Package: gcapc 1.29.0

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:Mingxiang Teng and Rafael A. Irizarry

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NEWS

# Install 'gcapc' in R:
install.packages('gcapc', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/tengmx/gcapc/issues

On BioConductor:gcapc-1.29.0(bioc 3.20)gcapc-1.28.0(bioc 3.19)

bioconductor-package

7 exports 0.82 score 51 dependencies

Last updated 2 months agofrom:0e8092acdb

Exports:bindWidthgcapcPeaksgcEffectspeaksCATread5endCoveragerefinePeaksrefineSites

Dependencies:abindaskpassBHBiobaseBiocGenericsBiocIOBiocParallelBiostringsbitopsBSgenomecodetoolscpp11crayoncurlDelayedArrayformatRfutile.loggerfutile.optionsGenomeInfoDbGenomeInfoDbDataGenomicAlignmentsGenomicRangeshttrIRangesjsonlitelambda.rlatticeMASSMatrixMatrixGenericsmatrixStatsmimeopensslR6RCurlrestfulrRhtslibrjsonRsamtoolsrtracklayerS4ArraysS4VectorssnowSparseArraySummarizedExperimentsysUCSC.utilsXMLXVectoryamlzlibbioc

The gcapc user's guide

Rendered fromgcapc.Rmdusingknitr::rmarkdownon Jun 30 2024.

Last update: 2017-06-08
Started: 2016-10-19