Package: infercnv 1.21.0

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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NEWS

# Install 'infercnv' in R:

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

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)

bioconductor-package

11 exports 1.58 score 189 dependencies 4 mentions

Last updated 2 months agofrom:65aaf9fcdc

Exports:add_to_seurat apply_median_filtering color.palette CreateInfercnvObject filterHighPNormals inferCNVBayesNet plot_cnv plot_per_group plot_subclusters run sample_object

Dependencies:abind ape argparse askpass base64enc BH Biobase BiocGenerics bitops bslib cachem caTools cli cluster coda codetools coin colorspace commonmark cowplot cpp11 crayon crosstalk curl data.table DelayedArray deldir digest doParallel dotCall64 dplyr dqrng edgeR evaluate fansi farver fastcluster fastDummies fastmap findpython fitdistrplus FNN fontawesome foreach formatR fs futile.logger futile.options future future.apply generics GenomeInfoDb GenomeInfoDbData GenomicRanges ggplot2 ggrepel ggridges globals glue goftest gplots gridExtra gtable gtools here HiddenMarkov highr htmltools htmlwidgets httpuv httr ica igraph IRanges irlba isoband iterators jquerylib jsonlite KernSmooth knitr labeling lambda.r later lattice lazyeval leiden libcoin lifecycle limma listenv lmtest locfit magrittr MASS Matrix MatrixGenerics matrixStats memoise mgcv mime miniUI modeltools multcomp munsell mvtnorm nlme openssl parallelDist parallelly patchwork pbapply phyclust pillar pkgconfig plotly plyr png polyclip progressr promises purrr R6 RANN rappdirs RColorBrewer Rcpp RcppAnnoy RcppArmadillo RcppEigen RcppHNSW RcppParallel RcppProgress RcppTOML reshape2 reticulate rjags rlang rmarkdown ROCR rprojroot RSpectra Rtsne S4Arrays S4Vectors sandwich sass scales scattermore sctransform Seurat SeuratObject shiny SingleCellExperiment sitmo sourcetools sp spam SparseArray spatstat.data spatstat.explore spatstat.geom spatstat.random spatstat.sparse spatstat.utils statmod stringi stringr SummarizedExperiment survival sys tensor TH.data tibble tidyr tidyselect tinytex UCSC.utils utf8 uwot vctrs viridisLite withr xfun xtable XVector yaml zlibbioc zoo

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 Jun 17 2024.

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

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
infercnv: Infer Copy Number Variation from Single-Cell RNA-Seq Data	infercnv-package _PACKAGE
add_to_seurat()	add_to_seurat
apply_median_filtering	apply_median_filtering
Helper function allowing greater control over the steps in a color palette.	color.palette
CreateInfercnvObject	CreateInfercnvObject
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 GrCh37	infercnv_genes_example
infercnv object result of the processing of run() in the example, to be used for other examples.	infercnv_object_example
The infercnv Class	infercnv infercnv-class
inferCNVBayesNet: Run Bayesian Network Mixture Model To Obtain Posterior Probabilities For HMM Predicted States	inferCNVBayesNet
MCMC_inferCNV class	MCMC_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 chromosome	plot_cnv
plot_per_group	plot_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_object	sample_object
validate_infercnv_obj()	validate_infercnv_obj