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
Rmd 41d1961 brimittleman 2019-09-04 wflow_publish(c(“analysis/signalsiteanalysis.Rmd”, “analysis/corrbetweenind.Rmd”,
html db6b12d brimittleman 2019-08-05 Build site.
Rmd c39919d brimittleman 2019-08-05 update pc plots
html 957c8f5 brimittleman 2019-06-13 Build site.
Rmd 6fea690 brimittleman 2019-06-13 fix big bug
html f1c3fb0 brimittleman 2019-05-09 Build site.
Rmd 1c60a3a brimittleman 2019-05-09 add metadata
html 144c00b brimittleman 2019-05-08 Build site.
Rmd 5e39f1c brimittleman 2019-05-08 choose pcs and start qtl rerun
html f5af9c6 brimittleman 2019-05-08 Build site.
Rmd 1ba7d2b brimittleman 2019-05-08 add pca 
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(reshape2)

Attaching package: 'reshape2'
The following object is masked from 'package:tidyr':

    smiths

Concatinate qqnorm res:

less APApeak_Phenotype_GeneLocAnno.Total.5perc.fc.gz.qqnorm_chr*.gz > APApeak_Phenotype_GeneLocAnno.Total.5perc.fc.gz.qqnorm.allChrom
less APApeak_Phenotype_GeneLocAnno.Nuclear.5perc.fc.gz.qqnorm_chr*.gz > APApeak_Phenotype_GeneLocAnno.Nuclear.5perc.fc.gz.qqnorm.allChrom
totalqqnorm=read.table("../data/phenotype_5perc/APApeak_Phenotype_GeneLocAnno.Total.5perc.fc.gz.qqnorm.allChrom", col.names = c('Chr',  'start',    'end',  'ID',   'NA18486',  'NA18498',  'NA18499',  'NA18501',  'NA18502',  'NA18504', 'NA18505',   'NA18508',  'NA18510',  'NA18511',  'NA18516',  'NA18519',  'NA18520',  'NA18522',  'NA18852', 'NA18853',   'NA18855',  'NA18856',  'NA18858',  'NA18861',  'NA18862',  'NA18870',  'NA18907',  'NA18909',  'NA18912', 'NA18913',   'NA18916',  'NA19092',  'NA19093',  'NA19101',  'NA19119',  'NA19130',  'NA19131',  'NA19137','NA19138',    'NA19140',  'NA19141',  'NA19144',  'NA19152',  'NA19153',  'NA19160',  'NA19171',  'NA19193',  'NA19200','NA19207',    'NA19209',  'NA19210',  'NA19223',  'NA19225',  'NA19238',  'NA19239',  'NA19257') )

totalqqnorm_matrix=as.matrix(totalqqnorm %>% select(-Chr, -start, -end, -ID))

RUn PCA:

pca_tot_peak=prcomp(totalqqnorm_matrix, center=T,scale=T)
pca_tot_df=as.data.frame(pca_tot_peak$rotation) %>% rownames_to_column(var="lib") %>% select(1:11)

pca_tot_df_fix=bind_cols(line=pca_tot_df[,dim(pca_tot_df)[[2]]],pca_tot_df[,3:dim(pca_tot_df)[[2]]-1])

Variance explained:

eigs_tot <- pca_tot_peak$sdev^2
proportion_tot = eigs_tot/sum(eigs_tot)

plot(proportion_tot)

Version Author Date
957c8f5 brimittleman 2019-06-13 
nuclearqqnorm=read.table("../data/phenotype_5perc/APApeak_Phenotype_GeneLocAnno.Nuclear.5perc.fc.gz.qqnorm.allChrom", col.names = c('Chr',  'start',    'end',  'ID',   'NA18486',  'NA18498',  'NA18499',  'NA18501',  'NA18502',  'NA18504', 'NA18505',   'NA18508',  'NA18510',  'NA18511',  'NA18516',  'NA18519',  'NA18520',  'NA18522',  'NA18852', 'NA18853',   'NA18855',  'NA18856',  'NA18858',  'NA18861',  'NA18862',  'NA18870',  'NA18907',  'NA18909',  'NA18912', 'NA18913',   'NA18916',  'NA19092',  'NA19093',  'NA19101',  'NA19119',  'NA19130',  'NA19131',  'NA19137','NA19138',    'NA19140',  'NA19141',  'NA19144',  'NA19152',  'NA19153',  'NA19160',  'NA19171',  'NA19193',  'NA19200','NA19207',    'NA19209',  'NA19210',  'NA19223',  'NA19225',  'NA19238',  'NA19239',  'NA19257'))

nuclearqqnorm_matrix=as.matrix(nuclearqqnorm %>% select(-Chr, -start, -end, -ID))
pca_nuc_peak=prcomp(nuclearqqnorm_matrix, center=T,scale=T)
pca_nuc_df=as.data.frame(pca_nuc_peak$rotation) %>% rownames_to_column(var="lib") %>% select(1:11)

pca_nuc_df_fix=bind_cols(line=pca_nuc_df[,dim(pca_nuc_df)[[2]]],pca_nuc_df[,3:dim(pca_nuc_df)[[2]]-1])

Variance explained:

eigs_nuc <- pca_nuc_peak$sdev^2
proportion_nuc = eigs_nuc/sum(eigs_nuc)

plot(proportion_nuc)

Version Author Date
957c8f5 brimittleman 2019-06-13

Plot together:

both_prop=as.data.frame(cbind(PCs=seq(1,54,1),Total=proportion_tot,Nuclear=proportion_nuc))
Warning in cbind(PCs = seq(1, 54, 1), Total = proportion_tot, Nuclear
= proportion_nuc): number of rows of result is not a multiple of vector
length (arg 2)
both_prop_melt=melt(both_prop, id.var=c("PCs"), variable.name="Fraction",value.name = "VariationExplained" )
ggplot(both_prop_melt, aes(x=PCs, y=VariationExplained,group=Fraction, color=Fraction)) + geom_line() + geom_vline(xintercept = 6, col="red") + annotate("text", label="6 PCs", x=10, y=.1) + labs(title="Proportion of variance explained \nin PCA on normalized APA usage")

Version Author Date
957c8f5 brimittleman 2019-06-13
144c00b brimittleman 2019-05-08 
both_prop_melt_filt=both_prop_melt %>% filter(PCs<10)

ggplot(both_prop_melt_filt, aes(x=PCs, y=VariationExplained,group=Fraction, color=Fraction)) + geom_line() + geom_vline(xintercept = 4, col="red") + annotate("text", label="4 PCs", x=5, y=.1) + labs(title="Proportion of variance explained \nin PCA on normalized APA usage")

Version Author Date
957c8f5 brimittleman 2019-06-13

WHich factors correlate with PCs:

metadata=read.table("../data/MetaDataSequencing.txt", stringsAsFactors = F, header = T)
metadata_tot=metadata %>% filter(fraction=="total") %>% select(batch,Sex, alive_avg, undiluted_avg,ratio260_280)
metadata_nuc=metadata %>% filter(fraction=="nuclear") %>% select(batch,Sex, alive_avg, undiluted_avg,ratio260_280)

Function from Ben

covariate_pc_pve_heatmap <- function(pc_df, covariate_df, title) {
  # Load in data
  pcs <- pc_df
  #pcs=pca_tot_df
  covs <- covariate_df
  #covs=metadata_tot

# Remove unimportant columns
  pcs <- as.matrix(pcs[,2:dim(pcs)[[2]]])
  covs <- data.frame(as.matrix(covs[,1:dim(covs)[[2]]]))

  # Initialize PVE heatmap
  pve_map <- matrix(0, dim(covs)[2], dim(pcs)[2])
  colnames(pve_map) <- colnames(pcs)
  rownames(pve_map) <- colnames(covs)

  # Loop through each PC, COV Pair and take correlation
  num_pcs <- dim(pcs)[2]
  num_covs <- dim(covs)[2]
  for (num_pc in 1:num_pcs) {
    for (num_cov in 1:num_covs) {
      pc_vec <- pcs[,num_pc]
      cov_vec <- covs[,num_cov]
      lin_model <- lm(pc_vec ~ cov_vec)
      pve_map[num_cov, num_pc] <- summary(lin_model)$adj.r.squared
      if (pve_map[num_cov, num_pc] <0){pve_map[num_cov, num_pc]=0}
    }
  }
  pve_map
  ord <- hclust( dist(scale(pve_map), method = "euclidean"), method = "ward.D" )$order

  melted_mat <- melt(pve_map)
  colnames(melted_mat) <- c("Covariate", "PC","PVE")

  #  Use factors to represent covariate and pc name
  melted_mat$Covariate <- factor(melted_mat$Covariate, levels = rownames(pve_map)[ord])
  melted_mat$PC <- factor(melted_mat$PC)
  if (dim(pcs)[2] == 10) {
    levels(melted_mat$PC) <- c(levels(melted_mat$PC)[1],levels(melted_mat$PC)[3:10],levels(melted_mat$PC)[2])
  }
  if (dim(pcs)[2] == 21) {
    levels(melted_mat$PC) <- c(levels(melted_mat$PC)[1],levels(melted_mat$PC)[12],levels(melted_mat$PC)[15:21],levels(melted_mat$PC)[2:11], levels(melted_mat$PC)[13:14])
  }

  #  PLOT!
  heatmap <- ggplot(data=melted_mat, aes(x=Covariate, y=PC)) + geom_tile(aes(fill=PVE)) + scale_fill_gradient2(midpoint=-.05, guide="colorbar")
  heatmap <- heatmap + theme(text = element_text(size=14), panel.background = element_blank(), axis.text.x = element_text(angle = 90, vjust=.5))
  heatmap <- heatmap + labs(y="latent factor", title=title)

  # Save File
  return(heatmap)
}
covariate_pc_pve_heatmap(pca_tot_df,metadata_tot, title="Total PCs")

Version Author Date
db6b12d brimittleman 2019-08-05
957c8f5 brimittleman 2019-06-13 
covariate_pc_pve_heatmap(pca_nuc_df,metadata_nuc, title="Nuclear PCs")

Version Author Date
db6b12d brimittleman 2019-08-05 

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] reshape2_1.4.3  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        workflowr_1.4.0 
 [9] tools_3.5.1      digest_0.6.18    lubridate_1.7.4  jsonlite_1.6    
[13] evaluate_0.12    nlme_3.1-137     gtable_0.2.0     lattice_0.20-38 
[17] pkgconfig_2.0.2  rlang_0.4.0      cli_1.1.0        rstudioapi_0.10 
[21] yaml_2.2.0       haven_1.1.2      withr_2.1.2      xml2_1.2.0      
[25] httr_1.3.1       knitr_1.20       hms_0.4.2        generics_0.0.2  
[29] fs_1.3.1         rprojroot_1.3-2  grid_3.5.1       tidyselect_0.2.5
[33] glue_1.3.0       R6_2.3.0         readxl_1.1.0     rmarkdown_1.10  
[37] modelr_0.1.2     magrittr_1.5     whisker_0.3-2    backports_1.1.2 
[41] scales_1.0.0     htmltools_0.3.6  rvest_0.3.2      assertthat_0.2.0
[45] colorspace_1.3-2 labeling_0.3     stringi_1.2.4    lazyeval_0.2.1  
[49] munsell_0.5.0    broom_0.5.1      crayon_1.3.4