Package: atacInferCnv 1.1.0

Konstantin Okonechnikov

atacInferCnv: Call CNV from single cell ATAC-seq data based on InferCNV adaptation

The package prepares input scATAC-seq data and adapts for copy number variance profiling with InferCNV package usage. It has also various paramters to control the analysis (e.g. external normal reference usage, meta-cells, bin size, etc) and custom plot visualizations.

Authors:Konstantin Okonechnikov [aut, cre], Supat Thongjuea [aut, fnd]

atacInferCnv_1.1.0.tar.gz

atacInferCnv_1.1.0.tgz(r-4.6-x86_64)atacInferCnv_1.1.0.tgz(r-4.6-arm64)atacInferCnv_1.1.0.tgz(r-4.5-x86_64)atacInferCnv_1.1.0.tgz(r-4.5-arm64)
atacInferCnv_1.1.0.tar.gz(r-4.7-arm64)atacInferCnv_1.1.0.tar.gz(r-4.7-x86_64)atacInferCnv_1.1.0.tar.gz(r-4.6-arm64)atacInferCnv_1.1.0.tar.gz(r-4.6-x86_64)
atacInferCnv_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
atacInferCnv/json (API)

# Install 'atacInferCnv' in R:

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

Bug tracker:https://github.com/kokonech/atacinfercnv/issues

Uses libs:

c++– GNU Standard C++ Library v3
jags– Just Another Gibbs Sampler for Bayesian MCMC - binary JAGS is Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS was written with three aims in mind: * To have an engine for the BUGS language that runs on Unix * To be extensible, allowing users to write their own functions, distributions and samplers. * To be a plaftorm for experimentation with ideas in Bayesian modelling This package contains the 'jags' binary as well as the associated shared library modules loaded by the binary.

On BioConductor:atacInferCnv-1.1.0(bioc 3.24)atacInferCnv-1.0.0(bioc 3.23)

epigenetics sequencing copynumbervariation singlecell immunooncology cpp jags

4.85 score 3 scripts 210 downloads 3 exports 197 dependencies

Last updated from:0347acd24d. Checks:8 NOTE, 2 OK, 1 ERROR, 3 FAIL. Indexed: yes.

Target	Result	Time
bioc-checks	NOTE	285
linux-devel-arm64	NOTE	510
linux-devel-x86_64	NOTE	593
source / vignettes	OK	515
linux-release-arm64	NOTE	519
linux-release-x86_64	NOTE	637
macos-release-arm64	NOTE	350
macos-release-x86_64	NOTE	722
macos-oldrel-arm64	NOTE	372
macos-oldrel-x86_64	ERROR	622
windows-devel	FAIL	387
windows-release	FAIL	369
windows-oldrel	FAIL	402
wasm-release	OK	227

Exports:plotCnvBlocks prepareAtacInferCnvInput runAtacInferCnv

Dependencies:abind ape argparse askpass base64enc BH Biobase BiocGenerics BiocParallel Biostrings bitops bslib cachem caTools cli cluster coda codetools coin commonmark config cowplot cpp11 crayon crosstalk curl data.table DelayedArray deldir digest doParallel dotCall64 dplyr dqrng edgeR evaluate farver fastcluster fastDummies fastmap fastmatch findpython fitdistrplus FNN fontawesome foreach formatR fs futile.logger futile.options future future.apply generics GenomeInfoDb GenomicRanges ggplot2 ggrepel ggridges globals glue goftest gplots gridExtra gtable gtools here HiddenMarkov highr htmltools htmlwidgets httpuv httr ica igraph infercnv IRanges irlba isoband iterators jquerylib jsonlite KernSmooth knitr labeling lambda.r later lattice lazyeval libcoin lifecycle limma listenv lmtest locfit magrittr MASS Matrix MatrixGenerics matrixStats memoise mime miniUI modeltools multcomp mvtnorm nlme openssl otel 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 RcppRoll RcppTOML reshape2 reticulate Rhtslib rjags rlang rmarkdown ROCR rprojroot Rsamtools RSpectra Rtsne S4Arrays S4Vectors S7 sandwich sass scales scattermore sctransform Seqinfo Seurat SeuratObject shiny Signac SingleCellExperiment sitmo snow sourcetools sp spam SparseArray sparseMatrixStats spatstat.data spatstat.explore spatstat.geom spatstat.random spatstat.sparse spatstat.univar 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 zoo

atacInferCnv: CNV inference from scATAC-seq data

Getting started | Custom settings | Applications | Session info

Rendered fromatacInferCnv.Rmdusingknitr::rmarkdown

Last update: 2026-04-17
Started: 2026-02-05

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Combine ATAC signals across bins of specific size	aggregateBins
atacInferCnv: CNV inference from single-cell chromatin accessibility data	atacInferCnv-package atacInferCnv
Compute meta-cells out of the main	extractMetacells
Function to plot CNV blocks	plotCnvBlocks
Prepare input for the CNV calling from scATAC-seq data	prepareAtacInferCnvInput
Wrapper function to run InferCNV calling	runAtacInferCnv
Write InferCNV configuration	writeConfig