Last updated: 2019-09-04

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: 41d1961

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/._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/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/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:  docs/figure/nonNormQTL.Rmd/._figure2D-1.pdf
    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/NuclearSpecAPAqtl.Rmd
    Modified:   analysis/PrematureTermQTL.Rmd
    Modified:   analysis/Readdistagainstfeatures.Rmd
    Modified:   analysis/overlapapaqtlsandeqtls.Rmd
    Modified:   analysis/rerunQTL_changePC.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
    Modified:   docs/figure/signalsiteanalysis.Rmd/figure1bMain-1.pdf
    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 0b8659d brimittleman 2019-06-19 Build site.
Rmd 654425c brimittleman 2019-06-19 subset on 5%
html 529a38a brimittleman 2019-06-18 Build site.
html cc966a0 brimittleman 2019-06-17 Build site.
Rmd 2f79c58 brimittleman 2019-06-17 write out data
html 386579e brimittleman 2019-06-10 Build site.
Rmd c753b24 brimittleman 2019-06-10 add nuc res
html 09323e7 brimittleman 2019-06-07 Build site.
Rmd f640ca3 brimittleman 2019-06-07 add results
html 4fa86e5 brimittleman 2019-06-07 Build site.
Rmd 3e5cc8e brimittleman 2019-06-07 code up to FC

I am interested in finding examples of intronic PAS that show RNAseq signatures upstream of the PAS but not downstream. To do this I will create a ratio of reads upstream/reads downstream standardized by the length of the region (up/downstream).

To do this I can use the work I did previously. Here I assigned each intronic PAS to an intron. I will do this analysis with the total fraction because I will be looking at steady state RNA seq.

library(workflowr)
This is workflowr version 1.4.0
Run ?workflowr for help getting started
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()

Total

mkdir ../data/intronRNAratio
totIntronicPeaks=read.table("../data/peaks_5perc/APApeak_Peaks_GeneLocAnno.Total.5perc.fc", stringsAsFactors = F, header = F,col.names = c("chr", "start", "end", "gene", "loc", "strand", "peak", "avgUsage")) %>% filter(loc=="intron") 

pas2intronTot=read.table("../data/intron_analysis/TotalIntronPeaksontoIntrons.bed",col.names = c("intronCHR", "intronStart", "intronEnd", "gene", "score", "strand", "peakCHR", "peakStart", "peakEnd", "PeakID", "meanUsage", "peakStrand"))  %>% mutate(PASloc=ifelse(strand=="+", peakEnd, peakStart)) %>% dplyr::select(intronCHR,intronStart, intronEnd, gene, strand, PeakID, PASloc ,meanUsage)

write.table(pas2intronTot, "../data/intronRNAratio/TotalIntronicPAS2Intron.txt", quote = F, row.names = F, col.names = F, sep="\t")

Make upstream and downstream PAS saf files using python.

 python getIntronUpstreamPAS.py
 python getIntronDownstreamPAS.py

These make Bed and SAF files. I will use the SAF files for feature counts with all of the RNA seq. These files are in /project2/yangili1/LCL/RNAseqGeuvadisBams/*.final.bam

sbatch FC_intornUpandDownsteamPAS.sh

Downstream Results:

downstream=read.table("../data/intronRNAratio/DownstreamIntron.fc", header = T,stringsAsFactors = F)
downstreamMean=rowSums(downstream[,7:ncol(downstream)])

downstreanMeanDF=as.data.frame(cbind(downstream[,1:6], downstreamMean)) %>% mutate(DownstreamMean_st=downstreamMean/Length) %>% select(Geneid,DownstreamMean_st )

Upstream Results:

upstream=read.table("../data/intronRNAratio/UpstreamIntron.fc", header = T,stringsAsFactors = F)
upstreamMean=rowSums(upstream[,7:ncol(upstream)])
upstreamMeanDF=as.data.frame(cbind(upstream[,1:6], upstreamMean)) %>% mutate(UpstreamMean_st=upstreamMean/Length) %>% select(Geneid,UpstreamMean_st )

Join Results:

I will use upstream - downstream

pas2intronTot_peaks=pas2intronTot %>% separate(PeakID, into=c("PAS", "gene", "loc"), sep=":") %>% select(PAS)


UpandDown=upstreamMeanDF %>% inner_join(downstreanMeanDF, by="Geneid") %>% mutate(UpMinusDown=UpstreamMean_st-DownstreamMean_st) %>% arrange(desc(UpMinusDown)) %>% separate(Geneid, sep=":", into=c("PAS", "gene", "loc", "PASloc", "Usage"))  %>% semi_join(pas2intronTot_peaks, by="PAS")


summary(UpandDown$UpMinusDown)
      Min.    1st Qu.     Median       Mean    3rd Qu.       Max. 
-1246.7926    -0.0324     0.0000     0.3251     0.2171   541.0908

I want to know how many are positive:

MoreUp=UpandDown %>% filter(UpMinusDown>0) 
summary(MoreUp$UpMinusDown)
    Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
  0.0000   0.0352   0.2268   2.7767   1.1271 541.0908 
nrow(MoreUp)
[1] 4131

4131 examples where there are more reads upstream in the intron than downstream.

To look for examples:

head(MoreUp)
        PAS     gene    loc    PASloc              Usage UpstreamMean_st
1  peak5519     HFM1 intron  91852934  0.889259259259259        541.0908
2 peak31203   NAP1L1 intron  76443346  0.906666666666667        473.3895
3 peak87311  BHLHE40 intron   5023296  0.866111111111111        321.8041
4 peak50349   ATXN2L intron  28844314 0.0661111111111111        217.0654
5  peak7377 NOTCH2NL intron 145277488  0.715925925925926        186.1226
6 peak60248   MYL12A intron   3248635  0.862777777777778        175.4362
  DownstreamMean_st UpMinusDown
1          0.000000    541.0908
2         99.452381    373.9371
3          6.033469    315.7707
4         14.939394    202.1260
5         12.959547    173.1631
6          9.109116    166.3271
write.table(MoreUp, file="../data/intronRNAratio/TotalPAS_MoreUpstreamRNAreads.txt", col.names = T, row.names = F, quote = F, sep="\t" )

Nuclear

We also have nacent RNA seq. I will do this with nuclear intronic PAS.

nucIntronicPeaks=read.table("../data/peaks_5perc/APApeak_Peaks_GeneLocAnno.Nuclear.5perc.fc", stringsAsFactors = F, header = F,col.names = c("chr", "start", "end", "gene", "loc", "strand", "peak", "avgUsage")) %>% filter(loc=="intron")


pas2intronNuc=read.table("../data/intron_analysis/IntronPeaksontoIntrons.bed",col.names = c("intronCHR", "intronStart", "intronEnd", "gene", "score", "strand", "peakCHR", "peakStart", "peakEnd", "PeakID", "meanUsage", "peakStrand"))  %>% mutate(PASloc=ifelse(strand=="+", peakEnd, peakStart)) %>% dplyr::select(intronCHR,intronStart, intronEnd, gene, strand, PeakID, PASloc ,meanUsage)

write.table(pas2intronNuc, "../data/intronRNAratio/NuclearIntronicPAS2Intron.txt", quote = F, row.names = F, col.names = F, sep="\t")

Make upstream and downstream PAS saf files using python.

python getUpstreamIntronNuclear.py
python getDownstreamIntronNuclear.py

These make Bed and SAF files. I will use the SAF files for feature counts with all of the nacent RNA seq.

sbatch FC_NucintornUpandDown.sh

Downstream Results:

downstreamNuc=read.table("../data/intronRNAratio/NuclearDownstreamIntron.fc", col.names = c("Geneid","Chr","Start", "End", "Strand", "Length", "Downstream"), header = T,stringsAsFactors = F)%>% mutate(Downstream_st=Downstream/Length) %>% select(Geneid,Downstream_st )

upstreamNuc=read.table("../data/intronRNAratio/NuclearUpstreamIntron.fc", col.names = c("Geneid","Chr","Start", "End", "Strand", "Length", "Upstream"), header = T,stringsAsFactors = F)%>% mutate(Upstream_st=Upstream/Length) %>% select(Geneid,Upstream_st )


pas2intronNucPAS=pas2intronNuc %>% separate(PeakID, into=c("PAS", "gene", "loc"), sep=":") %>% select(PAS)


UpandDown_nuc=upstreamNuc %>% inner_join(downstreamNuc, by="Geneid") %>% mutate(UpMinusDown=Upstream_st-Downstream_st) %>% arrange(desc(UpMinusDown)) %>% separate(Geneid, sep=":", into=c("PAS", "gene", "loc", "PASloc", "Usage")) %>% semi_join(pas2intronNucPAS, by="PAS")




summary(UpandDown_nuc$UpMinusDown)
      Min.    1st Qu.     Median       Mean    3rd Qu.       Max. 
-269.33846   -0.06775    0.01552    0.08418    0.36174   57.52867 
MoreUpNuc=UpandDown_nuc %>% filter(UpMinusDown>0) 
summary(MoreUpNuc$UpMinusDown)
    Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
 0.00001  0.08524  0.29229  0.66527  0.74025 57.52867 
nrow(MoreUpNuc)
[1] 7625
head(MoreUpNuc)
         PAS     gene    loc    PASloc              Usage Upstream_st
1  peak18198    BTAF1 intron  93719017  0.468148148148148    68.64486
2  peak83249 MIR155HG intron  26939933 0.0524074074074074    44.98583
3  peak86087    DDX17 intron  38887949 0.0955555555555556    89.22321
4   peak9172   SLAMF1 intron 160597898  0.123518518518519    17.37310
5  peak94269    RSRC1 intron 157921145 0.0548148148148148    18.57143
6 peak111306     IRF4 intron    403950 0.0694444444444444    15.43238
  Downstream_st UpMinusDown
1     11.116190    57.52867
2      0.000000    44.98583
3     57.814883    31.40833
4      0.000000    17.37310
5      2.275192    16.29624
6      0.000000    15.43238
write.table(MoreUpNuc, file="../data/intronRNAratio/NuclearPAS_MoreUpstreamNascentreads.txt", col.names = T, row.names = F, quote = F, sep="/t" )

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 workflowr_1.4.0

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] stringi_1.2.4    lazyeval_0.2.1   munsell_0.5.0    broom_0.5.1     
[49] crayon_1.3.4