Package: SARC 1.3.0

Krutik Patel

SARC: Statistical Analysis of Regions with CNVs

Imports a cov/coverage file (normalised read coverages from BAM files) and a cnv file (list of CNVs - similiar to a BED file) from WES/ WGS CNV (copy number variation) detection pipelines and utilises several metrics to weigh the likelihood of a sample containing a detected CNV being a true CNV or a false positive. Highly useful for diagnostic testing to filter out false positives to provide clinicians with fewer variants to interpret. SARC uniquely only used cov and csv (similiar to BED file) files which are the common CNV pipeline calling filetypes, and can be used as to supplement the Interactive Genome Browser (IGV) to generate many figures automatedly, which can be especially helpful in large cohorts with 100s-1000s of patients.

Authors:Krutik Patel [aut, cre]

SARC_1.3.0.tar.gz
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SARC.pdf |SARC.html
SARC/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/krutik6/sarc/issues

Datasets:

On BioConductor:SARC-1.3.0(bioc 3.20)SARC-1.2.0(bioc 3.19)

bioconductor-package

16 exports 0.71 score 194 dependencies

Last updated 2 months agofrom:a50c621e85

Exports:addExonsGenesanovaOnCNVcnvConfidencepasteExonsGenesphDunnetonCNVplotCNVplotCovPrepprepAnovaregionGrangeMakeregionMeanregionQuantilesregionSetregionSplitseeDistsetQDplotsetupCNVplot

Dependencies:abindAnnotationDbiaskpassbackportsbase64encBHBiobaseBiocBaseUtilsBiocGenericsBiocIOBiocParallelBiostringsbitbit64bitopsblobbootbroombslibcachemcallrcellrangerclassclicliprcodetoolscolorspaceconflictedcpp11crayoncrosstalkcurldata.tableDBIdbplyrDelayedArrayDEoptimRDescToolsdigestdplyrdtplyre1071evaluateExactexpmfansifarverfastmapfontawesomeforcatsformatRfsfutile.loggerfutile.optionsgarglegenericsGenomeInfoDbGenomeInfoDbDataGenomicAlignmentsGenomicFeaturesGenomicRangesggplot2gldgluegoogledrivegooglesheets4gridExtragtablehavenhighrhmshtmltoolshtmlwidgetshttridsIRangesisobandjquerylibjsonliteKEGGRESTknitrlabelinglambda.rlaterlatticelazyevallifecyclelmomlubridatemagrittrMASSmathjaxrMatrixMatrixGenericsMatrixModelsmatrixStatsmemoisemetapmgcvmimemnormtmodelrmultcompmulttestmunsellmutossmvtnormnlmenumDerivopensslpillarpkgconfigplogrplotlyplotrixplyrplyrangespngprettyunitsprocessxprogresspromisesproxypspurrrqqconfquantregR6raggRaggedExperimentrappdirsrbibutilsRColorBrewerRcppRCurlRdpackreadrreadxlrematchrematch2reprexreshape2restfulrRhtslibrjsonrlangrmarkdownrobustbaserootSolveRsamtoolsRSQLiterstudioapirtracklayerrvestS4ArraysS4VectorssandwichsassscalesselectrsnsnowSparseArraySparseMstringistringrSummarizedExperimentsurvivalsyssystemfontstextshapingTFisherTH.datatibbletidyrtidyselecttidyversetimechangetinytextzdbUCSC.utilsutf8uuidvctrsviridisLitevroomwithrxfunXMLxml2XVectoryamlzlibbioczoo

Tutorial of the SARC R Package. Flagging the confidence of CNVs from WES/ WGS cohorts.

Rendered fromSARC_guide.Rmdusingknitr::rmarkdownon Jun 30 2024.

Last update: 2023-08-17
Started: 2023-05-27

Readme and manuals

Help Manual

Help pageTopics
addExonsGenesaddExonsGenes
anovaOnCNVanovaOnCNV
cnvConfidencecnvConfidence
pasteExonsGenespasteExonsGenes
phDunnetonCNVphDunnetonCNV
plotCNVplotCNV
plotCovPrepplotCovPrep
prepAnovaprepAnova
regionGrangeMakeregionGrangeMake
regionMeanregionMean
regionQuantilesregionQuantiles
regionSetregionSet
regionSplitregionSplit
seeDistseeDist
setQDPlotsetQDplot
setupCNVplotsetupCNVplot
test cnvtest_cnv
test cnv 2test_cnv2
test coverage filetest_cov