Last updated: 2019-11-08
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.
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.
Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.
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.
Great job! Recording the operating system, R version, and package versions is critical for reproducibility.
Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.
Using absolute paths to the files within your workflowr project makes it difficult for you and others to run your code on a different machine. Change the absolute path(s) below to the suggested relative path(s) to make your code more reproducible.
absolute | relative |
---|---|
/project2/gilad/briana/apaQTL/data/intron_analysis/transcriptsMinusExons.sort.bed | ../data/intron_analysis/transcriptsMinusExons.sort.bed |
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: docs/figure/PAS_graphs_total.Rmd/.DS_Store
Ignored: docs/figure/choosePCs.Rmd/.DS_Store
Ignored: docs/figure/exvunexpeQTL.Rmd/.DS_Store
Ignored: docs/figure/snpinSS.Rmd/.DS_Store
Ignored: output/.DS_Store
Untracked files:
Untracked: .Rprofile
Untracked: ._.DS_Store
Untracked: .gitignore
Untracked: @
Untracked: GEO_brimittleman/
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/totSpecInNuclear.Rmd
Untracked: analysis/totSpecIncludenotTested.Rmd
Untracked: analysis/totalspec.Rmd
Untracked: apaQTL.Rproj
Untracked: checksumsfastq.txt.gz
Untracked: code/.NascentRNAdtPlotFirstintronicPAS.sh.swp
Untracked: code/._ApaQTL_nominalNonnorm.sh
Untracked: code/._BothFracDTPlotGeneRegions.sh
Untracked: code/._BothFracDTPlotGeneRegions_normalized.sh
Untracked: code/._DistPAS2Sig_RandomIntron.py
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/._NuclearandRNA5samp_dtplots.sh
Untracked: code/._PTTfacetboxplots.R
Untracked: code/._PrematureQTLNominal.sh
Untracked: code/._PrematureQTLPermuted.sh
Untracked: code/._QTL2bed.py
Untracked: code/._QTL2bed_withstrand.py
Untracked: code/._RNAbam2bw.sh
Untracked: code/._RNAseqDTplot.sh
Untracked: code/._RunRes2PAS.sh
Untracked: code/._SAF215upbed.py
Untracked: code/._SnakefilePAS
Untracked: code/._SnakefilefiltPAS
Untracked: code/._TESplots100bp.sh
Untracked: code/._TESplots150bp.sh
Untracked: code/._TESplots200bp.sh
Untracked: code/._TotalPAS_5perc.bed.py
Untracked: code/._Untitled
Untracked: code/._ZipandTabPheno.sh
Untracked: code/._aAPAqtl_nominal39ind.sh
Untracked: code/._allNucSpecQTLine.py
Untracked: code/._allNucSpecfromNonNorm.py
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_nominalInclusive.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/._fix_randomIntron.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/._mergeAnnotations.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/._nucspecnucPASine.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_dist2sig_randomintron.sh
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/._specAPAinE.py
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_inclusive.err
Untracked: code/APAqtl_nominal_inclusive.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/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/DistPAS2Sig_RandomIntron.py
Untracked: code/EandPqtl.err
Untracked: code/EandPqtl.out
Untracked: code/EncodeRNADTPlotGeneRegions.err
Untracked: code/EncodeRNADTPlotGeneRegions.out
Untracked: code/FC_NucintronPASupandDown.err
Untracked: code/FC_NucintronPASupandDown.out
Untracked: code/FC_UTR.err
Untracked: code/FC_UTR.out
Untracked: code/FC_intronPASupandDown.err
Untracked: code/FC_intronPASupandDown.out
Untracked: code/FC_nascent.err
Untracked: code/FC_nascentout
Untracked: code/FC_newPAS_olddata.err
Untracked: code/FC_newPAS_olddata.out
Untracked: code/HmmPermute.p
Untracked: code/IntronicPASDT.err
Untracked: code/IntronicPASDT.out
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/Nuclear_example.err
Untracked: code/Nuclear_example.out
Untracked: code/NuclearandRNA5samp_dtplots.sh
Untracked: code/NuclearandRNAFracDTPlotGeneRegions.err
Untracked: code/NuclearandRNAFracDTPlotGeneRegions.out
Untracked: code/PACbioDT.err
Untracked: code/PACbioDT.out
Untracked: code/PACbioDTitronic.err
Untracked: code/PACbioDTitronic.out
Untracked: code/Prematureqtl_nominal.err
Untracked: code/Prematureqtl_nominal.out
Untracked: code/Prematureqtl_permuted.err
Untracked: code/Prematureqtl_permuted.out
Untracked: code/README.md
Untracked: code/RNABam2BW.err
Untracked: code/RNABam2BW.out
Untracked: code/RNAseqDTPlotGeneRegions.err
Untracked: code/RNAseqDTPlotGeneRegions.out
Untracked: code/Rplots.pdf
Untracked: code/TESplots100bp.err
Untracked: code/TESplots100bp.out
Untracked: code/TESplots150bp.err
Untracked: code/TESplots150bp.out
Untracked: code/TESplots200bp.err
Untracked: code/TESplots200bp.out
Untracked: code/Total_example.err
Untracked: code/Total_example.out
Untracked: code/Untitled
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/annotatedPASregion.err
Untracked: code/annotatedPASregion.out
Untracked: code/apaQTL_nominalInclusive.sh
Untracked: code/assignPeak2Intronicregion.err
Untracked: code/assignPeak2Intronicregion.out
Untracked: code/assigntotPeak2Intronicregion.err
Untracked: code/assigntotPeak2Intronicregion.out
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/bothFrac_FC.err
Untracked: code/bothFrac_FC.out
Untracked: code/callSHscripts.txt
Untracked: code/closestannotated.err
Untracked: code/closestannotated.out
Untracked: code/closestannotatedbyfrac.err
Untracked: code/closestannotatedbyfrac.out
Untracked: code/dag.pdf
Untracked: code/dagPAS.pdf
Untracked: code/dagfiltPAS.pdf
Untracked: code/fixExandUnexeQTL
Untracked: code/fix_randomIntron.py
Untracked: code/genotypesYRI.gen.proc.keep.vcf.log
Untracked: code/genotypesYRI.gen.proc.keep.vcf.recode.vcf
Untracked: code/getseq100up.err
Untracked: code/getseq100up.out
Untracked: code/grouptranscripts.err
Untracked: code/grouptranscripts.out
Untracked: code/intersectPAS_ssSNPS.err
Untracked: code/intersectPAS_ssSNPS.out
Untracked: code/intersectVCFPAS.err
Untracked: code/intersectVCFPAS.out
Untracked: code/log/
Untracked: code/merge53PRIMEbam.err
Untracked: code/merge53PRIMEbam.out
Untracked: code/merge53RNAbam.err
Untracked: code/merge53prime.sh
Untracked: code/merge5RNABam.err
Untracked: code/merge5RNABam.out
Untracked: code/merge5RNAbam.out
Untracked: code/merge5RNAbam.sh
Untracked: code/mergeAnno.err
Untracked: code/mergeAnno.out
Untracked: code/mergeBWnorm.err
Untracked: code/mergeBWnorm.out
Untracked: code/mergeBamNacent.err
Untracked: code/mergeBamNacent.out
Untracked: code/mergeRNAbam.err
Untracked: code/mergeRNAbam.out
Untracked: code/mnaseDTPlot1stintron.err
Untracked: code/mnaseDTPlot1stintron.out
Untracked: code/mnaseDTPlot4thintron.err
Untracked: code/mnaseDTPlot4thintron.out
Untracked: code/netDTPlot4thintron.out
Untracked: code/netseqFC.err
Untracked: code/netseqFC.out
Untracked: code/neyDTPlot4thintron.err
Untracked: code/nucspecinE.py
Untracked: code/plink.log
Untracked: code/prxySNP.err
Untracked: code/prxySNP.out
Untracked: code/pttFacetBoxplots.err
Untracked: code/pttFacetBoxplots.out
Untracked: code/qtlFacetBoxplots.err
Untracked: code/qtlFacetBoxplots.out
Untracked: code/rLD_vcftools.hap.err
Untracked: code/riboqtl.err
Untracked: code/riboqtl.out
Untracked: code/runBestBamID.err
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/runHMMpermuteeQTLs.err
Untracked: code/runHMMpermuteeQTLs.out
Untracked: code/runMakeEmpiricaleQTLs.err
Untracked: code/runMakeEmpiricaleQTLs.out
Untracked: code/runMakeEmpiricaleQTLsunex.err
Untracked: code/runMakeEmpiricaleQTLsunex.out
Untracked: code/run_DistPAS2Sig.err
Untracked: code/run_DistPAS2Sig.out
Untracked: code/run_DistPAS2Sig_intron.err
Untracked: code/run_DistPAS2Sig_intron.out
Untracked: code/run_bam2bw.err
Untracked: code/run_bam2bw.out
Untracked: code/run_bam2bwexta.err
Untracked: code/run_bam2bwexta.out
Untracked: code/run_dist2sig_randomintron.sh
Untracked: code/run_getAPAfromanyeQTL.err
Untracked: code/run_getAPAfromanyeQTL.out
Untracked: code/run_getApaPval4eQTLs.err
Untracked: code/run_getApaPval4eQTLs.out
Untracked: code/run_getApaPval4eQTLsunexplained.err
Untracked: code/run_getApaPval4eQTLsunexplained.out
Untracked: code/run_leafcutter_ds.err
Untracked: code/run_leafcutter_ds.out
Untracked: code/run_sepgenobychrom.err
Untracked: code/run_sepgenobychrom.out
Untracked: code/run_sepusage.err
Untracked: code/run_sepusage.out
Untracked: code/run_verifybam.err
Untracked: code/run_verifybam.out
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/runprxySNP.err
Untracked: code/runprxySNP.out
Untracked: code/runres2pas.err
Untracked: code/runres2pas.out
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/specAPAinE.py
Untracked: code/subsetvcf_SS.err
Untracked: code/subsetvcf_SS.out
Untracked: code/subsetvcf_noSS.err
Untracked: code/subsetvcf_noSS.out
Untracked: code/subsetvcf_pas.err
Untracked: code/subsetvcf_pas.out
Untracked: code/subsetvcf_perm.err
Untracked: code/subsetvcf_perm.out
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/tabixSNPs.err
Untracked: code/tabixSNPs.out
Untracked: code/test_verifybam.err
Untracked: code/test_verifybam.out
Untracked: code/vcf_keepsnps.err
Untracked: code/vcf_keepsnps.out
Untracked: code/wrap_verifybam.err
Untracked: code/wrap_verifybam.out
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/ExpressionIndependentapaQTLs.txt
Untracked: data/FiveMergedBW/
Untracked: data/FiveMergedBam/
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_inclusive/
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/apaQTLNominal_inclusive/
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/phenotype_inclusivePAS/
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/PAS_graphs.Rmd/._figure1Both-1.pdf
Untracked: docs/figure/PAS_graphs.Rmd/._figure1CUTR-1.pdf
Untracked: docs/figure/PAS_graphs.Rmd/._figure1quant-1.pdf
Untracked: docs/figure/PAS_graphs_total.Rmd/._.DS_Store
Untracked: docs/figure/checkfirstintron.Rmd/
Untracked: docs/figure/choosePCs.Rmd/._.DS_Store
Untracked: docs/figure/exvunexpeQTL.Rmd/._.DS_Store
Untracked: docs/figure/snpinSS.Rmd/._.DS_Store
Untracked: nohup.out
Untracked: output/._.DS_Store
Untracked: output/._meanCorrelationPhenotypes.svg
Untracked: output/dtPlots/
Untracked: output/fastqc/
Untracked: output/meanCorrelationPhenotypes.svg
Untracked: run_verifybam517N.err
Untracked: run_verifybam517N.out
Unstaged changes:
Modified: analysis/NuclearSpecIncludeNotTested.Rmd
Modified: analysis/PASdescriptiveplots.Rmd
Modified: analysis/Readdistagainstfeatures.Rmd
Modified: analysis/nucSpecinEQTLs.Rmd
Modified: analysis/overlapapaqtlsandeqtls.Rmd
Modified: analysis/pQTLexampleplot.Rmd
Modified: analysis/propeQTLs_explained.Rmd
Modified: analysis/version15bpfilter.Rmd
Modified: code/DistPAS2Sig.py
Modified: code/apaQTLsnake.err
Deleted: code/test.txt
Deleted: reads_graphs.Rmd
Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
These are the previous versions of the R Markdown and HTML files. If you’ve configured a remote Git repository (see ?wflow_git_remote
), click on the hyperlinks in the table below to view them.
File | Version | Author | Date | Message |
---|---|---|---|---|
Rmd | d72c604 | brimittleman | 2019-11-08 | add first intron analysis |
html | e22e31c | brimittleman | 2019-06-20 | Build site. |
Rmd | b2def08 | brimittleman | 2019-06-20 | first intron in sites with ss |
html | 5a02775 | brimittleman | 2019-06-18 | Build site. |
Rmd | 078b340 | brimittleman | 2019-06-18 | add first intron length |
html | b3328b6 | brimittleman | 2019-06-18 | Build site. |
Rmd | 01bc8aa | brimittleman | 2019-06-18 | add verify first inton res |
In the previous analysis I saw that most of my intronic pas are in the first intron and skew toward the beginning of long introns. I will further explore this result here.
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(cowplot)
Attaching package: 'cowplot'
The following object is masked from 'package:ggplot2':
ggsave
library(workflowr)
This is workflowr version 1.4.0
Run ?workflowr for help getting started
These are the nuclear intronic PAS
pas2intron=read.table("../data/intron_analysis/IntronPeaksontoIntrons.bed",col.names = c("intronCHR", "intronStart", "intronEnd", "gene", "score", "strand", "peakCHR", "peakStart", "peakEnd", "PeakID", "meanUsage", "peakStrand"),stringsAsFactors = F) %>% mutate(PASloc=ifelse(strand=="+", peakEnd, peakStart)) %>% dplyr::select(intronStart, intronEnd, gene, strand, PeakID, PASloc ,meanUsage) %>% mutate(intronLength=intronEnd-intronStart , distance2PAS= ifelse(strand=="+", PASloc-intronStart, intronEnd-PASloc), propIntron=distance2PAS/intronLength) %>% mutate(LengthCat=ifelse(intronLength<=3929, "first", ifelse(intronLength>3929 &intronLength<=9220, "second", ifelse(intronLength>9220 &intronLength<=24094, "third", "fourth"))))
pas2intron$LengthCat <- factor(pas2intron$LengthCat, levels=c("first", "second", "third", "fourth"))
I want to plot the absolute distance rather than the standardized distance to the 5’ ss.
ggplot(pas2intron,aes(x=distance2PAS, fill=LengthCat)) + geom_histogram(bins=100) + facet_grid(~LengthCat) + xlim(0,5000)
Warning: Removed 5347 rows containing non-finite values (stat_bin).
Warning: Removed 8 rows containing missing values (geom_bar).
Version | Author | Date |
---|---|---|
b3328b6 | brimittleman | 2019-06-18 |
ggplot(pas2intron,aes(x=distance2PAS, fill=LengthCat)) + facet_grid(~LengthCat) + xlim(0,5000) + stat_ecdf(aes(col=LengthCat))
Warning: Removed 5347 rows containing non-finite values (stat_ecdf).
Version | Author | Date |
---|---|---|
b3328b6 | brimittleman | 2019-06-18 |
This is not the correct analysis. I need to actually look at which intron from all of them.
this is the file I created to get the introns. I need to remove genes with only 1 introm.
introns=read.table("/project2/gilad/briana/apaQTL/data/intron_analysis/transcriptsMinusExons.sort.bed",stringsAsFactors = F, col.names = c("chrom", "intronStart", "intronEnd", "gene", "score", "strand")) %>% group_by(gene) %>% filter(!grepl("hap",chrom)) %>% mutate(Intronid=ifelse(strand=="+", 1:n(),n():1), nintron=n()) %>% filter(nintron>2)
Join with PAS:
pas2intron_intron=pas2intron %>% inner_join(introns, by=c("intronStart","intronEnd","gene", "strand" ))
pas2intron_intron$Intronid=as.factor(pas2intron_intron$Intronid)
write.table(pas2intron_intron, "../data/intron_analysis/NuclearIntronPASwithWhichintron.txt", col.names = T, row.names = F, quote = F, sep="\t")
ggplot(pas2intron_intron,aes(x=Intronid)) + geom_bar(stat="count") + labs(title="intron ID for nuclear intronic pas", x="intron ID")
Version | Author | Date |
---|---|---|
b3328b6 | brimittleman | 2019-06-18 |
summary(pas2intron_intron$Intronid)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
2775 1840 1377 1110 828 677 547 439 380 347 259 221 181 164 137
16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
100 99 90 75 57 44 54 49 56 36 28 28 17 13 10
31 32 33 34 35 36 37 38 39 40 41 42 43 44 45
6 10 9 3 5 6 3 7 8 11 10 7 5 9 6
46 47 48 49 50 52 55 57 58 59 60 63 64 69 72
3 2 1 1 2 2 1 3 6 3 1 1 3 1 2
74 76 77 79 84 85 90 94 96 164 165
2 1 2 1 1 1 1 2 1 1 2
I want to see if the usage is the same over this:
pas2intron_intron_usagecat= pas2intron_intron %>% mutate(UsageCat=ifelse(meanUsage<=.1, "<.1", ifelse(meanUsage>.1 &meanUsage<=.2, "<.2", ifelse(meanUsage>.2 &meanUsage<=.3, "<.3", ">.3"))))
pas2intron_intron_usagecat$Intronid=as.numeric(as.character(pas2intron_intron_usagecat$Intronid))
ggplot(pas2intron_intron_usagecat,aes(x=Intronid, fill=UsageCat)) + geom_bar(stat="count") + labs(title="intron ID for nuclear intronic pas", x="intron ID") + facet_grid(~UsageCat)+ xlim(0,10)
Warning: Removed 1870 rows containing non-finite values (stat_count).
Warning: Removed 4 rows containing missing values (geom_bar).
Version | Author | Date |
---|---|---|
b3328b6 | brimittleman | 2019-06-18 |
Maybe by the number of introns?
summary(pas2intron_intron_usagecat$nintron)
Min. 1st Qu. Median Mean 3rd Qu. Max.
3.0 6.0 11.0 14.2 18.0 171.0
pas2intron_intron_usagecat_introncat= pas2intron_intron_usagecat %>% mutate(IntronCat=ifelse(nintron<=6, "first (<6)", ifelse(nintron>6 &nintron<=11, "second (6-11)", ifelse(nintron>11 &nintron<=18, "third (11-18)", "fourth (>18)"))))
pas2intron_intron_usagecat_introncat$IntronCat <- factor(pas2intron_intron_usagecat_introncat$IntronCat, levels=c("first (<6)", "second (6-11)", "third (11-18)", "fourth (>18)"))
ggplot(pas2intron_intron_usagecat_introncat,aes(x=Intronid, fill=IntronCat)) + geom_bar(stat="count") + labs(title="intron ID for nuclear intronic pas", x="intron ID") + facet_grid(~IntronCat) + xlim(0,10)
Warning: Removed 1870 rows containing non-finite values (stat_count).
Warning: Removed 3 rows containing missing values (geom_bar).
Version | Author | Date |
---|---|---|
b3328b6 | brimittleman | 2019-06-18 |
nuclear_cdf=ggplot(pas2intron_intron_usagecat_introncat,aes(x=Intronid, fill=IntronCat)) + stat_ecdf(aes(col=IntronCat)) + labs(title="intron ID for Nuclear intronic pas", x="intron ID") + xlim(0,10)+ geom_vline(xintercept = 2)
Number of introns in each and normalize by average intron size.
pas2intron_intron_grouped=pas2intron_intron %>% group_by(Intronid) %>% summarise(nBin=n(), meanSize=mean(intronLength)) %>% mutate(normNBin=nBin/meanSize)
pas2intron_intron_grouped$Intronid=as.integer(as.character(pas2intron_intron_grouped$Intronid))
ggplot(pas2intron_intron_grouped, aes(x=Intronid, y=normNBin)) +geom_bar(stat="identity") + labs(title="PAS by Intron", y="normalized number in intron category", x="intron category")
#zoom in 1-10
pas2intron_intron_grouped_small=pas2intron_intron_grouped %>% filter(Intronid <=10)
ggplot(pas2intron_intron_grouped_small, aes(x=Intronid, y=normNBin)) +geom_bar(stat="identity") + labs(title="PAS by Intron", y="normalized number in intron category", x="intron category")
pas2intronTot=read.table("../data/intron_analysis/TotalIntronPeaksontoIntrons.bed",col.names = c("intronCHR", "intronStart", "intronEnd", "gene", "score", "strand", "peakCHR", "peakStart", "peakEnd", "PeakID", "meanUsage", "peakStrand"),stringsAsFactors = F) %>% mutate(PASloc=ifelse(strand=="+", peakEnd, peakStart)) %>% dplyr::select(intronStart, intronEnd, gene, strand, PeakID, PASloc ,meanUsage) %>% mutate(intronLength=intronEnd-intronStart , distance2PAS= ifelse(strand=="+", PASloc-intronStart, intronEnd-PASloc), propIntron=distance2PAS/intronLength) %>% mutate(LengthCat=ifelse(intronLength<=3785, "first", ifelse(intronLength>3785 &intronLength<=8872, "second", ifelse(intronLength>8872 &intronLength<=22928, "third", "fourth"))))
pas2intronTot$LengthCat <- factor(pas2intronTot$LengthCat, levels=c("first", "second", "third", "fourth"))
pas2intronTot_intron=pas2intronTot %>% inner_join(introns, by=c("intronStart","intronEnd","gene", "strand" ))
write.table(pas2intronTot_intron, "../data/intron_analysis/TotalIntronPASwithWhichintron.txt", col.names = T, row.names = F, quote = F, sep="\t")
summary(pas2intronTot_intron$nintron)
Min. 1st Qu. Median Mean 3rd Qu. Max.
3.00 6.00 11.00 14.66 18.00 171.00
pas2intronTot_intron_usagecat_introncat= pas2intronTot_intron %>% mutate(IntronCat=ifelse(nintron<=6, "first (<6)", ifelse(nintron>6 &nintron<=11, "second (6-11)", ifelse(nintron>11 &nintron<=18, "third (11-18)", "fourth (>18)"))))
ggplot(pas2intronTot_intron_usagecat_introncat,aes(x=Intronid, fill=IntronCat)) + geom_bar(stat="count") + labs(title="intron ID for Total intronic pas", x="intron ID") + facet_grid(~IntronCat) + xlim(0,10)
Warning: Removed 1219 rows containing non-finite values (stat_count).
Warning: Removed 3 rows containing missing values (geom_bar).
totalcdf=ggplot(pas2intronTot_intron_usagecat_introncat,aes(x=Intronid, fill=IntronCat)) + stat_ecdf(aes(col=IntronCat)) + labs(title="intron ID for Total intronic pas", x="intron ID") + xlim(0,10) + geom_vline(xintercept = 2)
Plot both:
pas2intronTot_intron_usagecat_introncat_frac=pas2intronTot_intron_usagecat_introncat %>% mutate(fraction="Total") %>% select(Intronid,IntronCat,fraction)
pas2intron_intron_usagecat_introncat_frac=pas2intron_intron_usagecat_introncat%>% mutate(fraction="Nuclear") %>% select(Intronid,IntronCat,fraction)
intronidboth=bind_rows(pas2intronTot_intron_usagecat_introncat_frac,pas2intron_intron_usagecat_introncat_frac)
Warning in bind_rows_(x, .id): binding character and factor vector,
coercing into character vector
ggplot(intronidboth,aes(x=Intronid)) + stat_ecdf(aes(col=fraction)) + labs(title="intron ID for intronic pas", x="intron ID") + xlim(0,10) + facet_grid(~IntronCat)
Warning: Removed 3089 rows containing non-finite values (stat_ecdf).
Version | Author | Date |
---|---|---|
b3328b6 | brimittleman | 2019-06-18 |
plot_grid(nuclear_cdf,totalcdf)
Warning: Removed 1870 rows containing non-finite values (stat_ecdf).
Warning: Removed 1219 rows containing non-finite values (stat_ecdf).
Usage in both fractions.
TotalIntronicUsage=pas2intronTot_intron_usagecat_introncat %>% mutate(fraction="Total") %>% select(meanUsage,fraction)
NuclearIntronicUsage=pas2intron_intron_usagecat_introncat%>% mutate(fraction="Nuclear") %>% select(meanUsage,fraction)
bothIntronicUsage=bind_rows(TotalIntronicUsage,NuclearIntronicUsage)
ggplot(bothIntronicUsage, aes(x=meanUsage)) + stat_ecdf(aes(col=fraction))
Final plot:
first intron (conditioned on the intron being > 2KB) shows no signal (plotting the first 2kb only)
firstintron_nuclear=pas2intron_intron_usagecat_introncat %>% filter(Intronid==1,intronLength>2000)
firstintron_total=pas2intronTot_intron_usagecat_introncat %>% filter(Intronid==1,intronLength>2000)
ggplot(firstintron_nuclear,aes(x=distance2PAS, fill=LengthCat)) + geom_histogram(bins=50) +xlim(0,2000) + facet_grid(~LengthCat)+ labs(title="Nuclear intronic PAS in first intron (3025)")
Warning: Removed 1970 rows containing non-finite values (stat_bin).
Warning: Removed 8 rows containing missing values (geom_bar).
Version | Author | Date |
---|---|---|
5a02775 | brimittleman | 2019-06-18 |
ggplot(firstintron_total,aes(x=distance2PAS, fill=LengthCat)) + geom_histogram(bins=50) +xlim(0,2000) + facet_grid(~LengthCat) + labs(title="Total intronic PAS in first intron (1804)")
Warning: Removed 1069 rows containing non-finite values (stat_bin).
Warning: Removed 8 rows containing missing values (geom_bar).
sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)
Matrix products: default
BLAS/LAPACK: /software/openblas-0.2.19-el7-x86_64/lib/libopenblas_haswellp-r0.2.19.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] workflowr_1.4.0 cowplot_0.9.4 forcats_0.3.0 stringr_1.3.1
[5] dplyr_0.8.0.1 purrr_0.3.2 readr_1.3.1 tidyr_0.8.3
[9] tibble_2.1.1 ggplot2_3.1.1 tidyverse_1.2.1
loaded via a namespace (and not attached):
[1] Rcpp_1.0.2 cellranger_1.1.0 plyr_1.8.4 compiler_3.5.1
[5] pillar_1.3.1 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 reshape2_1.4.3
[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