Different Dominant Length Differences

Last updated: 2020-04-21

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: 95685ef

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/AREstabilityScores.Rmd
    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/DTUTR.sh
    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/FindDomXCutoff.py
    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/GetTopminus2Usage.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/NuclearDTUTR.err
    Untracked:  code/NuclearDTUTRt.out
    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/RunNewDom.err
    Untracked:  code/RunNewDom.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/runNewDom.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/ARE_Elements/
    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/DomDefGreaterX/
    Untracked:  data/DomStructure_4/
    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/miRNA/
    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/ExploredAPA_DF.Rmd
    Modified:   analysis/MMExpreiment.Rmd
    Modified:   analysis/NewdomanddAPA.Rmd
    Modified:   analysis/OppositeMap.Rmd
    Modified:   analysis/TotalDomStructure.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	95685ef	brimittleman	2020-04-21	add length diff analysis

I found a strong enrichment for genes with different dominant PAS in the set of DE genes. ##.4 set
I will start with the 0.4 set. Then I can expand.

library(workflowr)

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

library(ggpubr)

Loading required package: ggplot2

Loading required package: magrittr

library(tidyverse)

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

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

── Conflicts ───────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
✖ tidyr::extract()   masks magrittr::extract()
✖ dplyr::filter()    masks stats::filter()
✖ dplyr::lag()       masks stats::lag()
✖ purrr::set_names() masks magrittr::set_names()

PAS=read.table("../data/PAS_doubleFilter/PAS_5perc_either_HumanCoord_BothUsage_meta_doubleFilter.txt", header = T, stringsAsFactors = F)
MetaCol=colnames(PAS)

nameID=read.table("../../genome_anotation_data/ensemble_to_genename.txt",sep="\t", header = T, stringsAsFactors = F)
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) %>% mutate(DE=ifelse(adj.P.Val<=.05, "Yes","No")) %>% select(gene,DE)
DE_yes= DE %>% filter(DE=="Yes")

HumanRes=read.table("../data/DomDefGreaterX/Human_AllGenes_DiffTop.txt", col.names = c("Human_PAS", "gene","Human_DiffDom"),stringsAsFactors = F)

ChimpRes=read.table("../data/DomDefGreaterX/Chimp_AllGenes_DiffTop.txt", col.names = c("Chimp_PAS", "gene","Chimp_DiffDom"),stringsAsFactors = F)

BothRes=HumanRes %>% inner_join(ChimpRes,by="gene")

BothRes_40=BothRes %>% filter(Chimp_DiffDom >=0.4 | Human_DiffDom>=0.4) %>% mutate(Set= ifelse(Human_PAS==Chimp_PAS,"Same", "Different"),cut=40)

ReswithDE= BothRes_40  %>% select(-Human_DiffDom,-Chimp_DiffDom) %>% gather("species","PAS", -gene, -Set, -cut) %>%  inner_join(DE, by="gene") 

ReswithDE_same= ReswithDE %>% filter(Set=="Same")
ReswithDE_diff= ReswithDE %>% filter(Set=="Different")

Pull in the gene annotation so I can get the length. In human first

genes=read.table("../../genome_anotation_data/hg38_refseq_anno/hg38_ncbiRefseq_GenesParsed_sort.bed", col.names = c("chr", "geneStart", "geneEnd", "gene", "score", "strand"), stringsAsFactors = F) %>% select(geneStart, geneEnd, gene)

I need to add the meta data for the different PAS.

ReswithDE_diffMeta=ReswithDE_diff %>% inner_join(PAS, by=c("gene","PAS")) %>% mutate(Center=start+100) %>% inner_join(genes, by="gene") %>% mutate(Dist2TSS=ifelse(strandFix=="+", Center-geneStart, geneEnd-Center))

ReswithDE_diffMetaSM= ReswithDE_diffMeta %>% select(gene, species, DE, Dist2TSS) %>% spread(species, Dist2TSS)

Look at the difference in size by DE:

chimp-human

= chimp longer
= human longer

This is the difference in isoform length (not accounting for splce differences)

ReswithDE_diffMetaSM_diff= ReswithDE_diffMetaSM %>% mutate(Diff=Chimp_PAS-Human_PAS)

ggplot(ReswithDE_diffMetaSM_diff, aes(x=Diff,by=DE, col=DE) )+ stat_ecdf()

Look at the DE:

ReswithDE_diffMetaSM_diff_DE= ReswithDE_diffMetaSM_diff %>% filter(DE=="Yes") %>% mutate(longer=ifelse(Diff>0, "Chimp", "Human"))

ReswithDE_diffMetaSM_diff_DE %>% group_by(longer) %>% summarise(n=n())

# A tibble: 2 x 2
  longer     n
  <chr>  <int>
1 Chimp     44
2 Human     32

ggplot(ReswithDE_diffMetaSM_diff_DE, aes(y=abs(Diff),x=longer))+geom_boxplot() + stat_compare_means()

I want to add the information about which has higher expression:

DEeffect= 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) %>% select(gene, logFC) %>% mutate(directionDE=ifelse(logFC>=1, "Chimp", "Human"))

LengthDiffandDe=ReswithDE_diffMetaSM_diff_DE %>% inner_join(DEeffect, by="gene")

tableg=LengthDiffandDe %>% group_by(longer, directionDE) %>% summarise(n=n())
tableg

# A tibble: 4 x 3
# Groups:   longer [2]
  longer directionDE     n
  <chr>  <chr>       <int>
1 Chimp  Chimp          10
2 Chimp  Human          34
3 Human  Chimp           9
4 Human  Human          23

More of these are upregulated in human

to run a chi sq test i need to spread this:

tabler= tableg %>% spread(directionDE, n) %>% column_to_rownames("longer")

chisq.test(tabler)


    Pearson's Chi-squared test with Yates' continuity correction

data:  tabler
X-squared = 0.07197, df = 1, p-value = 0.7885

This is not outside of expectation.

Does not seem like length and direction are confounded.

All cutoffs

Expand to larger set:

I need the different ones, then i get the distance for each from the gene file and get the longer isoform, then add in the DE direction

Probably easier to do it one at a time rather than a loop.

BothRes_10=BothRes %>% filter(Chimp_DiffDom >=0.1 | Human_DiffDom>=0.1) %>% mutate(Set= ifelse(Human_PAS==Chimp_PAS,"Same", "Different"),cut=10) 
BothRes_20=BothRes %>% filter(Chimp_DiffDom >=0.2 | Human_DiffDom>=0.2) %>% mutate(Set= ifelse(Human_PAS==Chimp_PAS,"Same", "Different"),cut=20)
BothRes_30=BothRes %>% filter(Chimp_DiffDom >=0.3 | Human_DiffDom>=0.3) %>% mutate(Set= ifelse(Human_PAS==Chimp_PAS,"Same", "Different"),cut=30)
#BothRes_40=BothRes %>% filter(Chimp_DiffDom >=0.4 | Human_DiffDom>=0.4) %>% mutate(Set= ifelse(Human_PAS==Chimp_PAS,"Same", "Different"),cut=40)
BothRes_50=BothRes %>% filter(Chimp_DiffDom >=0.5 | Human_DiffDom>=0.5) %>% mutate(Set= ifelse(Human_PAS==Chimp_PAS,"Same", "Different"),cut=50)
BothRes_60=BothRes %>% filter(Chimp_DiffDom >=0.6 | Human_DiffDom>=0.6) %>% mutate(Set= ifelse(Human_PAS==Chimp_PAS,"Same", "Different"),cut=60)
BothRes_70=BothRes %>% filter(Chimp_DiffDom >=0.7 | Human_DiffDom>=0.7) %>% mutate(Set= ifelse(Human_PAS==Chimp_PAS,"Same", "Different"),cut=70)
BothRes_80=BothRes %>% filter(Chimp_DiffDom >=0.8 | Human_DiffDom>=0.8) %>% mutate(Set= ifelse(Human_PAS==Chimp_PAS,"Same", "Different"),cut=80)
BothRes_90=BothRes %>% filter(Chimp_DiffDom >=0.9 | Human_DiffDom>=0.9) %>% mutate(Set= ifelse(Human_PAS==Chimp_PAS,"Same", "Different"),cut=90)

10

ReswithDE10= BothRes_10  %>% 
  filter(Set=="Different") %>%
  select(-Human_DiffDom,-Chimp_DiffDom) %>% 
  gather("species","PAS", -gene, -Set, -cut) %>% 
  inner_join(DE, by="gene") %>% 
  inner_join(PAS, by=c("gene","PAS")) %>%
  mutate(Center=start+100) %>% 
  inner_join(genes, by="gene") %>% 
  mutate(Dist2TSS=ifelse(strandFix=="+", Center-geneStart, geneEnd-Center))%>% 
  select(gene, species, DE, Dist2TSS) %>%
  spread(species, Dist2TSS)%>% 
  mutate(Diff=Chimp_PAS-Human_PAS) %>% 
  filter(DE=="Yes") %>% 
  mutate(longer=ifelse(Diff>0, "Chimp", "Human"))%>% 
  inner_join(DEeffect, by="gene")

tableg10=ReswithDE10 %>% group_by(longer, directionDE) %>% summarise(n=n()) %>% spread(directionDE, n) %>% column_to_rownames("longer")
tableg10

      Chimp Human
Chimp    53   247
Human    31    99

chisq.test(tableg10)


    Pearson's Chi-squared test with Yates' continuity correction

data:  tableg10
X-squared = 1.8278, df = 1, p-value = 0.1764

20

ReswithDE20= BothRes_20  %>% 
  filter(Set=="Different") %>%
  select(-Human_DiffDom,-Chimp_DiffDom) %>% 
  gather("species","PAS", -gene, -Set, -cut) %>% 
  inner_join(DE, by="gene") %>% 
  inner_join(PAS, by=c("gene","PAS")) %>%
  mutate(Center=start+100) %>% 
  inner_join(genes, by="gene") %>% 
  mutate(Dist2TSS=ifelse(strandFix=="+", Center-geneStart, geneEnd-Center))%>% 
  select(gene, species, DE, Dist2TSS) %>%
  spread(species, Dist2TSS)%>% 
  mutate(Diff=Chimp_PAS-Human_PAS) %>% 
  filter(DE=="Yes") %>% 
  mutate(longer=ifelse(Diff>0, "Chimp", "Human"))%>% 
  inner_join(DEeffect, by="gene")

tableg20=ReswithDE20 %>% group_by(longer, directionDE) %>% summarise(n=n()) %>% spread(directionDE, n) %>% column_to_rownames("longer")
tableg20

      Chimp Human
Chimp    26   127
Human    17    51

chisq.test(tableg20)


    Pearson's Chi-squared test with Yates' continuity correction

data:  tableg20
X-squared = 1.4487, df = 1, p-value = 0.2287

30

ReswithDE30= BothRes_30  %>% 
  filter(Set=="Different") %>%
  select(-Human_DiffDom,-Chimp_DiffDom) %>% 
  gather("species","PAS", -gene, -Set, -cut) %>% 
  inner_join(DE, by="gene") %>% 
  inner_join(PAS, by=c("gene","PAS")) %>%
  mutate(Center=start+100) %>% 
  inner_join(genes, by="gene") %>% 
  mutate(Dist2TSS=ifelse(strandFix=="+", Center-geneStart, geneEnd-Center))%>% 
  select(gene, species, DE, Dist2TSS) %>%
  spread(species, Dist2TSS)%>% 
  mutate(Diff=Chimp_PAS-Human_PAS) %>% 
  filter(DE=="Yes") %>% 
  mutate(longer=ifelse(Diff>0, "Chimp", "Human"))%>% 
  inner_join(DEeffect, by="gene")

tableg30=ReswithDE30 %>% group_by(longer, directionDE) %>% summarise(n=n()) %>% spread(directionDE, n) %>% column_to_rownames("longer")
tableg30

      Chimp Human
Chimp    14    54
Human    14    34

chisq.test(tableg30)


    Pearson's Chi-squared test with Yates' continuity correction

data:  tableg30
X-squared = 0.71084, df = 1, p-value = 0.3992

50

ReswithDE50= BothRes_50  %>% 
  filter(Set=="Different") %>%
  select(-Human_DiffDom,-Chimp_DiffDom) %>% 
  gather("species","PAS", -gene, -Set, -cut) %>% 
  inner_join(DE, by="gene") %>% 
  inner_join(PAS, by=c("gene","PAS")) %>%
  mutate(Center=start+100) %>% 
  inner_join(genes, by="gene") %>% 
  mutate(Dist2TSS=ifelse(strandFix=="+", Center-geneStart, geneEnd-Center))%>% 
  select(gene, species, DE, Dist2TSS) %>%
  spread(species, Dist2TSS)%>% 
  mutate(Diff=Chimp_PAS-Human_PAS) %>% 
  filter(DE=="Yes") %>% 
  mutate(longer=ifelse(Diff>0, "Chimp", "Human"))%>% 
  inner_join(DEeffect, by="gene")

tableg50=ReswithDE50 %>% group_by(longer, directionDE) %>% summarise(n=n()) %>% spread(directionDE, n) %>% column_to_rownames("longer")
tableg50

      Chimp Human
Chimp     4    23
Human     7    17

chisq.test(tableg50)


    Pearson's Chi-squared test with Yates' continuity correction

data:  tableg50
X-squared = 0.81499, df = 1, p-value = 0.3667

60

ReswithDE60= BothRes_60  %>% 
  filter(Set=="Different") %>%
  select(-Human_DiffDom,-Chimp_DiffDom) %>% 
  gather("species","PAS", -gene, -Set, -cut) %>% 
  inner_join(DE, by="gene") %>% 
  inner_join(PAS, by=c("gene","PAS")) %>%
  mutate(Center=start+100) %>% 
  inner_join(genes, by="gene") %>% 
  mutate(Dist2TSS=ifelse(strandFix=="+", Center-geneStart, geneEnd-Center))%>% 
  select(gene, species, DE, Dist2TSS) %>%
  spread(species, Dist2TSS)%>% 
  mutate(Diff=Chimp_PAS-Human_PAS) %>% 
  filter(DE=="Yes") %>% 
  mutate(longer=ifelse(Diff>0, "Chimp", "Human"))%>% 
  inner_join(DEeffect, by="gene")

tableg60=ReswithDE60 %>% group_by(longer, directionDE) %>% summarise(n=n()) %>% spread(directionDE, n) %>% column_to_rownames("longer")
tableg60

      Chimp Human
Chimp     3    16
Human     3    14

chisq.test(tableg60)

Warning in chisq.test(tableg60): Chi-squared approximation may be incorrect


    Pearson's Chi-squared test with Yates' continuity correction

data:  tableg60
X-squared = 1.3188e-31, df = 1, p-value = 1

70

ReswithDE70= BothRes_70  %>% 
  filter(Set=="Different") %>%
  select(-Human_DiffDom,-Chimp_DiffDom) %>% 
  gather("species","PAS", -gene, -Set, -cut) %>% 
  inner_join(DE, by="gene") %>% 
  inner_join(PAS, by=c("gene","PAS")) %>%
  mutate(Center=start+100) %>% 
  inner_join(genes, by="gene") %>% 
  mutate(Dist2TSS=ifelse(strandFix=="+", Center-geneStart, geneEnd-Center))%>% 
  select(gene, species, DE, Dist2TSS) %>%
  spread(species, Dist2TSS)%>% 
  mutate(Diff=Chimp_PAS-Human_PAS) %>% 
  filter(DE=="Yes") %>% 
  mutate(longer=ifelse(Diff>0, "Chimp", "Human"))%>% 
  inner_join(DEeffect, by="gene")

tableg70=ReswithDE70 %>% group_by(longer, directionDE) %>% summarise(n=n()) %>% spread(directionDE, n) %>% column_to_rownames("longer") %>% replace_na(list(Chimp=0, Human=0))
tableg70

      Chimp Human
Chimp     2    10
Human     0     6

chisq.test(tableg70)

Warning in chisq.test(tableg70): Chi-squared approximation may be incorrect


    Pearson's Chi-squared test with Yates' continuity correction

data:  tableg70
X-squared = 0.070312, df = 1, p-value = 0.7909

80

ReswithDE80= BothRes_80  %>% 
  filter(Set=="Different") %>%
  select(-Human_DiffDom,-Chimp_DiffDom) %>% 
  gather("species","PAS", -gene, -Set, -cut) %>% 
  inner_join(DE, by="gene") %>% 
  inner_join(PAS, by=c("gene","PAS")) %>%
  mutate(Center=start+100) %>% 
  inner_join(genes, by="gene") %>% 
  mutate(Dist2TSS=ifelse(strandFix=="+", Center-geneStart, geneEnd-Center))%>% 
  select(gene, species, DE, Dist2TSS) %>%
  spread(species, Dist2TSS)%>% 
  mutate(Diff=Chimp_PAS-Human_PAS) %>% 
  filter(DE=="Yes") %>% 
  mutate(longer=ifelse(Diff>0, "Chimp", "Human"))%>% 
  inner_join(DEeffect, by="gene")

tableg80=ReswithDE80 %>% group_by(longer, directionDE) %>% summarise(n=n()) %>% spread(directionDE, n) %>% column_to_rownames("longer")%>% replace_na(list(Chimp=0, Human=0))
tableg80

      Human
Chimp     8
Human     3

chisq.test(tableg80)


    Chi-squared test for given probabilities

data:  tableg80
X-squared = 2.2727, df = 1, p-value = 0.1317

90

ReswithDE90= BothRes_90  %>% 
  filter(Set=="Different") %>%
  select(-Human_DiffDom,-Chimp_DiffDom) %>% 
  gather("species","PAS", -gene, -Set, -cut) %>% 
  inner_join(DE, by="gene") %>% 
  inner_join(PAS, by=c("gene","PAS")) %>%
  mutate(Center=start+100) %>% 
  inner_join(genes, by="gene") %>% 
  mutate(Dist2TSS=ifelse(strandFix=="+", Center-geneStart, geneEnd-Center))%>% 
  select(gene, species, DE, Dist2TSS) %>%
  spread(species, Dist2TSS)%>% 
  mutate(Diff=Chimp_PAS-Human_PAS) %>% 
  filter(DE=="Yes") %>% 
  mutate(longer=ifelse(Diff>0, "Chimp", "Human"))%>% 
  inner_join(DEeffect, by="gene")

tableg90=ReswithDE90 %>% group_by(longer, directionDE) %>% summarise(n=n()) %>% spread(directionDE, n) %>% column_to_rownames("longer")%>% replace_na(list(Chimp=0, Human=0))
tableg90

      Human
Chimp     5
Human     1

chisq.test(tableg90)

Warning in chisq.test(tableg90): Chi-squared approximation may be incorrect


    Chi-squared test for given probabilities

data:  tableg90
X-squared = 2.6667, df = 1, p-value = 0.1025

All pvalue:

pvalues=c(chisq.test(tableg90)$p.value,chisq.test(tableg80)$p.value,chisq.test(tableg80)$p.value,chisq.test(tableg70)$p.value,chisq.test(tableg60)$p.value,chisq.test(tableg50)$p.value,chisq.test(tabler)$p.value,chisq.test(tableg30)$p.value,chisq.test(tableg20)$p.value, chisq.test(tableg10)$p.value)

Warning in chisq.test(tableg90): Chi-squared approximation may be incorrect

Warning in chisq.test(tableg70): Chi-squared approximation may be incorrect

Warning in chisq.test(tableg60): Chi-squared approximation may be incorrect

pvalues

 [1] 0.1024704 0.1316680 0.1316680 0.7908823 1.0000000 0.3666503 0.7884902
 [8] 0.3991644 0.2287363 0.1763932

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    tidyverse_1.2.1
 [9] ggpubr_0.2      magrittr_1.5    ggplot2_3.1.1   workflowr_1.6.0

loaded via a namespace (and not attached):
 [1] tidyselect_0.2.5 haven_1.1.2      lattice_0.20-38  colorspace_1.3-2
 [5] generics_0.0.2   htmltools_0.3.6  yaml_2.2.0       utf8_1.1.4      
 [9] rlang_0.4.0      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     plyr_1.8.4      
[17] munsell_0.5.0    gtable_0.2.0     cellranger_1.1.0 rvest_0.3.2     
[21] evaluate_0.12    labeling_0.3     knitr_1.20       httpuv_1.4.5    
[25] fansi_0.4.0      broom_0.5.1      Rcpp_1.0.2       promises_1.0.1  
[29] scales_1.0.0     backports_1.1.2  jsonlite_1.6     fs_1.3.1        
[33] hms_0.4.2        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      lazyeval_0.2.1  
[41] crayon_1.3.4     whisker_0.3-2    pkgconfig_2.0.2  xml2_1.2.0      
[45] lubridate_1.7.4  assertthat_0.2.0 rmarkdown_1.10   httr_1.3.1      
[49] rstudioapi_0.10  R6_2.3.0         nlme_3.1-137     git2r_0.26.1    
[53] compiler_3.5.1

Different Dominant Length Differences

Briana Mittleman

4/21/2020

All cutoffs

10

20

30

50

60

70

80

90

All pvalue: