Package: infercnv 1.23.0

Christophe Georgescu

infercnv: Infer Copy Number Variation from Single-Cell RNA-Seq Data

Using single-cell RNA-Seq expression to visualize CNV in cells.

Authors:Timothy Tickle [aut], Itay Tirosh [aut], Christophe Georgescu [aut, cre], Maxwell Brown [aut], Brian Haas [aut]

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infercnv.pdf |infercnv.html✨
infercnv/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/broadinstitute/infercnv/issues

Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
  • c++– GNU Standard C++ Library v3
Datasets:
  • HMM_states - Infercnv object result of the processing of run() in the HMM example, to be used for other examples.
  • infercnv_annots_example - Generated classification for 10 normal cells and 10 tumor cells.
  • infercnv_data_example - Generated SmartSeq2 expression data with 10 normal cells and 10 tumor cells. This is only to demonstrate how to use methods, not actual data to be used in an analysis.
  • infercnv_genes_example - Downsampled gene coordinates file from GrCh37
  • infercnv_object_example - Infercnv object result of the processing of run() in the example, to be used for other examples.
  • mcmc_obj - Infercnv object result of the processing of inferCNVBayesNet in the example, to be used for other examples.

On BioConductor:infercnv-1.21.0(bioc 3.20)infercnv-1.20.0(bioc 3.19)

softwarecopynumbervariationvariantdetectionstructuralvariationgenomicvariationgeneticstranscriptomicsstatisticalmethodbayesianhiddenmarkovmodelsinglecell

11.00 score 561 stars 666 scripts 2.4k downloads 4 mentions 11 exports 190 dependencies

Last updated 23 days agofrom:ec059e200c. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 30 2024
R-4.5-winNOTEOct 31 2024
R-4.5-linuxNOTEOct 30 2024
R-4.4-winNOTEOct 31 2024
R-4.4-macNOTEOct 31 2024
R-4.3-winNOTEOct 31 2024
R-4.3-macNOTEOct 31 2024

Exports:add_to_seuratapply_median_filteringcolor.paletteCreateInfercnvObjectfilterHighPNormalsinferCNVBayesNetplot_cnvplot_per_groupplot_subclustersrunsample_object

Dependencies:abindapeargparseaskpassbase64encBHBiobaseBiocGenericsbitopsbslibcachemcaToolscliclustercodacodetoolscoincolorspacecommonmarkcowplotcpp11crayoncrosstalkcurldata.tableDelayedArraydeldirdigestdoParalleldotCall64dplyrdqrngedgeRevaluatefansifarverfastclusterfastDummiesfastmapfindpythonfitdistrplusFNNfontawesomeforeachformatRfsfutile.loggerfutile.optionsfuturefuture.applygenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2ggrepelggridgesglobalsgluegoftestgplotsgridExtragtablegtoolshereHiddenMarkovhighrhtmltoolshtmlwidgetshttpuvhttricaigraphIRangesirlbaisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglambda.rlaterlatticelazyevalleidenlibcoinlifecyclelimmalistenvlmtestlocfitmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimeminiUImodeltoolsmultcompmunsellmvtnormnlmeopensslparallelDistparallellypatchworkpbapplyphyclustpillarpkgconfigplotlyplyrpngpolyclipprogressrpromisespurrrR6RANNrappdirsRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppHNSWRcppParallelRcppProgressRcppTOMLreshape2reticulaterjagsrlangrmarkdownROCRrprojrootRSpectraRtsneS4ArraysS4VectorssandwichsassscalesscattermoresctransformSeuratSeuratObjectshinySingleCellExperimentsitmosourcetoolsspspamSparseArrayspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilsstatmodstringistringrSummarizedExperimentsurvivalsystensorTH.datatibbletidyrtidyselecttinytexUCSC.utilsutf8uwotvctrsviridisLitewithrxfunxtableXVectoryamlzlibbioczoo

Visualizing Large-scale Copy Number Variation in Single-Cell RNA-Seq Expression Data

Timothy Tickle, Itay Tirosh, Christophe Georgescu, Maxwell Brown, Brian Haas

Rendered frominferCNV.Rmdusingknitr::rmarkdownon Oct 30 2024.

Last update: 2021-02-12
Started: 2016-03-15

Readme and manuals

Help Manual

Help pageTopics
infercnv: Infer Copy Number Variation from Single-Cell RNA-Seq Datainfercnv-package _PACKAGE
add_to_seurat()add_to_seurat
apply_median_filteringapply_median_filtering
Helper function allowing greater control over the steps in a color palette.color.palette
CreateInfercnvObjectCreateInfercnvObject
filterHighPNormals: Filter the HMM identified CNV's by the CNV's posterior probability of belonging to a normal state.filterHighPNormals
infercnv object result of the processing of run() in the HMM example, to be used for other examples.HMM_states
Generated classification for 10 normal cells and 10 tumor cells.infercnv_annots_example
Generated SmartSeq2 expression data with 10 normal cells and 10 tumor cells. This is only to demonstrate how to use methods, not actual data to be used in an analysis.infercnv_data_example
Downsampled gene coordinates file from GrCh37infercnv_genes_example
infercnv object result of the processing of run() in the example, to be used for other examples.infercnv_object_example
The infercnv Classinfercnv infercnv-class
inferCNVBayesNet: Run Bayesian Network Mixture Model To Obtain Posterior Probabilities For HMM Predicted StatesinferCNVBayesNet
MCMC_inferCNV classMCMC_inferCNV MCMC_inferCNV-class
infercnv object result of the processing of inferCNVBayesNet in the example, to be used for other examples.mcmc_obj
Plot the matrix as a heatmap, with cells as rows and genes as columns, ordered according to chromosomeplot_cnv
plot_per_groupplot_per_group
Plot a heatmap of the data in the infercnv object with the subclusters being displayed as annotations.plot_subclusters
run() : Invokes a routine inferCNV analysis to Infer CNV changes given a matrix of RNASeq counts.run
sample_objectsample_object
validate_infercnv_obj()validate_infercnv_obj