Package: SOMNiBUS 1.13.0

Kathleen Klein

SOMNiBUS: Smooth modeling of bisulfite sequencing

This package aims to analyse count-based methylation data on predefined genomic regions, such as those obtained by targeted sequencing, and thus to identify differentially methylated regions (DMRs) that are associated with phenotypes or traits. The method is built a rich flexible model that allows for the effects, on the methylation levels, of multiple covariates to vary smoothly along genomic regions. At the same time, this method also allows for sequencing errors and can adjust for variability in cell type mixture.

Authors:Kaiqiong Zhao [aut], Kathleen Klein [cre], Audrey Lemaçon [ctb, ctr], Simon Laurin-Lemay [ctb, ctr], My Intelligent Machines Inc. [ctr], Celia Greenwood [ths, aut]

SOMNiBUS_1.13.0.tar.gz
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SOMNiBUS.pdf |SOMNiBUS.html✨
SOMNiBUS/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/kaiqiong/somnibus/issues

Datasets:
  • RAdat - Methylation data from a rheumatoid arthritis study
  • RAdat2 - A simulated methylation dataset based on a real data.

On BioConductor:SOMNiBUS-1.13.0(bioc 3.20)SOMNiBUS-1.12.0(bioc 3.19)

dnamethylationregressionepigeneticsdifferentialmethylationsequencingfunctionalprediction

4.00 score 1 stars 3 scripts 128 downloads 1 mentions 15 exports 133 dependencies

Last updated 8 months agofrom:ad81567efc. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 13 2024
R-4.5-winNOTEOct 13 2024
R-4.5-linuxNOTEOct 13 2024
R-4.4-winNOTEOct 13 2024
R-4.4-macNOTEOct 13 2024
R-4.3-winNOTEOct 13 2024
R-4.3-macNOTEOct 13 2024

Exports:binomRegMethModelbinomRegMethModelPlotbinomRegMethModelPredbinomRegMethModelSimbinomRegMethPredPlotformatFromBismarkformatFromBSmoothformatFromBSseqrunSOMNiBUSsplitDataByBedsplitDataByChromatinsplitDataByDensitysplitDataByGenesplitDataByGRangessplitDataByRegion

Dependencies:abindAnnotationDbiAnnotationHubannotatraskpassassortheadbeachmatBHBiobaseBiocFileCacheBiocGenericsBiocIOBiocManagerBiocParallelBiocVersionBiostringsbitbit64bitopsblobBSgenomebsseqcachemclicliprcodetoolscolorspacecpp11crayoncurldata.tableDBIdbplyrDelayedArrayDelayedMatrixStatsdplyrfansifarverfastmapfilelockformatRfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataGenomicAlignmentsGenomicFeaturesGenomicRangesggplot2gluegtablegtoolsHDF5ArrayhmshttrIRangesisobandjsonliteKEGGRESTlabelinglambda.rlatticelifecyclelimmalocfitmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimemunsellnlmeopensslpermutepillarpkgconfigplogrplyrpngprettyunitsprogresspurrrR.methodsS3R.ooR.utilsR6rappdirsRColorBrewerRcppRCurlreadrregioneRreshape2restfulrrhdf5rhdf5filtersRhdf5libRhtslibrjsonrlangRsamtoolsRSQLitertracklayerS4ArraysS4VectorsscalessnowSparseArraysparseMatrixStatsstatmodstringistringrSummarizedExperimentsystibbletidyrtidyselecttzdbUCSC.utilsutf8vctrsVGAMviridisLitevroomwithrXMLXVectoryamlzlibbioc

Analyzing Targeted Bisulfite Sequencing data with SOMNiBUS

Kaiqiong Zhao

Rendered fromSOMNiBUS.Rmdusingknitr::rmarkdownon Oct 13 2024.

Last update: 2023-07-17
Started: 2019-01-24

Readme and manuals

Help Manual

Help pageTopics
A smoothed-EM algorithm to estimate covariate effects and test regional association in Bisulfite Sequencing-derived methylation databinomRegMethModel
Plot the smooth covariate effectbinomRegMethModelPlot
A smoothed-EM algorithm to estimate covariate effects and test regional association in Bisulfite Sequencing-derived methylation databinomRegMethModelPred
Simulate Bisulfite sequencing data from specified smooth covariate effectsbinomRegMethModelSim
Plot the predicted methylation levelsbinomRegMethPredPlot
Parsing output from the Bismark alignment suiteformatFromBismark
Parsing output from the BSmooth alignment suiteformatFromBSmooth
Parsing output from the BSseq packageformatFromBSseq
Methylation data from a rheumatoid arthritis studyRAdat
A simulated methylation dataset based on a real data.RAdat2
Wrapper function running the smoothed-EM algorithm to estimate covariate effects and test regional association in Bisulfite Sequencing-derived methylation datarunSOMNiBUS
Split methylation data into regions based on the genomic annotationssplitDataByBed
Split methylation data into regions based on the chromatin statessplitDataByChromatin
Split methylation data into regions based on the density of CpGssplitDataByDensity
Split methylation data into regions based on the genes annotationssplitDataByGene
Split methylation data into regions based on the genomic annotationssplitDataByGRanges
Split methylation data into regions based on the spacing of CpGssplitDataByRegion