Number of Conserved PAS

Last updated: 2020-04-08

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: 856c506

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-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/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/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.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.xlsx
    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_frompantro5.txt
    Untracked:  data/metadata_HCpanel_frompantro5.xlsx
    Untracked:  data/multimap/
    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	856c506	brimittleman	2020-04-08	fix labels
html	321219e	brimittleman	2020-04-07	Build site.
Rmd	d231c12	brimittleman	2020-04-07	diff in dom
html	d81b148	brimittleman	2020-04-07	Build site.
Rmd	a672b02	brimittleman	2020-04-07	numb dist for dom

library(workflowr)

This is workflowr version 1.6.0
Run ?workflowr for help getting started

library(tidyverse)

── Attaching packages ─────────────────────────────────────────────────────────── tidyverse 1.2.1 ──

✔ ggplot2 3.1.1       ✔ purrr   0.3.2  
✔ tibble  2.1.1       ✔ dplyr   0.8.0.1
✔ tidyr   0.8.3       ✔ stringr 1.3.1  
✔ readr   1.3.1       ✔ forcats 0.3.0

── Conflicts ────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()

I look at genes with the same dominant PAS but I want to look at the distribution of PAS in a gene. Are the number of PAS used for each gene conserved. I can use different usage filters then see if the distributions are the same or different when the gene has the same dominant site.

One question is whether we see examples of 1 dominant site in one species and the other has more than one site used at similar proportions.

I can start by looking at the genes with shared dominant PAS to see if the usages in each species are similar.

I will filter for genes with more than 1 PAS

PASMeta=read.table("../data/PAS_doubleFilter/PAS_5perc_either_HumanCoord_BothUsage_meta_doubleFilter.txt", header = T, stringsAsFactors = F)
PASpregene=PASMeta %>% group_by(gene) %>% summarize(nPAS=n())
PASmore2=PASpregene %>% filter(nPAS>1)
DiffDom=read.table("../data/DominantPAS_DF/Nuclear_DiffDom.txt",header = T,stringsAsFactors = F) %>% filter(gene %in% PASmore2$gene)
SameDom=read.table("../data/DominantPAS_DF/Nuclear_SameDom.txt",header = T,stringsAsFactors = F) %>% mutate(DiffinDom=Chimp-Human) %>% filter(gene %in% PASmore2$gene)

Plot this: - is more in human:

ggplot(SameDom,aes(x=DiffinDom))+ geom_histogram(bins=100)

Version	Author	Date
d81b148	brimittleman	2020-04-07

A bit shifted toward chimp.

summary(SameDom$DiffinDom)

      Min.    1st Qu.     Median       Mean    3rd Qu.       Max. 
-0.7666667 -0.0008333  0.0733333  0.0781255  0.1591667  0.5408333

I can look at examples at each extreme.

Fore both species, i want to get the number of PAS used at certain cutoffs, 0%-50%

Cutoff=seq(0,.5,.1)
cutoffCol=c()
nPAS=seq(1,5,1)
ChimpGenes=c()
HumanGenes=c()
nPAScol=c()
for (i in Cutoff){
  for (n in nPAS){
    human= PASMeta %>% filter(gene %in% PASmore2$gene, Human >= i) %>% group_by(gene) %>% summarise(nPASingene=n()) %>% filter(nPASingene==n) %>% nrow() 
    HumanGenes=c(HumanGenes,human)
    chimp= PASMeta %>% filter(gene %in% PASmore2$gene,Chimp >= i) %>% group_by(gene) %>% summarise(nPASingene=n()) %>% filter(nPASingene==n) %>% nrow() 
    ChimpGenes=c(ChimpGenes,chimp)
    nPAScol=c(nPAScol,n)
    cutoffCol=c(cutoffCol,i)
  }
}

DFdata=as.data.frame(cbind(nPAScol,cutoffCol,ChimpGenes, HumanGenes))
DFdata_gather=DFdata %>% gather("Species", "NGene", -nPAScol, -cutoffCol)
DFdata_gather$nPAScol=as.factor(DFdata_gather$nPAScol)
DFdata_gather$cutoffCol=as.factor(DFdata_gather$cutoffCol)

ggplot(DFdata_gather,aes(x=cutoffCol, by=nPAScol, y=NGene,fill=nPAScol))+ geom_bar(position = "dodge", stat="identity") +facet_grid(~Species) + scale_fill_brewer(palette="Dark2", name="Number of PAS") + labs(title="Number of PAS per gene by usage",y="Number of Genes", x="Usage is at least")

Version	Author	Date
d81b148	brimittleman	2020-04-07

Do the same thing for same dominant:

PASMetaSame= PASMeta %>% filter(gene %in% SameDom$gene)
cutoffCol_same=c()
ChimpGenes_same=c()
HumanGenes_same=c()
nPAScol_same=c()
for (i in Cutoff){
  for (n in nPAS){
    human= PASMetaSame %>% filter( Human >= i) %>% group_by(gene) %>% summarise(nPASingene=n()) %>% filter(nPASingene==n) %>% nrow() 
    HumanGenes_same=c(HumanGenes_same,human)
    chimp= PASMetaSame %>% filter(Chimp >= i) %>% group_by(gene) %>% summarise(nPASingene=n()) %>% filter(nPASingene==n) %>% nrow() 
    ChimpGenes_same=c(ChimpGenes_same,chimp)
    nPAScol_same=c(nPAScol_same,n)
    cutoffCol_same=c(cutoffCol_same,i)
  }
}

DFdata_same=as.data.frame(cbind(nPAScol_same,cutoffCol_same,ChimpGenes_same, HumanGenes_same))
DFdata_gather_same=DFdata_same %>% gather("Species", "NGene", -nPAScol_same, -cutoffCol_same)
DFdata_gather_same$nPAScol_same=as.factor(DFdata_gather_same$nPAScol_same)
DFdata_gather_same$cutoffCol_same=as.factor(DFdata_gather_same$cutoffCol_same)

ggplot(DFdata_gather_same,aes(x=cutoffCol_same, by=nPAScol_same, y=NGene,fill=nPAScol_same))+ geom_bar(position = "dodge", stat="identity") +facet_grid(~Species) + scale_fill_brewer(palette="Dark2", name="Number of PAS") + labs(title="Number of PAS per gene by usage \n same domiant",y="Number of Genes", x="Usage is at least")

Version	Author	Date
d81b148	brimittleman	2020-04-07

Different dominannt:

PASMetaDiff= PASMeta %>% filter(gene %in% DiffDom$gene)
cutoffCol_Diff=c()
ChimpGenes_Diff=c()
HumanGenes_Diff=c()
nPAScol_Diff=c()
for (i in Cutoff){
  for (n in nPAS){
    human= PASMetaDiff %>% filter( Human >= i) %>% group_by(gene) %>% summarise(nPASingene=n()) %>% filter(nPASingene==n) %>% nrow() 
    HumanGenes_Diff=c(HumanGenes_Diff,human)
    chimp= PASMetaDiff %>% filter(Chimp >= i) %>% group_by(gene) %>% summarise(nPASingene=n()) %>% filter(nPASingene==n) %>% nrow() 
    ChimpGenes_Diff=c(ChimpGenes_Diff,chimp)
    nPAScol_Diff=c(nPAScol_Diff,n)
    cutoffCol_Diff=c(cutoffCol_Diff,i)
  }
}

DFdata_Diff=as.data.frame(cbind(nPAScol_Diff,cutoffCol_Diff,ChimpGenes_Diff, HumanGenes_Diff))
DFdata_gather_Diff=DFdata_Diff %>% gather("Species", "NGene", -nPAScol_Diff, -cutoffCol_Diff)
DFdata_gather_Diff$nPAScol_Diff=as.factor(DFdata_gather_Diff$nPAScol_Diff)
DFdata_gather_Diff$cutoffCol_Diff=as.factor(DFdata_gather_Diff$cutoffCol_Diff)

ggplot(DFdata_gather_Diff,aes(x=cutoffCol_Diff, by=nPAScol_Diff, y=NGene,fill=nPAScol_Diff))+ geom_bar(position = "dodge", stat="identity") +facet_grid(~Species) + scale_fill_brewer(palette="Dark2", name="Number of PAS") + labs(title="Number of PAS per gene by usage \n different domiant",y="Number of Genes", x="Usage is at least")

Version	Author	Date
d81b148	brimittleman	2020-04-07

Number of PAS in same vs diffferent:

NpasSame=PASMetaSame%>% group_by(gene) %>% summarise(nPAS=n()) %>% group_by(nPAS) %>% summarise(Same=n(),PropSame=Same/nrow(PASMetaSame)) %>% select(-Same)
NpasDiff=PASMetaDiff %>% group_by(gene) %>% summarise(nPAS=n()) %>% group_by(nPAS) %>% summarise(Different=n(), PropDiff=Different/nrow(PASMetaDiff)) %>% select(-Different)

NpasBoth= NpasSame %>% inner_join(NpasDiff) %>% gather("GeneSet", "Prop", -nPAS)

Joining, by = "nPAS"

NpasBoth$nPAS=as.factor(NpasBoth$nPAS)

ggplot(NpasBoth,aes(fill=GeneSet, y=Prop, x=nPAS))+ geom_bar(position = "dodge", stat="identity") + scale_fill_brewer(palette="Dark2", labels=c("Different Dominant", "Same Dominant"),name="") + labs(y="Proportion of Genes", x="Number of PAS", title="Number of PAS distribution by Dominance structure")

Version	Author	Date
d81b148	brimittleman	2020-04-07

When the dominant are diff:

PASMeta_humanDom_diff=PASMeta %>% filter(PAS%in%DiffDom$HumanPAS) %>% mutate(Diff=Human-Chimp)

ggplot(PASMeta_humanDom_diff,aes(x=Human, y=Chimp))+geom_point() + geom_abline(slope=1, intercept = 0,col="red") +labs(title="PAS usage for different dominant, condition on Human")

Version	Author	Date
321219e	brimittleman	2020-04-07

ggplot(PASMeta_humanDom_diff,aes(x=Diff))+geom_histogram(bins=100) + labs(title="Difference in Human - Chimp for Human Dominant")

Version	Author	Date
321219e	brimittleman	2020-04-07

PASMeta_ChimpDom_diff=PASMeta %>% filter(PAS%in%DiffDom$ChimpPAS) %>% mutate(Diff=Human-Chimp)

ggplot(PASMeta_ChimpDom_diff,aes(x=Human, y=Chimp))+geom_point() + geom_abline(slope=1, intercept = 0,col="red") +labs(title="PAS usage for different dominant, condition on Chimp")

Version	Author	Date
321219e	brimittleman	2020-04-07

ggplot(PASMeta_ChimpDom_diff,aes(x=Diff))+geom_histogram(bins=100) + labs(title="Difference in Human - Chimp for Chimp Dominant")

Version	Author	Date
321219e	brimittleman	2020-04-07

ggplot(PASMeta_humanDom_diff,aes(x=Diff))+geom_histogram(bins=100, fill="#D95F02",alpha=.5) + labs(title="Human Usage - Chimp Usage \n Colored by dominant") + geom_histogram(data=PASMeta_ChimpDom_diff,aes(x=Diff), bins = 100, fill="#1B9E77", alpha=.5) + geom_vline(xintercept = mean(PASMeta_ChimpDom_diff$Diff), col="#1B9E77")+ geom_vline(xintercept = mean(PASMeta_humanDom_diff$Diff), col="#D95F02") + geom_histogram(bins=100, data=SameDom, aes(x=DiffinDom), alpha=.3)+ geom_vline(xintercept = mean(SameDom$DiffinDom))

Version	Author	Date
321219e	brimittleman	2020-04-07

mean(PASMeta_humanDom_diff$Diff)

[1] 0.106281

mean(PASMeta_ChimpDom_diff$Diff)

[1] -0.164446

Do this same analysis but by number of PAS in the gene.

PASMeta_humanDom_diffsmall= PASMeta_humanDom_diff %>% select(gene, Diff) %>% mutate(Species="Human")%>% full_join(PASpregene, by="gene")

PASMeta_ChimpDom_diffsmall= PASMeta_ChimpDom_diff %>% select(gene, Diff) %>% mutate(Species="Chimp")%>% full_join(PASpregene, by="gene")

SameDomSmall=SameDom %>% rename(Diff=DiffinDom) %>% select(gene, Diff) %>% mutate(Species="Both")%>% full_join(PASpregene, by="gene")



Alldiff=PASMeta_humanDom_diffsmall %>% bind_rows(PASMeta_ChimpDom_diffsmall) %>% bind_rows(SameDomSmall) %>% full_join(PASpregene, by="gene")



ggplot(PASMeta_humanDom_diffsmall,aes(x=Diff)) +geom_histogram(bins=100, fill="#D95F02",alpha=.5) + geom_histogram(data=PASMeta_ChimpDom_diffsmall,aes(x=Diff), bins = 100, fill="#1B9E77", alpha=.5) + geom_histogram(bins=100, data=SameDomSmall, aes(x=Diff), alpha=.3)+ facet_grid(~nPAS)

Warning: Removed 6796 rows containing non-finite values (stat_bin).

Warning: Removed 6796 rows containing non-finite values (stat_bin).

Warning: Removed 4143 rows containing non-finite values (stat_bin).

Version	Author	Date
321219e	brimittleman	2020-04-07

I want something a bit different dominant PAS in human - human value for dominant PAS in chimp

DiffDomfromH= DiffDom %>% select(Human, ChimpPAS) %>% rename(PAS=ChimpPAS, humanDom=Human) %>% inner_join(PASMeta, by="PAS")%>% mutate(Diff=humanDom-Human,Dom="Human") %>% select(gene,Dom, Diff) %>% inner_join(PASpregene, by="gene")%>% filter(nPAS<6)

DiffDomfromC= DiffDom %>% select(Chimp, HumanPAS) %>% rename(PAS=HumanPAS, ChimpDom=Chimp) %>% inner_join(PASMeta, by="PAS")%>% mutate(Diff=ChimpDom-Chimp,Dom="Chimp")%>% select(gene,Dom, Diff) %>% inner_join(PASpregene, by="gene") %>% filter(nPAS<6)


ggplot(DiffDomfromH,aes(x=Diff))+ geom_histogram(bins=50, fill="#D95F02",alpha=.5) + geom_histogram(data=DiffDomfromC, bins=50,fill="#1B9E77", alpha=.5 ) + facet_grid(~nPAS) + labs(x="Difference in Mean usage", title="Dominant PAS in species - same species value for \nthe 'dominant' in other species")

Version	Author	Date
321219e	brimittleman	2020-04-07

ggplot(DiffDomfromH,aes(x=Diff))+ geom_histogram(bins=50, fill="#D95F02",alpha=.5) + geom_histogram(data=DiffDomfromC, bins=50,fill="#1B9E77", alpha=.5 ) + labs(x="Difference in Mean usage", title="Dominant PAS in species - same species value for \nthe 'dominant' in other species")

Version	Author	Date
321219e	brimittleman	2020-04-07

sessionInfo()

R version 3.5.1 (2018-07-02)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)

Matrix products: default
BLAS/LAPACK: /software/openblas-0.2.19-el7-x86_64/lib/libopenblas_haswellp-r0.2.19.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] forcats_0.3.0   stringr_1.3.1   dplyr_0.8.0.1   purrr_0.3.2    
 [5] readr_1.3.1     tidyr_0.8.3     tibble_2.1.1    ggplot2_3.1.1  
 [9] tidyverse_1.2.1 workflowr_1.6.0

loaded via a namespace (and not attached):
 [1] tidyselect_0.2.5   reshape2_1.4.3     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        RColorBrewer_1.1-2 modelr_0.1.2      
[16] readxl_1.1.0       plyr_1.8.4         munsell_0.5.0     
[19] gtable_0.2.0       cellranger_1.1.0   rvest_0.3.2       
[22] evaluate_0.12      labeling_0.3       knitr_1.20        
[25] httpuv_1.4.5       broom_0.5.1        Rcpp_1.0.2        
[28] promises_1.0.1     scales_1.0.0       backports_1.1.2   
[31] jsonlite_1.6       fs_1.3.1           hms_0.4.2         
[34] digest_0.6.18      stringi_1.2.4      grid_3.5.1        
[37] rprojroot_1.3-2    cli_1.1.0          tools_3.5.1       
[40] magrittr_1.5       lazyeval_0.2.1     crayon_1.3.4      
[43] whisker_0.3-2      pkgconfig_2.0.2    xml2_1.2.0        
[46] lubridate_1.7.4    assertthat_0.2.0   rmarkdown_1.10    
[49] httr_1.3.1         rstudioapi_0.10    R6_2.3.0          
[52] nlme_3.1-137       git2r_0.26.1       compiler_3.5.1

Number of Conserved PAS

Briana Mittleman

4/7/2020