c("red", "black"), pch=16,bty = 'n')

Version	Author	Date
272b0b4	brimittleman	2019-07-08

nucapaPTT=read.table("../data/pttQTL/Nuclearapa_NuclearPttQTL.txt", col.names = names, stringsAsFactors = F)
nucapaNotPTT=read.table("../data/pttQTL/Nuclearapa_NOT_NuclearPttQTL.txt", col.names = names, stringsAsFactors = F)

qqplot(-log10(runif(nrow(nucapaNotPTT))), -log10(nucapaNotPTT$bpval),ylab="-log10 expression permuted pvalue", xlab="Uniform expectation", main="Nuclear PTT genes in Nuclear apaQTL")
points(sort(-log10(runif(nrow(nucapaPTT)))), sort(-log10(nucapaPTT$bpval)),col= alpha("Red"))
abline(0,1)

legend("topleft", legend=c("ptt gene", "All other genes"),col=c("red", "black"), pch=16,bty = 'n')

Version	Author	Date
272b0b4	brimittleman	2019-07-08

These show the sharing is super high and we are getting at similar phenotypes in ptt and apa.

wilcox.test(nucapaPTT$bpval,nucapaNotPTT$bpval,alternative="less")


    Wilcoxon rank sum test with continuity correction

data:  nucapaPTT$bpval and nucapaNotPTT$bpval
W = 2372300, p-value < 2.2e-16
alternative hypothesis: true location shift is less than 0

wilcox.test(nucapaPTT$bpval,nucapaNotPTT$bpval,alternative="less")$p.value

[1] 9.869063e-41

Is there something interesting about the non overlap genes:

pttOnlyTot=totptt %>% anti_join(totAPA,by="gene")


totapaPTT_pttstatus=totapaPTT %>% separate(pid, into=c("chr", "start", "end", "geneID"),sep=":")  %>% separate(geneID, into=c("gene", "pos", "strand", "pas"),sep="_") %>% mutate(APAQTL=ifelse(gene %in% pttOnlyTot$gene, "No", "Yes"))

ggplot(totapaPTT_pttstatus,aes(x=APAQTL, y=bpval)) + geom_boxplot()

Version	Author	Date
33a700a	brimittleman	2019-07-25

pttOnlyTot$gene

[1] "C10orf88" "PHACTR4"  "USP37"    "ZNF718"

pttOnlyNuc=nucptt %>% anti_join(nucAPA,by="gene")


nucapaPTT_pttstatus=nucapaPTT %>% separate(pid, into=c("chr", "start", "end", "geneID"),sep=":")  %>% separate(geneID, into=c("gene", "pos", "strand", "pas"),sep="_") %>% mutate(APAQTL=ifelse(gene %in% pttOnlyTot$gene, "No", "Yes"))


ggplot(nucapaPTT_pttstatus,aes(x=APAQTL, y=bpval)) + geom_boxplot()

Version	Author	Date
33a700a	brimittleman	2019-07-25

pttOnlyNuc$gene

 [1] "ATP5C1"   "ARHGAP5"  "AP4E1"    "USP14"    "PRKCZ"    "MAP3K7CL"
 [7] "BCL2L13"  "IRAK2"    "FYCO1"    "IL17RB"   "SEC24B"   "HSPA9"   
[13] "PREP"     "ERLIN2"   "HACD4"

Plot these:

nucpttQTL %>% separate(pid, into=c("chr","start","end","geneID"), sep=":") %>% separate(geneID, into=c("gene","loc"),sep="_") %>%  anti_join(nucAPA,by="gene") %>% select(gene, chr,sid)

       gene chr         sid
1    ATP5C1  10   rs2802460
2    ATP5C1  10   rs2802460
3   ARHGAP5  14 rs114000106
4   ARHGAP5  14 rs114000106
5     AP4E1  15  rs56056949
6     AP4E1  15  rs56056949
7     USP14  18  rs11876726
8     USP14  18  rs11876726
9     PRKCZ   1  rs13302944
10 MAP3K7CL  21   rs9808644
11  BCL2L13  22   rs9604775
12    IRAK2   3   rs6776059
13    FYCO1   3  rs59842697
14    FYCO1   3  rs59842697
15   IL17RB   3   rs2289205
16   IL17RB   3   rs2289205
17   SEC24B   4   rs1509314
18    HSPA9   5  rs41294546
19    HSPA9   5  rs41294546
20     PREP   6  rs76627946
21     PREP   6  rs76627946
22   ERLIN2   8  rs77049216
23    HACD4   9  rs57721805
24    HACD4   9  rs57721805

Examples done need to rerun

These are from exploratory analysis

sbatch  run_qtlFacetBoxplots.sh Nuclear PPFIA1 11 rs188630869 none
sbatch  run_qtlFacetBoxplots.sh Nuclear ZDHHC17 12  rs74792673 none
sbatch  run_qtlFacetBoxplots.sh Nuclear ZNF844  19  rs116146966 none
sbatch  run_qtlFacetBoxplots.sh Nuclear PRKCZ   1   rs13302944 none


sbatch  run_qtlFacetBoxplots.sh Nuclear POU2F1  1   rs6668193 none
sbatch  run_qtlFacetBoxplots.sh Nuclear MAP3K7CL    21  rs9808644 none
sbatch  run_qtlFacetBoxplots.sh Nuclear BCL2L13 22  rs8141618 none
sbatch  run_qtlFacetBoxplots.sh Nuclear LINC00342   2   rs193252777 none
sbatch  run_qtlFacetBoxplots.sh Nuclear DZIP3   3   rs112409302 none

sbatch  run_qtlFacetBoxplots.sh Nuclear SUB1    5   rs76941541 none
sbatch  run_qtlFacetBoxplots.sh Nuclear BLVRA   7   rs1181594 none
sbatch  run_qtlFacetBoxplots.sh Nuclear NAPEPLD 7   rs56047178 none
sbatch  run_qtlFacetBoxplots.sh Nuclear WNT2    7   rs76105832 none
sbatch  run_qtlFacetBoxplots.sh Nuclear HACD4   9   rs57721805 none

totpttQTL %>% separate(pid, into=c("chr","start","end","geneID"), sep=":") %>% separate(geneID, into=c("gene","loc"),sep="_") %>%  anti_join(totAPA,by="gene") %>% select(gene, chr,sid)

      gene chr        sid
1 C10orf88  10  rs7904973
2 C10orf88  10  rs7904973
3  PHACTR4   1 rs76130516
4    USP37   2 rs79468589
5   ZNF718   4  rs6814287
6   ZNF718   4 rs28531086

sbatch  run_qtlFacetBoxplots.sh Total C10orf88  10  rs7091776 none
sbatch  run_qtlFacetBoxplots.sh Total UROS  10  rs11244646 none
sbatch  run_qtlFacetBoxplots.sh Total LRRC57    15  rs61489160 none
sbatch  run_qtlFacetBoxplots.sh Total ELMOD3    2   rs908302 none
sbatch  run_qtlFacetBoxplots.sh Total USP37 2   rs79468589 none
sbatch  run_qtlFacetBoxplots.sh Total PLSCR1    3   rs59690244 none
sbatch  run_qtlFacetBoxplots.sh Total ZNF718    4   rs6814287 none
sbatch  run_qtlFacetBoxplots.sh Total ZSCAN12   6   rs3799500 none

Moved these reslts to a ptt dir in the example qtl dir.

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_1.4.0 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 plyr_1.8.4       compiler_3.5.1  
 [5] pillar_1.3.1     git2r_0.25.2     highr_0.7        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] htmltools_0.3.6  rvest_0.3.2      assertthat_0.2.0 colorspace_1.3-2
[45] labeling_0.3     stringi_1.2.4    lazyeval_0.2.1   munsell_0.5.0   
[49] broom_0.5.1      crayon_1.3.4

apaQTL and PTTqtls

Briana Mittleman

7/8/2019

Examples done need to rerun