Last updated: 2020-04-10

Checks: 7 0

Knit directory: Comparative_APA/analysis/

This reproducible R Markdown analysis was created with workflowr (version 1.6.0). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.

R Markdown file: up-to-date

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

Environment: empty

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

Seed: set.seed(20190902)

The command set.seed(20190902) 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: fbabfb7

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:    code/chimp_log/
    Ignored:    code/human_log/
    Ignored:    data/.DS_Store
    Ignored:    data/TrialFiltersMeta.txt.sb-9845453e-R58Y0Q/
    Ignored:    data/mediation_prot/
    Ignored:    data/metadata_HCpanel.txt.sb-284518db-RGf0kd/
    Ignored:    data/metadata_HCpanel.txt.sb-a5794dd2-i594qs/
    Ignored:    output/.DS_Store

Untracked files:
    Untracked:  ._.DS_Store
    Untracked:  Chimp/
    Untracked:  Human/
    Untracked:  analysis/CrossChimpThreePrime.Rmd
    Untracked:  analysis/DiffTransProtvsExpression.Rmd
    Untracked:  analysis/DiffUsedUTR.Rmd
    Untracked:  analysis/GvizPlots.Rmd
    Untracked:  analysis/HandC.TvN
    Untracked:  analysis/PhenotypeOverlap10.Rmd
    Untracked:  analysis/annotationBias.Rmd
    Untracked:  analysis/assessReadQual.Rmd
    Untracked:  analysis/diffExpressionPantro6.Rmd
    Untracked:  code/._AlignmentScores.sh
    Untracked:  code/._BothFCMM.sh
    Untracked:  code/._BothFCMMPrim.sh
    Untracked:  code/._BothFCnewOInclusive.sh
    Untracked:  code/._ChimpStarMM2.sh
    Untracked:  code/._ClassifyLeafviz.sh
    Untracked:  code/._ClosestorthoEx.sh
    Untracked:  code/._Config_chimp.yaml
    Untracked:  code/._Config_chimp_full.yaml
    Untracked:  code/._Config_human.yaml
    Untracked:  code/._ConvertJunc2Bed.sh
    Untracked:  code/._CountNucleotides.py
    Untracked:  code/._CrossMapChimpRNA.sh
    Untracked:  code/._CrossMapThreeprime.sh
    Untracked:  code/._DiffSplice.sh
    Untracked:  code/._DiffSplicePlots.sh
    Untracked:  code/._DiffSplicePlots_gencode.sh
    Untracked:  code/._DiffSplice_gencode.sh
    Untracked:  code/._DiffSplice_removebad.sh
    Untracked:  code/._Filter255MM.sh
    Untracked:  code/._FilterPrimSec.sh
    Untracked:  code/._FindIntronForDomPAS.sh
    Untracked:  code/._FindIntronForDomPAS_DF.sh
    Untracked:  code/._GetMAPQscore.py
    Untracked:  code/._GetSecondaryMap.py
    Untracked:  code/._Lift5perPAS.sh
    Untracked:  code/._LiftFinalChimpJunc2Human.sh
    Untracked:  code/._LiftOrthoPAS2chimp.sh
    Untracked:  code/._MapBadSamples.sh
    Untracked:  code/._MismatchNumbers.sh
    Untracked:  code/._PAS_ATTAAA.sh
    Untracked:  code/._PAS_ATTAAA_df.sh
    Untracked:  code/._PAS_seqExpanded.sh
    Untracked:  code/._PASsequences.sh
    Untracked:  code/._PASsequences_DF.sh
    Untracked:  code/._PlotNuclearUsagebySpecies.R
    Untracked:  code/._PlotNuclearUsagebySpecies_DF.R
    Untracked:  code/._QuantMergedClusters.sh
    Untracked:  code/._RNATranscriptDTplot.sh
    Untracked:  code/._ReverseLiftFilter.R
    Untracked:  code/._RunFixLeafCluster.sh
    Untracked:  code/._RunNegMCMediation.sh
    Untracked:  code/._RunNegMCMediationDF.sh
    Untracked:  code/._RunPosMCMediationDF.err
    Untracked:  code/._RunPosMCMediationDF.sh
    Untracked:  code/._SAF2Bed.py
    Untracked:  code/._Snakefile
    Untracked:  code/._SnakefilePAS
    Untracked:  code/._SnakefilePASfilt
    Untracked:  code/._SortIndexBadSamples.sh
    Untracked:  code/._StarMM2.sh
    Untracked:  code/._TestFC.sh
    Untracked:  code/._assignPeak2Intronicregion
    Untracked:  code/._assignPeak2Intronicregion.sh
    Untracked:  code/._bed215upbed.py
    Untracked:  code/._bed2Bedbothstrand.py
    Untracked:  code/._bed2SAF_gen.py
    Untracked:  code/._buildIndecpantro5
    Untracked:  code/._buildIndecpantro5.sh
    Untracked:  code/._buildLeafviz.sh
    Untracked:  code/._buildLeafviz_leadAnno.sh
    Untracked:  code/._buildStarIndex.sh
    Untracked:  code/._chimpChromprder.sh
    Untracked:  code/._chimpMultiCov.sh
    Untracked:  code/._chimpMultiCov255.sh
    Untracked:  code/._chimpMultiCovInclusive.sh
    Untracked:  code/._chooseSignalSite.py
    Untracked:  code/._cleanbed2saf.py
    Untracked:  code/._cluster.json
    Untracked:  code/._cluster2bed.py
    Untracked:  code/._clusterLiftReverse.sh
    Untracked:  code/._clusterLiftReverse_removebad.sh
    Untracked:  code/._clusterLiftprimary.sh
    Untracked:  code/._clusterLiftprimary_removebad.sh
    Untracked:  code/._converBam2Junc.sh
    Untracked:  code/._converBam2Junc_removeBad.sh
    Untracked:  code/._extraSnakefiltpas
    Untracked:  code/._extractPhyloReg.py
    Untracked:  code/._extractPhyloRegGene.py
    Untracked:  code/._extractPhylopGeneral.ph
    Untracked:  code/._extractPhylopGeneral.py
    Untracked:  code/._extractPhylopReg200down.py
    Untracked:  code/._extractPhylopReg200up.py
    Untracked:  code/._filter5percPAS.py
    Untracked:  code/._filterNumChroms.py
    Untracked:  code/._filterPASforMP.py
    Untracked:  code/._filterPostLift.py
    Untracked:  code/._filterPrimaryread.py
    Untracked:  code/._filterSecondaryread.py
    Untracked:  code/._fixExonFC.py
    Untracked:  code/._fixFCheadforExp.py
    Untracked:  code/._fixLeafCluster.py
    Untracked:  code/._fixLiftedJunc.py
    Untracked:  code/._fixUTRexonanno.py
    Untracked:  code/._formathg38Anno.py
    Untracked:  code/._formatpantro6Anno.py
    Untracked:  code/._getRNAseqMapStats.sh
    Untracked:  code/._hg19MapStats.sh
    Untracked:  code/._humanChromorder.sh
    Untracked:  code/._humanMultiCov.sh
    Untracked:  code/._humanMultiCov255.sh
    Untracked:  code/._humanMultiCov_inclusive.sh
    Untracked:  code/._intersectLiftedPAS.sh
    Untracked:  code/._liftJunctionFiles.sh
    Untracked:  code/._liftPAS19to38.sh
    Untracked:  code/._liftedchimpJunc2human.sh
    Untracked:  code/._makeNuclearDapaplots.sh
    Untracked:  code/._makeNuclearDapaplots_DF.sh
    Untracked:  code/._makeSamplyGroupsHuman_TvN.py
    Untracked:  code/._mapRNAseqhg19.sh
    Untracked:  code/._mapRNAseqhg19_newPipeline.sh
    Untracked:  code/._maphg19.sh
    Untracked:  code/._maphg19_subjunc.sh
    Untracked:  code/._mediation_test.R
    Untracked:  code/._mergeChimp3prime_inhg38.sh
    Untracked:  code/._mergeandBWRNAseq.sh
    Untracked:  code/._mergedBam2BW.sh
    Untracked:  code/._nameClusters.py
    Untracked:  code/._negativeMediation_montecarlo.R
    Untracked:  code/._negativeMediation_montecarloDF.R
    Untracked:  code/._numMultimap.py
    Untracked:  code/._overlapMMandOrthoexon.sh
    Untracked:  code/._overlapPASandOrthoexon.sh
    Untracked:  code/._overlapapaQTLPAS.sh
    Untracked:  code/._parseHg38.py
    Untracked:  code/._postiveMediation_montecarlo_DF.R
    Untracked:  code/._prepareCleanLiftedFC_5perc4LC.py
    Untracked:  code/._prepareLeafvizAnno.sh
    Untracked:  code/._preparePAS4lift.py
    Untracked:  code/._primaryLift.sh
    Untracked:  code/._processhg38exons.py
    Untracked:  code/._quantJunc.sh
    Untracked:  code/._quantJunc_TEST.sh
    Untracked:  code/._quantJunc_removeBad.sh
    Untracked:  code/._quantLiftedPASPrimary.sh
    Untracked:  code/._quantMerged_seperatly.sh
    Untracked:  code/._recLiftchim2human.sh
    Untracked:  code/._revLiftPAShg38to19.sh
    Untracked:  code/._reverseLift.sh
    Untracked:  code/._runCheckReverseLift.sh
    Untracked:  code/._runChimpDiffIso.sh
    Untracked:  code/._runCountNucleotides.sh
    Untracked:  code/._runFilterNumChroms.sh
    Untracked:  code/._runHumanDiffIso.sh
    Untracked:  code/._runNuclearDiffIso_DF.sh
    Untracked:  code/._runNuclearDifffIso.sh
    Untracked:  code/._runTotalDiffIso.sh
    Untracked:  code/._run_chimpverifybam.sh
    Untracked:  code/._run_verifyBam.sh
    Untracked:  code/._snakemake.batch
    Untracked:  code/._snakemakePAS.batch
    Untracked:  code/._snakemakePASchimp.batch
    Untracked:  code/._snakemakePAShuman.batch
    Untracked:  code/._snakemake_chimp.batch
    Untracked:  code/._snakemake_human.batch
    Untracked:  code/._snakemakefiltPAS.batch
    Untracked:  code/._snakemakefiltPAS_chimp
    Untracked:  code/._snakemakefiltPAS_chimp.sh
    Untracked:  code/._snakemakefiltPAS_human.sh
    Untracked:  code/._spliceSite2Fasta.py
    Untracked:  code/._submit-snakemake-chimp.sh
    Untracked:  code/._submit-snakemake-human.sh
    Untracked:  code/._submit-snakemakePAS-chimp.sh
    Untracked:  code/._submit-snakemakePAS-human.sh
    Untracked:  code/._submit-snakemakefiltPAS-chimp.sh
    Untracked:  code/._submit-snakemakefiltPAS-human.sh
    Untracked:  code/._subset_diffisopheno_Nuclear_HvC.py
    Untracked:  code/._subset_diffisopheno_Nuclear_HvC_DF.py
    Untracked:  code/._subset_diffisopheno_Total_HvC.py
    Untracked:  code/._threeprimeOrthoFC.sh
    Untracked:  code/._transcriptDTplotsNuclear.sh
    Untracked:  code/._verifyBam4973.sh
    Untracked:  code/._verifyBam4973inHuman.sh
    Untracked:  code/._wrap_chimpverifybam.sh
    Untracked:  code/._wrap_verifyBam.sh
    Untracked:  code/._writeMergecode.py
    Untracked:  code/.snakemake/
    Untracked:  code/ALLPAS_sequenceDF.err
    Untracked:  code/ALLPAS_sequenceDF.out
    Untracked:  code/AlignmentScores.err
    Untracked:  code/AlignmentScores.out
    Untracked:  code/AlignmentScores.sh
    Untracked:  code/BothFCMM.err
    Untracked:  code/BothFCMM.out
    Untracked:  code/BothFCMM.sh
    Untracked:  code/BothFCMMPrim.err
    Untracked:  code/BothFCMMPrim.out
    Untracked:  code/BothFCMMPrim.sh
    Untracked:  code/BothFCnewOInclusive.sh
    Untracked:  code/BothFCnewOInclusive.sh.err
    Untracked:  code/BothFCnewOInclusive.sh.out
    Untracked:  code/ChimpStarMM2.err
    Untracked:  code/ChimpStarMM2.out
    Untracked:  code/ChimpStarMM2.sh
    Untracked:  code/ClassifyLeafviz.sh
    Untracked:  code/ClosestorthoEx.err
    Untracked:  code/ClosestorthoEx.out
    Untracked:  code/ClosestorthoEx.sh
    Untracked:  code/Config_chimp.yaml
    Untracked:  code/Config_chimp_full.yaml
    Untracked:  code/Config_human.yaml
    Untracked:  code/ConvertJunc2Bed.err
    Untracked:  code/ConvertJunc2Bed.out
    Untracked:  code/ConvertJunc2Bed.sh
    Untracked:  code/CountNucleotides.py
    Untracked:  code/CrossMapChimpRNA.sh
    Untracked:  code/CrossMapThreeprime.sh
    Untracked:  code/CrossmapChimp3prime.err
    Untracked:  code/CrossmapChimp3prime.out
    Untracked:  code/CrossmapChimpRNA.err
    Untracked:  code/CrossmapChimpRNA.out
    Untracked:  code/DiffSplice.err
    Untracked:  code/DiffSplice.out
    Untracked:  code/DiffSplice.sh
    Untracked:  code/DiffSplicePlots.err
    Untracked:  code/DiffSplicePlots.out
    Untracked:  code/DiffSplicePlots.sh
    Untracked:  code/DiffSplicePlots_gencode.sh
    Untracked:  code/DiffSplice_gencode.sh
    Untracked:  code/DiffSplice_removebad.err
    Untracked:  code/DiffSplice_removebad.out
    Untracked:  code/DiffSplice_removebad.sh
    Untracked:  code/Filter255.err
    Untracked:  code/Filter255.out
    Untracked:  code/Filter255MM.sh
    Untracked:  code/FilterPrimSec.err
    Untracked:  code/FilterPrimSec.out
    Untracked:  code/FilterPrimSec.sh
    Untracked:  code/FilterReverseLift.err
    Untracked:  code/FilterReverseLift.out
    Untracked:  code/FindIntronForDomPAS.err
    Untracked:  code/FindIntronForDomPAS.out
    Untracked:  code/FindIntronForDomPAS.sh
    Untracked:  code/FindIntronForDomPAS_DF.sh
    Untracked:  code/GencodeDiffSplice.err
    Untracked:  code/GencodeDiffSplice.out
    Untracked:  code/GetMAPQscore.py
    Untracked:  code/GetSecondaryMap.py
    Untracked:  code/HchromOrder.err
    Untracked:  code/HchromOrder.out
    Untracked:  code/IntersectMMandOrtho.err
    Untracked:  code/IntersectMMandOrtho.out
    Untracked:  code/IntersectPASandOrtho.err
    Untracked:  code/IntersectPASandOrtho.out
    Untracked:  code/JunctionLift.err
    Untracked:  code/JunctionLift.out
    Untracked:  code/JunctionLiftFinalChimp.err
    Untracked:  code/JunctionLiftFinalChimp.out
    Untracked:  code/Lift5perPAS.sh
    Untracked:  code/Lift5perPASbed.err
    Untracked:  code/Lift5perPASbed.out
    Untracked:  code/LiftClustersFirst.err
    Untracked:  code/LiftClustersFirst.out
    Untracked:  code/LiftClustersFirst_remove.err
    Untracked:  code/LiftClustersFirst_remove.out
    Untracked:  code/LiftClustersSecond.err
    Untracked:  code/LiftClustersSecond.out
    Untracked:  code/LiftClustersSecond_remove.err
    Untracked:  code/LiftClustersSecond_remove.out
    Untracked:  code/LiftFinalChimpJunc2Human.sh
    Untracked:  code/LiftOrthoPAS2chimp.sh
    Untracked:  code/LiftorthoPAS.err
    Untracked:  code/LiftorthoPASt.out
    Untracked:  code/Log.out
    Untracked:  code/MapBadSamples.err
    Untracked:  code/MapBadSamples.out
    Untracked:  code/MapBadSamples.sh
    Untracked:  code/MapStats.err
    Untracked:  code/MapStats.out
    Untracked:  code/MaxEntCode/
    Untracked:  code/MergeClusters.err
    Untracked:  code/MergeClusters.out
    Untracked:  code/MergeClusters.sh
    Untracked:  code/MismatchNumbers.err
    Untracked:  code/MismatchNumbers.out
    Untracked:  code/MismatchNumbers.sh
    Untracked:  code/PAS_ATTAAA.err
    Untracked:  code/PAS_ATTAAA.out
    Untracked:  code/PAS_ATTAAA.sh
    Untracked:  code/PAS_ATTAAADF.err
    Untracked:  code/PAS_ATTAAADF.out
    Untracked:  code/PAS_ATTAAA_df.sh
    Untracked:  code/PAS_seqExpanded.sh
    Untracked:  code/PAS_sequence.err
    Untracked:  code/PAS_sequence.out
    Untracked:  code/PAS_sequenceDF.err
    Untracked:  code/PAS_sequenceDF.out
    Untracked:  code/PASexpanded_sequenceDF.err
    Untracked:  code/PASexpanded_sequenceDF.out
    Untracked:  code/PASsequences.sh
    Untracked:  code/PASsequences_DF.sh
    Untracked:  code/PlotNuclearUsagebySpecies.R
    Untracked:  code/PlotNuclearUsagebySpecies_DF.R
    Untracked:  code/QuantMergeClusters
    Untracked:  code/QuantMergeClusters.err
    Untracked:  code/QuantMergeClusters.out
    Untracked:  code/QuantMergedClusters.sh
    Untracked:  code/RNATranscriptDTplot.err
    Untracked:  code/RNATranscriptDTplot.out
    Untracked:  code/RNATranscriptDTplot.sh
    Untracked:  code/Rev_liftoverPAShg19to38.err
    Untracked:  code/Rev_liftoverPAShg19to38.out
    Untracked:  code/ReverseLiftFilter.R
    Untracked:  code/RunFixCluster.err
    Untracked:  code/RunFixCluster.out
    Untracked:  code/RunFixLeafCluster.sh
    Untracked:  code/RunNegMCMediation.err
    Untracked:  code/RunNegMCMediation.sh
    Untracked:  code/RunNegMCMediationDF.err
    Untracked:  code/RunNegMCMediationDF.out
    Untracked:  code/RunNegMCMediationDF.sh
    Untracked:  code/RunNegMCMediationr.out
    Untracked:  code/RunPosMCMediation.err
    Untracked:  code/RunPosMCMediation.sh
    Untracked:  code/RunPosMCMediationDF.err
    Untracked:  code/RunPosMCMediationDF.out
    Untracked:  code/RunPosMCMediationDF.sh
    Untracked:  code/RunPosMCMediationr.out
    Untracked:  code/SAF215upbed_gen.py
    Untracked:  code/SAF2Bed.py
    Untracked:  code/Snakefile
    Untracked:  code/SnakefilePAS
    Untracked:  code/SnakefilePASfilt
    Untracked:  code/SortIndexBadSamples.err
    Untracked:  code/SortIndexBadSamples.out
    Untracked:  code/SortIndexBadSamples.sh
    Untracked:  code/StarMM2.err
    Untracked:  code/StarMM2.out
    Untracked:  code/StarMM2.sh
    Untracked:  code/TestFC.err
    Untracked:  code/TestFC.out
    Untracked:  code/TestFC.sh
    Untracked:  code/TotalTranscriptDTplot.err
    Untracked:  code/TotalTranscriptDTplot.out
    Untracked:  code/Upstream10Bases_general.py
    Untracked:  code/allPASSeq_df.sh
    Untracked:  code/apaQTLsnake.err
    Untracked:  code/apaQTLsnake.out
    Untracked:  code/apaQTLsnakePAS.err
    Untracked:  code/apaQTLsnakePAS.out
    Untracked:  code/apaQTLsnakePAShuman.err
    Untracked:  code/apaQTLsnakefiltPAS.err
    Untracked:  code/apaQTLsnakefiltPAS.out
    Untracked:  code/assignPeak2Intronicregion.err
    Untracked:  code/assignPeak2Intronicregion.out
    Untracked:  code/assignPeak2Intronicregion.sh
    Untracked:  code/bam2junc.err
    Untracked:  code/bam2junc.out
    Untracked:  code/bam2junc_remove.err
    Untracked:  code/bam2junc_remove.out
    Untracked:  code/bed215upbed.py
    Untracked:  code/bed2Bedbothstrand.py
    Untracked:  code/bed2SAF_gen.py
    Untracked:  code/bed2saf.py
    Untracked:  code/bg_to_cov.py
    Untracked:  code/buildIndecpantro5
    Untracked:  code/buildIndecpantro5.sh
    Untracked:  code/buildLeafviz.err
    Untracked:  code/buildLeafviz.out
    Untracked:  code/buildLeafviz.sh
    Untracked:  code/buildLeafviz_leadAnno.sh
    Untracked:  code/buildLeafviz_leafanno.err
    Untracked:  code/buildLeafviz_leafanno.out
    Untracked:  code/buildStarIndex.sh
    Untracked:  code/callPeaksYL.py
    Untracked:  code/chimpChromprder.sh
    Untracked:  code/chimpMultiCov.err
    Untracked:  code/chimpMultiCov.out
    Untracked:  code/chimpMultiCov.sh
    Untracked:  code/chimpMultiCov255.sh
    Untracked:  code/chimpMultiCovInclusive.err
    Untracked:  code/chimpMultiCovInclusive.out
    Untracked:  code/chimpMultiCovInclusive.sh
    Untracked:  code/chooseAnno2Bed.py
    Untracked:  code/chooseAnno2SAF.py
    Untracked:  code/chooseSignalSite.py
    Untracked:  code/chromOrder.err
    Untracked:  code/chromOrder.out
    Untracked:  code/classifyLeafviz.err
    Untracked:  code/classifyLeafviz.out
    Untracked:  code/cleanbed2saf.py
    Untracked:  code/cluster.json
    Untracked:  code/cluster2bed.py
    Untracked:  code/clusterLiftReverse.sh
    Untracked:  code/clusterLiftReverse_removebad.sh
    Untracked:  code/clusterLiftprimary.sh
    Untracked:  code/clusterLiftprimary_removebad.sh
    Untracked:  code/clusterPAS.json
    Untracked:  code/clusterfiltPAS.json
    Untracked:  code/comands2Mege.sh
    Untracked:  code/converBam2Junc.sh
    Untracked:  code/converBam2Junc_removeBad.sh
    Untracked:  code/convertNumeric.py
    Untracked:  code/environment.yaml
    Untracked:  code/extraSnakefiltpas
    Untracked:  code/extractPhyloReg.py
    Untracked:  code/extractPhyloRegGene.py
    Untracked:  code/extractPhylopGeneral.py
    Untracked:  code/extractPhylopReg200down.py
    Untracked:  code/extractPhylopReg200up.py
    Untracked:  code/filter5perc.R
    Untracked:  code/filter5percPAS.py
    Untracked:  code/filter5percPheno.py
    Untracked:  code/filterBamforMP.pysam2_gen.py
    Untracked:  code/filterJuncChroms.err
    Untracked:  code/filterJuncChroms.out
    Untracked:  code/filterMissprimingInNuc10_gen.py
    Untracked:  code/filterNumChroms.py
    Untracked:  code/filterPASforMP.py
    Untracked:  code/filterPostLift.py
    Untracked:  code/filterPrimaryread.py
    Untracked:  code/filterSAFforMP_gen.py
    Untracked:  code/filterSecondaryread.py
    Untracked:  code/filterSortBedbyCleanedBed_gen.R
    Untracked:  code/filterpeaks.py
    Untracked:  code/fixExonFC.py
    Untracked:  code/fixFChead.py
    Untracked:  code/fixFChead_bothfrac.py
    Untracked:  code/fixFCheadforExp.py
    Untracked:  code/fixLeafCluster.py
    Untracked:  code/fixLiftedJunc.py
    Untracked:  code/fixUTRexonanno.py
    Untracked:  code/formathg38Anno.py
    Untracked:  code/generateStarIndex.err
    Untracked:  code/generateStarIndex.out
    Untracked:  code/generateStarIndexHuman.err
    Untracked:  code/generateStarIndexHuman.out
    Untracked:  code/getAlloverlap.py
    Untracked:  code/getRNAseqMapStats.sh
    Untracked:  code/hg19MapStats.err
    Untracked:  code/hg19MapStats.out
    Untracked:  code/hg19MapStats.sh
    Untracked:  code/humanChromorder.sh
    Untracked:  code/humanFiles
    Untracked:  code/humanMultiCov.err
    Untracked:  code/humanMultiCov.out
    Untracked:  code/humanMultiCov.sh
    Untracked:  code/humanMultiCov255.err
    Untracked:  code/humanMultiCov255.out
    Untracked:  code/humanMultiCov255.sh
    Untracked:  code/humanMultiCovInclusive.err
    Untracked:  code/humanMultiCovInclusive.out
    Untracked:  code/humanMultiCov_inclusive.sh
    Untracked:  code/intersectAnno.err
    Untracked:  code/intersectAnno.out
    Untracked:  code/intersectAnnoExt.err
    Untracked:  code/intersectAnnoExt.out
    Untracked:  code/intersectLiftedPAS.sh
    Untracked:  code/leafcutter_merge_regtools_redo.py
    Untracked:  code/liftJunctionFiles.sh
    Untracked:  code/liftPAS19to38.sh
    Untracked:  code/liftoverPAShg19to38.err
    Untracked:  code/liftoverPAShg19to38.out
    Untracked:  code/log/
    Untracked:  code/make5percPeakbed.py
    Untracked:  code/makeFileID.py
    Untracked:  code/makeNuclearDapaplots.sh
    Untracked:  code/makeNuclearDapaplots_DF.sh
    Untracked:  code/makeNuclearPlots.err
    Untracked:  code/makeNuclearPlots.out
    Untracked:  code/makeNuclearPlotsDF.err
    Untracked:  code/makeNuclearPlotsDF.out
    Untracked:  code/makePheno.py
    Untracked:  code/makeSamplyGroupsChimp_TvN.py
    Untracked:  code/makeSamplyGroupsHuman_TvN.py
    Untracked:  code/mapRNAseqhg19.sh
    Untracked:  code/mapRNAseqhg19_newPipeline.sh
    Untracked:  code/maphg19.err
    Untracked:  code/maphg19.out
    Untracked:  code/maphg19.sh
    Untracked:  code/maphg19_new.err
    Untracked:  code/maphg19_new.out
    Untracked:  code/maphg19_sub.err
    Untracked:  code/maphg19_sub.out
    Untracked:  code/maphg19_subjunc.sh
    Untracked:  code/mediation_test.R
    Untracked:  code/merge.err
    Untracked:  code/mergeChimp3prime_inhg38.sh
    Untracked:  code/merge_leafcutter_clusters_redo.py
    Untracked:  code/mergeandBWRNAseq.sh
    Untracked:  code/mergeandsort_ChimpinHuman.err
    Untracked:  code/mergeandsort_ChimpinHuman.out
    Untracked:  code/mergedBam2BW.sh
    Untracked:  code/mergedbam2bw.err
    Untracked:  code/mergedbam2bw.out
    Untracked:  code/mergedbamRNAand2bw.err
    Untracked:  code/mergedbamRNAand2bw.out
    Untracked:  code/nameClusters.py
    Untracked:  code/namePeaks.py
    Untracked:  code/negativeMediation_montecarlo.R
    Untracked:  code/negativeMediation_montecarloDF.R
    Untracked:  code/nuclearTranscriptDTplot.err
    Untracked:  code/nuclearTranscriptDTplot.out
    Untracked:  code/numMultimap.py
    Untracked:  code/overlapMMandOrthoexon.sh
    Untracked:  code/overlapPAS.err
    Untracked:  code/overlapPAS.out
    Untracked:  code/overlapPASandOrthoexon.sh
    Untracked:  code/overlapapaQTLPAS.sh
    Untracked:  code/overlapapaQTLPAS_extended.sh
    Untracked:  code/overlapapaQTLPAS_samples.sh
    Untracked:  code/parseHg38.py
    Untracked:  code/peak2PAS.py
    Untracked:  code/pheno2countonly.R
    Untracked:  code/postiveMediation_montecarlo.R
    Untracked:  code/postiveMediation_montecarlo_DF.R
    Untracked:  code/prepareAnnoLeafviz.err
    Untracked:  code/prepareAnnoLeafviz.out
    Untracked:  code/prepareCleanLiftedFC_5perc4LC.py
    Untracked:  code/prepareLeafvizAnno.sh
    Untracked:  code/preparePAS4lift.py
    Untracked:  code/prepare_phenotype_table.py
    Untracked:  code/primaryLift.err
    Untracked:  code/primaryLift.out
    Untracked:  code/primaryLift.sh
    Untracked:  code/processhg38exons.py
    Untracked:  code/quantJunc.sh
    Untracked:  code/quantJunc_TEST.sh
    Untracked:  code/quantJunc_removeBad.sh
    Untracked:  code/quantLiftedPAS.err
    Untracked:  code/quantLiftedPAS.out
    Untracked:  code/quantLiftedPAS.sh
    Untracked:  code/quantLiftedPASPrimary.err
    Untracked:  code/quantLiftedPASPrimary.out
    Untracked:  code/quantLiftedPASPrimary.sh
    Untracked:  code/quatJunc.err
    Untracked:  code/quatJunc.out
    Untracked:  code/recChimpback2Human.err
    Untracked:  code/recChimpback2Human.out
    Untracked:  code/recLiftchim2human.sh
    Untracked:  code/revLift.err
    Untracked:  code/revLift.out
    Untracked:  code/revLiftPAShg38to19.sh
    Untracked:  code/reverseLift.sh
    Untracked:  code/runCheckReverseLift.sh
    Untracked:  code/runChimpDiffIso.sh
    Untracked:  code/runChimpDiffIsoDF.sh
    Untracked:  code/runCountNucleotides.err
    Untracked:  code/runCountNucleotides.out
    Untracked:  code/runCountNucleotides.sh
    Untracked:  code/runCountNucleotidesPantro6.err
    Untracked:  code/runCountNucleotidesPantro6.out
    Untracked:  code/runCountNucleotides_pantro6.sh
    Untracked:  code/runFilterNumChroms.sh
    Untracked:  code/runHumanDiffIso.sh
    Untracked:  code/runHumanDiffIsoDF.sh
    Untracked:  code/runNuclearDiffIso_DF.sh
    Untracked:  code/runNuclearDifffIso.sh
    Untracked:  code/runTotalDiffIso.sh
    Untracked:  code/run_Chimpleafcutter_ds.err
    Untracked:  code/run_Chimpleafcutter_ds.out
    Untracked:  code/run_Chimpverifybam.err
    Untracked:  code/run_Chimpverifybam.out
    Untracked:  code/run_Humanleafcutter_dF.err
    Untracked:  code/run_Humanleafcutter_dF.out
    Untracked:  code/run_Humanleafcutter_ds.err
    Untracked:  code/run_Humanleafcutter_ds.out
    Untracked:  code/run_Nuclearleafcutter_ds.err
    Untracked:  code/run_Nuclearleafcutter_ds.out
    Untracked:  code/run_Nuclearleafcutter_dsDF.err
    Untracked:  code/run_Nuclearleafcutter_dsDF.out
    Untracked:  code/run_Totalleafcutter_ds.err
    Untracked:  code/run_Totalleafcutter_ds.out
    Untracked:  code/run_chimpverifybam.sh
    Untracked:  code/run_verifyBam.sh
    Untracked:  code/run_verifybam.err
    Untracked:  code/run_verifybam.out
    Untracked:  code/slurm-62824013.out
    Untracked:  code/slurm-62825841.out
    Untracked:  code/slurm-62826116.out
    Untracked:  code/slurm-64108209.out
    Untracked:  code/slurm-64108521.out
    Untracked:  code/slurm-64108557.out
    Untracked:  code/snakePASChimp.err
    Untracked:  code/snakePASChimp.out
    Untracked:  code/snakePAShuman.out
    Untracked:  code/snakemake.batch
    Untracked:  code/snakemakeChimp.err
    Untracked:  code/snakemakeChimp.out
    Untracked:  code/snakemakeHuman.err
    Untracked:  code/snakemakeHuman.out
    Untracked:  code/snakemakePAS.batch
    Untracked:  code/snakemakePASFiltChimp.err
    Untracked:  code/snakemakePASFiltChimp.out
    Untracked:  code/snakemakePASFiltHuman.err
    Untracked:  code/snakemakePASFiltHuman.out
    Untracked:  code/snakemakePAS_Human.batch
    Untracked:  code/snakemakePASchimp.batch
    Untracked:  code/snakemakePAShuman.batch
    Untracked:  code/snakemake_chimp.batch
    Untracked:  code/snakemake_human.batch
    Untracked:  code/snakemakefiltPAS.batch
    Untracked:  code/snakemakefiltPAS_chimp.sh
    Untracked:  code/snakemakefiltPAS_human.batch
    Untracked:  code/snakemakefiltPAS_human.sh
    Untracked:  code/spliceSite2Fasta.py
    Untracked:  code/submit-snakemake-chimp.sh
    Untracked:  code/submit-snakemake-human.sh
    Untracked:  code/submit-snakemakePAS-chimp.sh
    Untracked:  code/submit-snakemakePAS-human.sh
    Untracked:  code/submit-snakemakefiltPAS-chimp.sh
    Untracked:  code/submit-snakemakefiltPAS-human.sh
    Untracked:  code/subset_diffisopheno.py
    Untracked:  code/subset_diffisopheno_Chimp_tvN.py
    Untracked:  code/subset_diffisopheno_Chimp_tvN_DF.py
    Untracked:  code/subset_diffisopheno_Huma_tvN.py
    Untracked:  code/subset_diffisopheno_Huma_tvN_DF.py
    Untracked:  code/subset_diffisopheno_Nuclear_HvC.py
    Untracked:  code/subset_diffisopheno_Nuclear_HvC_DF.py
    Untracked:  code/subset_diffisopheno_Total_HvC.py
    Untracked:  code/test
    Untracked:  code/test.txt
    Untracked:  code/threeprimeOrthoFC.out
    Untracked:  code/threeprimeOrthoFC.sh
    Untracked:  code/threeprimeOrthoFCcd.err
    Untracked:  code/transcriptDTplotsNuclear.sh
    Untracked:  code/transcriptDTplotsTotal.sh
    Untracked:  code/verifyBam4973.sh
    Untracked:  code/verifyBam4973inHuman.sh
    Untracked:  code/verifybam4973.err
    Untracked:  code/verifybam4973.out
    Untracked:  code/verifybam4973HumanMap.err
    Untracked:  code/verifybam4973HumanMap.out
    Untracked:  code/wrap_Chimpverifybam.err
    Untracked:  code/wrap_Chimpverifybam.out
    Untracked:  code/wrap_chimpverifybam.sh
    Untracked:  code/wrap_verifyBam.sh
    Untracked:  code/wrap_verifybam.err
    Untracked:  code/wrap_verifybam.out
    Untracked:  code/writeMergecode.py
    Untracked:  data/._.DS_Store
    Untracked:  data/._HC_filenames.txt
    Untracked:  data/._HC_filenames.txt.sb-4426323c-IKIs0S
    Untracked:  data/._HC_filenames.xlsx
    Untracked:  data/._MapPantro6_meta.txt
    Untracked:  data/._MapPantro6_meta.txt.sb-a5794dd2-Cskmlm
    Untracked:  data/._MapPantro6_meta.xlsx
    Untracked:  data/._OppositeSpeciesMap.txt
    Untracked:  data/._OppositeSpeciesMap.txt.sb-a5794dd2-mayWJf
    Untracked:  data/._OppositeSpeciesMap.xlsx
    Untracked:  data/._RNASEQ_metadata.txt
    Untracked:  data/._RNASEQ_metadata.txt.sb-4426323c-TE4ns3
    Untracked:  data/._RNASEQ_metadata.txt.sb-51f67ae1-HXp7Gq
    Untracked:  data/._RNASEQ_metadata_2Removed.txt
    Untracked:  data/._RNASEQ_metadata_2Removed.txt.sb-4426323c-a4lBwx
    Untracked:  data/._RNASEQ_metadata_2Removed.xlsx
    Untracked:  data/._RNASEQ_metadata_stranded.txt
    Untracked:  data/._RNASEQ_metadata_stranded.txt.sb-a5794dd2-D659m2
    Untracked:  data/._RNASEQ_metadata_stranded.txt.sb-a5794dd2-ImNMoY
    Untracked:  data/._RNASEQ_metadata_stranded.txt.sb-e4bf31f0-ZGnGgl
    Untracked:  data/._RNASEQ_metadata_stranded.xlsx
    Untracked:  data/._TrialFiltersMeta.txt
    Untracked:  data/._TrialFiltersMeta.txt.sb-9845453e-R58Y0Q
    Untracked:  data/._metadata_HCpanel.txt
    Untracked:  data/._metadata_HCpanel.txt.sb-a3d92a2d-b9cYoF
    Untracked:  data/._metadata_HCpanel.txt.sb-a5794dd2-i594qs
    Untracked:  data/._metadata_HCpanel.txt.sb-f4823d1e-qihGek
    Untracked:  data/._metadata_HCpanel_frompantro5.xlsx
    Untracked:  data/._~$RNASEQ_metadata.xlsx
    Untracked:  data/._~$metadata_HCpanel.xlsx
    Untracked:  data/._.xlsx
    Untracked:  data/BaseComp/
    Untracked:  data/CleanLiftedPeaks_FC_primary/
    Untracked:  data/CompapaQTLpas/
    Untracked:  data/DNDS/
    Untracked:  data/DTmatrix/
    Untracked:  data/DiffExpression/
    Untracked:  data/DiffIso_Nuclear/
    Untracked:  data/DiffIso_Nuclear_DF/
    Untracked:  data/DiffIso_Total/
    Untracked:  data/DiffSplice/
    Untracked:  data/DiffSplice_liftedJunc/
    Untracked:  data/DiffSplice_removeBad/
    Untracked:  data/DominantPAS/
    Untracked:  data/DominantPAS_DF/
    Untracked:  data/EvalPantro5/
    Untracked:  data/HC_filenames.txt
    Untracked:  data/HC_filenames.xlsx
    Untracked:  data/Khan_prot/
    Untracked:  data/Li_eqtls/
    Untracked:  data/MapPantro6_meta.txt
    Untracked:  data/MapPantro6_meta.xlsx
    Untracked:  data/MapStats/
    Untracked:  data/NormalizedClusters/
    Untracked:  data/NuclearHvC/
    Untracked:  data/NuclearHvC_DF/
    Untracked:  data/OppositeSpeciesMap.txt
    Untracked:  data/OppositeSpeciesMap.xlsx
    Untracked:  data/OrthoExonBed/
    Untracked:  data/OverlapBenchmark/
    Untracked:  data/OverlappingPAS/
    Untracked:  data/PAS/
    Untracked:  data/PAS_SAF/
    Untracked:  data/PAS_doubleFilter/
    Untracked:  data/Peaks_5perc/
    Untracked:  data/Pheno_5perc/
    Untracked:  data/Pheno_5perc_DF_nuclear/
    Untracked:  data/Pheno_5perc_nuclear/
    Untracked:  data/Pheno_5perc_nuclear_old/
    Untracked:  data/Pheno_5perc_total/
    Untracked:  data/PhyloP/
    Untracked:  data/Pol2Chip/
    Untracked:  data/RNASEQ_metadata.txt
    Untracked:  data/RNASEQ_metadata_2Removed.txt
    Untracked:  data/RNASEQ_metadata_2Removed.xlsx
    Untracked:  data/RNASEQ_metadata_stranded.txt
    Untracked:  data/RNASEQ_metadata_stranded.txt.sb-e4bf31f0-ZGnGgl/
    Untracked:  data/RNASEQ_metadata_stranded.xlsx
    Untracked:  data/SignalSites/
    Untracked:  data/SignalSites_doublefilter/
    Untracked:  data/SpliceSite/
    Untracked:  data/TestAnnoBiasOE/
    Untracked:  data/TestMM2/
    Untracked:  data/TestMM2_AS/
    Untracked:  data/TestMM2_PrimaryRead/
    Untracked:  data/TestMM2_SeondaryRead/
    Untracked:  data/TestMM2_mismatch/
    Untracked:  data/TestMM2_quality/
    Untracked:  data/TestWithinMergePAS/
    Untracked:  data/Test_FC_methods/
    Untracked:  data/Threeprime2Ortho/
    Untracked:  data/TotalFractionPAS/
    Untracked:  data/TotalHvC/
    Untracked:  data/TrialFiltersMeta.txt
    Untracked:  data/TwoBadSampleAnalysis/
    Untracked:  data/Wang_ribo/
    Untracked:  data/apaQTLGenes/
    Untracked:  data/bioGRID/
    Untracked:  data/chainFiles/
    Untracked:  data/cleanPeaks_anno/
    Untracked:  data/cleanPeaks_byspecies/
    Untracked:  data/cleanPeaks_lifted/
    Untracked:  data/files4viz_nuclear/
    Untracked:  data/files4viz_nuclear_DF/
    Untracked:  data/gviz/
    Untracked:  data/leafviz/
    Untracked:  data/liftover_files/
    Untracked:  data/mediation/
    Untracked:  data/mediation_DF/
    Untracked:  data/metadata_HCpanel.txt
    Untracked:  data/metadata_HCpanel.xlsx
    Untracked:  data/metadata_HCpanel_extra.txt
    Untracked:  data/metadata_HCpanel_frompantro5.txt
    Untracked:  data/metadata_HCpanel_frompantro5.xlsx
    Untracked:  data/multimap/
    Untracked:  data/orthoUTR/
    Untracked:  data/primaryLift/
    Untracked:  data/reverseLift/
    Untracked:  data/testQuant/
    Untracked:  data/~$RNASEQ_metadata.xlsx
    Untracked:  data/~$metadata_HCpanel.xlsx
    Untracked:  data/.xlsx
    Untracked:  output/._.DS_Store
    Untracked:  output/dtPlots/
    Untracked:  projectNotes.Rmd
    Untracked:  proteinModelSet.Rmd

Unstaged changes:
    Modified:   analysis/ExploredAPA.Rmd
    Modified:   analysis/MMExpreiment.Rmd
    Modified:   analysis/OppositeMap.Rmd
    Modified:   analysis/TotalVNuclearBothSpecies.Rmd
    Modified:   analysis/annotationInfo.Rmd
    Modified:   analysis/changeMisprimcut.Rmd
    Modified:   analysis/comp2apaQTLPAS.Rmd
    Modified:   analysis/correlationPhenos.Rmd
    Modified:   analysis/establishCutoffs.Rmd
    Modified:   analysis/investigatePantro5.Rmd
    Modified:   analysis/multiMap.Rmd
    Modified:   analysis/pol2.Rmd
    Modified:   analysis/speciesSpecific.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 fbabfb7 brimittleman 2020-04-10 remove 18499
html c2a0778 brimittleman 2020-04-06 Build site.
Rmd 9676d72 brimittleman 2020-04-06 updated anno
html f02217e brimittleman 2020-01-28 Build site.
Rmd 86aabf2 brimittleman 2020-01-28 add expression overlap with APA exploration

I will complete the same analysis I did in the other explore APA and expression analysis but I will subset the overlapping gene. For these I know that there are differences in both phenotypes.

Genes with overlap:

GenesUse=read.table("../data/DiffIso_Nuclear_DF/GeneswithDEanddAPA.txt", header = T, stringsAsFactors = F)

In this analysis I will do as much as I can do compare APA and expression. I will look at the genes we have data for both.

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("gplots")

Attaching package: 'gplots'
The following object is masked from 'package:stats':

    lowess
library("scales")

Attaching package: 'scales'
The following object is masked from 'package:purrr':

    discard
The following object is masked from 'package:readr':

    col_factor
library("RColorBrewer")
library(ggpubr)
Loading required package: magrittr

Attaching package: 'magrittr'
The following object is masked from 'package:purrr':

    set_names
The following object is masked from 'package:tidyr':

    extract

I will start with a full correlation matrix using the counts for the top used PAS (mean human and chimp).

TopUsedPAS=read.table("../data/PAS_doubleFilter/PAS_5perc_either_HumanCoord_BothUsage_meta_doubleFilter.txt", header=T,stringsAsFactors = F) %>% mutate(MeanUsage=(Chimp+Human)/2) %>% group_by(gene) %>% arrange(desc(MeanUsage)) %>% slice(1) %>% ungroup() %>% dplyr::select(PAS, chr, start, end) %>% rename("Chr"= chr,"Start"= start, "End"= end)

Filter these in the counts file:

#Both:human74:chr1:944201:944401:+:NOC2L_utr3


HumanCounts=read.table("../Human/data/CleanLiftedPeaks_FC/ALLPAS_postLift_LocParsed_Human_fixed.fc",stringsAsFactors = F,header = T) %>% inner_join(TopUsedPAS,by=c("Chr", "Start", "End")) %>% separate(Geneid, into=c("d", "pas", "chr","start","end","strand", "geneID"), sep=":") %>% separate(geneID,into=c("gene","loc"),sep="_") %>% dplyr::select(PAS, gene, contains("_N"))

ChimpCounts=read.table("../Chimp/data/CleanLiftedPeaks_FC/ALLPAS_postLift_LocParsed_Chimp_fixed.fc",stringsAsFactors = F,header = T) %>% separate(Geneid, into=c("d", "PAS", "chr","start","end","strand", "geneID"), sep=":") %>% separate(geneID,into=c("gene","loc"),sep="_") %>% inner_join(TopUsedPAS,by=c("PAS")) %>% dplyr::select(PAS, gene, contains("_N"))
Warning: Expected 2 pieces. Additional pieces discarded in 4 rows [50254,
50255, 50256, 95621].
AllCounts=HumanCounts %>% inner_join(ChimpCounts, by=c("gene", "PAS")) %>% dplyr::select(-PAS)


colnames(AllCounts)=paste("APA" ,colnames(AllCounts), sep="_")


AllCounts=AllCounts %>% rename("gene"= APA_gene) %>% filter(gene %in% GenesUse$gene)

Expression counts:

nameID=read.table("../../genome_anotation_data/ensemble_to_genename.txt",sep="\t", header = T, stringsAsFactors = F)
HumanRNA=read.table("../Human/data/RNAseq/ExonCounts/RNAseqOrthoExon.fixed.fc", header = T, stringsAsFactors = F) %>% dplyr::select(-Chr,-Start,-End,-Strand, -Length)

ChimpRNA=read.table("../Chimp/data/RNAseq/ExonCounts/RNAseqOrthoExon.fixed.fc", header = T, stringsAsFactors = F) %>% dplyr::select(-Chr,-Start,-End,-Strand, -Length)


RNACounts=HumanRNA %>% inner_join(ChimpRNA,by="Geneid") %>% rename("Gene_stable_ID"=Geneid) %>% inner_join(nameID, by="Gene_stable_ID") %>% dplyr::select(-Gene_stable_ID, -Source_of_gene_name) %>% rename("gene"= Gene.name) %>% group_by(gene) %>% slice(1) %>% ungroup()


colnames(RNACounts)=paste("RNA" ,colnames(RNACounts), sep="_")

RNACounts=RNACounts %>% rename("gene"= RNA_gene) %>% filter(gene %in% GenesUse$gene)

Add all together:

BothPhenoCount=  RNACounts %>% inner_join(AllCounts, by="gene")%>% column_to_rownames(var="gene")

Names=colnames(BothPhenoCount)
pal <- c(brewer.pal(9, "Set1"), brewer.pal(8, "Set2"), brewer.pal(12, "Set3"))
colors <- colorRampPalette(c(brewer.pal(9, "Blues")[1],brewer.pal(9, "Blues")[9]))(100)
Species=c(rep("Human",5), rep("Chimp",6),rep("Human",5),rep("Chimp",6))
Meta=as.data.frame(cbind(Names,Species )) %>% mutate(Pheno=ifelse(grepl("RNA",Names),"RNA", "APA" )) 
Warning in cbind(Names, Species): number of rows of result is not a
multiple of vector length (arg 2)
cors <- cor(BothPhenoCount, method="spearman", use="pairwise.complete.obs")

heatmap.2( cors, scale="none", col = colors, margins = c(12, 12), trace='none',ColSideColors=pal[as.integer(as.factor(Meta$Species))], RowSideColors=pal[as.integer(as.factor(Meta$Pheno))+9], cexCol = 0.2 + 1/log10(15), cexRow = 0.2 + 1/log10(15))

Version Author Date
c2a0778 brimittleman 2020-04-06
f02217e brimittleman 2020-01-28

Pvalues:

DE= read.table("../data/DiffExpression/DEtested_allres.txt",header=F, stringsAsFactors = F,col.names = c('Gene_stable_ID', 'logFC' ,'AveExpr', 't', 'P.Value', 'adj.P.Val', 'B')) %>% inner_join(nameID, by="Gene_stable_ID") %>% dplyr::select(-Gene_stable_ID, -Source_of_gene_name) %>% rename("gene"=Gene.name)%>% filter(gene %in% GenesUse$gene)

APA=read.table(c("../data/DiffIso_Nuclear_DF/AllPAS_withGeneSig.txt"),header = T,stringsAsFactors = F) 
GenesWithapa=read.table("../data/DiffIso_Nuclear_DF/SignifianceEitherGENES_Nuclear.txt", header = T, stringsAsFactors = F) %>% filter(gene %in% GenesUse$gene)

DEandAPA= DE %>% inner_join(APA, by="gene") %>% mutate(HasDPAU=ifelse(gene %in% GenesWithapa$gene, "Yes","No"))

Correlation between effect sizes:

ggplot(DEandAPA,aes(x=logFC, y=logef)) + geom_point() + labs(x="DE log Effect size", y="APA effect size",title="Relationship between effect sizes") + geom_density2d()

Version Author Date
c2a0778 brimittleman 2020-04-06
f02217e brimittleman 2020-01-28 
ggplot(DEandAPA,aes(x=abs(logFC), y=abs(logef))) + geom_point()+ labs(x="abs(DE log Effect size)", y="abs(APA effect size)",title="Relationship between absolute values of effect sizes") + geom_smooth(method="lm") +annotate("text", label="Beta= 0.28 , R2= 0.03",y=40,x=5)

Version Author Date
c2a0778 brimittleman 2020-04-06
f02217e brimittleman 2020-01-28 
summary(lm(abs(DEandAPA$logef)~abs(DEandAPA$logFC)))

Call:
lm(formula = abs(DEandAPA$logef) ~ abs(DEandAPA$logFC))

Residuals:
   Min     1Q Median     3Q    Max 
-2.141 -0.728 -0.355  0.206 85.459 

Coefficients:
                    Estimate Std. Error t value Pr(>|t|)    
(Intercept)          0.84969    0.05699  14.910  < 2e-16 ***
abs(DEandAPA$logFC)  0.24810    0.03621   6.853 8.64e-12 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 2.082 on 3264 degrees of freedom
Multiple R-squared:  0.01418,   Adjusted R-squared:  0.01388 
F-statistic: 46.96 on 1 and 3264 DF,  p-value: 8.638e-12

Subset the PAS in the top used:

TopUsedPASlow= TopUsedPAS %>% rename("chr"=Chr, "start"=Start, "end"=End)
DEandAPA_filt= DEandAPA %>% semi_join(TopUsedPASlow,by=c("chr","start","end"))

Correlation between effect sizes:

ggplot(DEandAPA_filt,aes(x=logFC, y=logef)) + geom_point() + labs(x="DE log Effect size", y="APA effect size", title="Relationship between effect sizes \n most used PAS")

Version Author Date
c2a0778 brimittleman 2020-04-06
f02217e brimittleman 2020-01-28 
ggplot(DEandAPA_filt,aes(x=abs(logFC), y=abs(logef))) + geom_point( )+ labs(x="abs(DE log Effect size)", y="abs(APA effect size)",title="Relationship between absolute values of effect sizes \n most used PAS") + geom_smooth(method="lm") +annotate("text", label="Beta= 0.3 , R2= 0.04",y=20,x=5)

Version Author Date
c2a0778 brimittleman 2020-04-06
f02217e brimittleman 2020-01-28 
summary(lm(abs(DEandAPA_filt$logef)~abs(DEandAPA_filt$logFC)))

Call:
lm(formula = abs(DEandAPA_filt$logef) ~ abs(DEandAPA_filt$logFC))

Residuals:
    Min      1Q  Median      3Q     Max 
-2.2025 -0.7283 -0.3141  0.1841 16.8990 

Coefficients:
                         Estimate Std. Error t value Pr(>|t|)    
(Intercept)               0.90926    0.09678   9.395  < 2e-16 ***
abs(DEandAPA_filt$logFC)  0.34544    0.06231   5.544 4.41e-08 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 1.555 on 608 degrees of freedom
Multiple R-squared:  0.04812,   Adjusted R-squared:  0.04656 
F-statistic: 30.74 on 1 and 608 DF,  p-value: 4.405e-08

Number of significant PAS and de

DEandAPA_sig= DEandAPA %>% filter(SigPAU2 == "Yes") %>% group_by(gene) %>% summarise(NsigPAS=n())

DEandAPA_sigWithDE= DE %>% inner_join(DEandAPA_sig,by="gene" )


summary(lm(data=DEandAPA_sigWithDE, abs(logFC)~NsigPAS))

Call:
lm(formula = abs(logFC) ~ NsigPAS, data = DEandAPA_sigWithDE)

Residuals:
    Min      1Q  Median      3Q     Max 
-1.3016 -0.6169 -0.3045  0.2329  5.7502 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  0.85417    0.10191   8.382 3.62e-16 ***
NsigPAS      0.23005    0.06607   3.482 0.000534 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 1.002 on 608 degrees of freedom
Multiple R-squared:  0.01955,   Adjusted R-squared:  0.01794 
F-statistic: 12.12 on 1 and 608 DF,  p-value: 0.0005339
ggplot(DEandAPA_sigWithDE, aes(x=NsigPAS, y=abs(logFC))) +geom_point() + geom_smooth(method = "lm") + annotate("text",label="beta=.2, r2=0.018, pvalue=0.0006",x=4, y=6) + labs(x="Number of differentially used PAS 20%",title="Relationship between DE effect size and dAPA PAS")

Version Author Date
c2a0778 brimittleman 2020-04-06
f02217e brimittleman 2020-01-28 
cor( DEandAPA_sigWithDE$NsigPAS, DEandAPA_sigWithDE$logFC, method = "spearman")
[1] -0.04383949
cor(DEandAPA_sigWithDE$B, DEandAPA_sigWithDE$NsigPAS, method = "spearman")
[1] 0.1248363

Maybe use the variance in effect sizes for dAPA:

APA_var= APA %>% group_by(gene) %>% summarise(VarLogef=var(logef), VarDeltaPAU=var(deltaPAU))

APA_varDE= APA_var %>% inner_join(DE, by="gene")
cor(APA_varDE$VarDeltaPAU, APA_varDE$B, method = "spearman")
[1] 0.09857041
cor(APA_varDE$VarDeltaPAU, APA_varDE$logFC, method = "spearman")
[1] -0.02724444
cor(APA_varDE$VarLogef, APA_varDE$B, method = "spearman")
[1] 0.2396989
cor(APA_varDE$VarLogef, APA_varDE$logFC, method = "spearman")
[1] -0.01888453

This does not help other than for the varlogeffect size for APA and the DE beta value.


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] ggpubr_0.2         magrittr_1.5       RColorBrewer_1.1-2
 [4] scales_1.0.0       gplots_3.0.1       forcats_0.3.0     
 [7] stringr_1.3.1      dplyr_0.8.0.1      purrr_0.3.2       
[10] readr_1.3.1        tidyr_0.8.3        tibble_2.1.1      
[13] ggplot2_3.1.1      tidyverse_1.2.1   

loaded via a namespace (and not attached):
 [1] gtools_3.8.1       tidyselect_0.2.5   haven_1.1.2       
 [4] lattice_0.20-38    colorspace_1.3-2   generics_0.0.2    
 [7] htmltools_0.3.6    yaml_2.2.0         rlang_0.4.0       
[10] later_0.7.5        pillar_1.3.1       glue_1.3.0        
[13] withr_2.1.2        modelr_0.1.2       readxl_1.1.0      
[16] plyr_1.8.4         munsell_0.5.0      gtable_0.2.0      
[19] workflowr_1.6.0    cellranger_1.1.0   rvest_0.3.2       
[22] caTools_1.17.1.1   evaluate_0.12      labeling_0.3      
[25] knitr_1.20         httpuv_1.4.5       broom_0.5.1       
[28] Rcpp_1.0.2         KernSmooth_2.23-15 promises_1.0.1    
[31] backports_1.1.2    gdata_2.18.0       jsonlite_1.6      
[34] fs_1.3.1           hms_0.4.2          digest_0.6.18     
[37] stringi_1.2.4      grid_3.5.1         rprojroot_1.3-2   
[40] bitops_1.0-6       cli_1.1.0          tools_3.5.1       
[43] lazyeval_0.2.1     crayon_1.3.4       whisker_0.3-2     
[46] pkgconfig_2.0.2    MASS_7.3-51.1      xml2_1.2.0        
[49] lubridate_1.7.4    assertthat_0.2.0   rmarkdown_1.10    
[52] httr_1.3.1         rstudioapi_0.10    R6_2.3.0          
[55] nlme_3.1-137       git2r_0.26.1       compiler_3.5.1