Package: profileplyr 1.23.0
profileplyr: Visualization and annotation of read signal over genomic ranges with profileplyr
Quick and straightforward visualization of read signal over genomic intervals is key for generating hypotheses from sequencing data sets (e.g. ChIP-seq, ATAC-seq, bisulfite/methyl-seq). Many tools both inside and outside of R and Bioconductor are available to explore these types of data, and they typically start with a bigWig or BAM file and end with some representation of the signal (e.g. heatmap). profileplyr leverages many Bioconductor tools to allow for both flexibility and additional functionality in workflows that end with visualization of the read signal.
Authors:
profileplyr_1.23.0.tar.gz
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profileplyr.pdf |profileplyr.html✨
profileplyr/json (API)
NEWS
# Install 'profileplyr' in R: |
install.packages('profileplyr', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
- K27ac_GRlist_hind_liver_top5000 - GRangesList of the top 5000 H3K27ac peaks from hindbrain and liver downloaded from ENCODE
- gene_list_character - Character vector of the top differentially expressed genes from hindbrain versus liver as measured by RNA-seq
- gene_list_dataframe - Dataframe of top differentially expressed genes from hindbrain versus liver as measured by RNA-seq
On BioConductor:profileplyr-1.23.0(bioc 3.21)profileplyr-1.22.0(bioc 3.20)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
chipseqdataimportsequencingchiponchipcoverage
Last updated 23 days agofrom:580fe4151f. Checks:OK: 1 NOTE: 4 WARNING: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 31 2024 |
R-4.5-win | NOTE | Oct 31 2024 |
R-4.5-linux | NOTE | Oct 31 2024 |
R-4.4-win | NOTE | Oct 31 2024 |
R-4.4-mac | WARNING | Oct 31 2024 |
R-4.3-win | NOTE | Oct 31 2024 |
R-4.3-mac | WARNING | Oct 31 2024 |
Exports:annotateRangesannotateRanges_greatas_profileplyrBamBigwig_to_chipProfileclusterRangesconvertToEnrichedHeatmapMatexport_deepToolsMatgenerateEnrichedHeatmapgenerateProfilePlotgroupByimport_deepToolsMatorderByparamssampleDatasampleData<-summarize
Dependencies:abindAnnotationDbiapeaplotaskpassbase64encBHBiobaseBiocGenericsBiocIOBiocParallelBiostringsbitbit64bitopsblobbootbslibcachemcaToolsChIPseekerchipseqcirclizecliclueclustercodetoolscolorspacecommonmarkComplexHeatmapcowplotcpp11crayoncrosstalkcurldata.tableDBIDelayedArraydeldirdigestdoParallelDOSEdplyrDTEnrichedHeatmapenrichplotevaluatefansifarverfastmapfastmatchfgseafontawesomeforeachformatRfsfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataGenomicAlignmentsGenomicFeaturesGenomicRangesGetoptLongggforceggfunggnewscaleggplot2ggplotifyggrepelggtangleggtreeGlobalOptionsglueGO.dbGOSemSimgplotsgridGraphicsgtablegtoolshighrhmshtmltoolshtmlwidgetshttpuvhttrhwriterigraphinterpIRangesisobanditeratorsjpegjquerylibjsonliteKEGGRESTKernSmoothknitrlabelinglambda.rlaterlatticelatticeExtralazyevallifecyclelocfitmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimemunsellnlmeopensslorg.Hs.eg.dborg.Mm.eg.dbpatchworkpheatmappillarpkgconfigplogrplotrixplyrpngpolyclippreprocessCoreprettyunitsprogresspromisespurrrpwalignqvalueR.methodsS3R.ooR.utilsR6rappdirsRColorBrewerRcppRcppEigenRCurlreshape2restfulrrGREATRhtslibrjsonrlangrmarkdownRsamtoolsRSQLitertracklayerS4ArraysS4VectorssassscalesscatterpieshapeshinyShortReadsnowsoGGisourcetoolsSparseArraystringistringrSummarizedExperimentsyssystemfontstibbletidyrtidyselecttidytreetifftinytextreeiotweenrTxDb.Hsapiens.UCSC.hg19.knownGeneTxDb.Hsapiens.UCSC.hg38.knownGeneTxDb.Mmusculus.UCSC.mm10.knownGeneTxDb.Mmusculus.UCSC.mm9.knownGeneUCSC.utilsutf8vctrsviridisLitewithrxfunXMLxtableXVectoryamlyulab.utilszlibbioc