Package: vmrseq 1.4.0

Ning Shen

vmrseq: Probabilistic Modeling of Single-cell Methylation Heterogeneity

High-throughput single-cell measurements of DNA methylation allows studying inter-cellular epigenetic heterogeneity, but this task faces the challenges of sparsity and noise. We present vmrseq, a statistical method that overcomes these challenges and identifies variably methylated regions accurately and robustly.

Authors:Ning Shen [aut, cre]

vmrseq_1.4.0.tar.gz
vmrseq_1.4.0.zip(r-4.7)vmrseq_1.4.0.zip(r-4.6)vmrseq_1.4.0.zip(r-4.5)
vmrseq_1.4.0.tgz(r-4.6-any)vmrseq_1.4.0.tgz(r-4.5-any)
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vmrseq_1.4.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
vmrseq/json (API)
NEWS

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

Bug tracker:https://github.com/nshen7/vmrseq/issues

Datasets:

On BioConductor:vmrseq-1.5.0(bioc 3.24)vmrseq-1.4.0(bioc 3.23)

softwareimmunooncologydnamethylationepigeneticssinglecellsequencingwholegenomecomputational-biologydimensionality-reductionepigenomics-workflowhidden-markov-modelprobabilistic-models

5.18 score 10 stars 5 scripts 248 downloads 8 exports 180 dependencies

Last updated from:4b0c9831aa (on RELEASE_3_23). Checks:8 NOTE, 2 OK. Indexed: no.

TargetResultTimeFilesSyslog
bioc-checksNOTE204
linux-devel-x86_64NOTE504
source / vignettesOK362
linux-release-x86_64NOTE496
macos-release-arm64NOTE347
macos-oldrel-arm64NOTE244
windows-develNOTE418
windows-releaseNOTE431
windows-oldrelNOTE424
wasm-releaseOK204

Exports:HDF5NAdrop2matrixpoolDataregionSummarytpEstimatetpPlotvmrseqFitvmrseqOptimControlvmrseqSmooth

Dependencies:abindAnnotationDbiarulesaskpassbase64encBHBiobaseBiocGenericsBiocIObiocmakeBiocParallelBiostringsbitbit64bitopsblobbrewbriobslibbumphuntercachemcallrcigarilloclicliprcodetoolscommonmarkcpp11crayoncredentialscurldata.tableDBIDelayedArraydescdevtoolsdiffobjdigestdir.expirydoRNGdownlitdplyrellipsisevaluatefansifarverfastmapfilelockfloatfontawesomeforeachformatRfsfutile.loggerfutile.optionsgamlss.distgenericsGenomicAlignmentsGenomicFeaturesGenomicRangesgertggplot2gitcredsgluegtableh5mreadHDF5Arrayhighrhtmltoolshtmlwidgetshttpuvhttrhttr2iniIRangesirlbaisobanditeratorsjquerylibjsonliteKEGGRESTknitrlabelinglambda.rlaterlatticelifecyclelimmalocfitmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemimeminiUIopensslotelpakpillarpkgbuildpkgconfigpkgdownpkgloadpngpraiseprettyunitsprocessxprofvispromisesproxypspurrrR6raggrappdirsrcmdcheckRColorBrewerRcppRcppProgressRCurlrecommenderlabrecosystemregistryrestfulrrhdf5rhdf5filtersRhdf5libRhtslibrjsonrlangrmarkdownrngtoolsroxygen2rprojrootRsamtoolsRSQLiterstudioapirtracklayerrversionsS4ArraysS4VectorsS7sassscalesSeqinfosessioninfoshinysnowsourcetoolsSparseArraystatmodstringistringrSummarizedExperimentsyssystemfontstestthattextshapingtibbletidyrtidyselecttinytexurlcheckerusethisutf8vctrsviridisLitewaldowhiskerwithrxfunXMLxml2xopenxtableXVectoryamlzip

Analyzing single-cell bisulfite sequencing data with vmrseq

Ning Shen

Rendered fromvmrseq-vignette.Rmdusingknitr::rmarkdownon May 30 2026.

Last update: 2025-04-30
Started: 2023-05-24