Package: gcapc 1.31.0
Mingxiang Teng
gcapc: GC Aware Peak Caller
Peak calling for ChIP-seq data with consideration of potential GC bias in sequencing reads. GC bias is first estimated with generalized linear mixture models using effective GC strategy, then applied into peak significance estimation.
Authors:
gcapc_1.31.0.tar.gz
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gcapc.pdf |gcapc.html✨
gcapc/json (API)
NEWS
| # Install 'gcapc' in R: |
| install.packages('gcapc', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/tengmx/gcapc/issues
On BioConductor:gcapc-1.29.0(bioc 3.20)gcapc-1.28.0(bioc 3.19)
sequencingchipseqbatcheffectpeakdetection
Last updated 23 days agofrom:35dd473587. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 30 2024 |
| R-4.5-win | OK | Oct 31 2024 |
| R-4.5-linux | OK | Oct 30 2024 |
| R-4.4-win | OK | Oct 31 2024 |
| R-4.4-mac | OK | Oct 31 2024 |
| R-4.3-win | OK | Oct 31 2024 |
| R-4.3-mac | OK | Oct 31 2024 |
Exports:bindWidthgcapcPeaksgcEffectspeaksCATread5endCoveragerefinePeaksrefineSites
Dependencies:abindaskpassBHBiobaseBiocGenericsBiocIOBiocParallelBiostringsbitopsBSgenomecodetoolscpp11crayoncurlDelayedArrayformatRfutile.loggerfutile.optionsGenomeInfoDbGenomeInfoDbDataGenomicAlignmentsGenomicRangeshttrIRangesjsonlitelambda.rlatticeMASSMatrixMatrixGenericsmatrixStatsmimeopensslR6RCurlrestfulrRhtslibrjsonRsamtoolsrtracklayerS4ArraysS4VectorssnowSparseArraySummarizedExperimentsysUCSC.utilsXMLXVectoryamlzlibbioc
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| ChIP-seq Binding Width And Peak Window Size Estimation | bindWidth |
| GC Effects Aware Peak Calling | gcapcPeaks |
| ChIP-seq GC Effects Estimation | gcEffects |
| CATplot of Peaks | peaksCAT |
| Reads Coverage Using 5-end Base | read5endCoverage |
| Refine Peaks with GC Effects | refinePeaks |
| Adjust ChIP-seq Read Count Table | refineSites |
