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cinaR
View on CRAN: Click
here
Download and install cinaR package within the R console
Install from CRAN:
install.packages("cinaR")
Install from Github:
library("remotes")
install_github("cran/cinaR") Install by package version:
library("remotes")
install_version("cinaR", "0.2.3") Attach the package and use:
library("cinaR")
Maintained by
Onur Karakaslar
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-11-14
Latest Update: 2022-05-18
Description:
Differential analyses and Enrichment pipeline for bulk 'ATAC-seq' data
analyses. This package combines different packages to have an ultimate package
for both data analyses and visualization of 'ATAC-seq' data. Methods are described in
'Karakaslar et al.' (2021) .
How to cite:
Onur Karakaslar (2020). cinaR: A Computational Pipeline for Bulk 'ATAC-Seq' Profiles. R package version 0.2.3, https://cran.r-project.org/web/packages/cinaR. Accessed 06 Mar. 2026.
Previous versions and publish date:
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Other R packages that cinaR depends,
imports, suggests or enhances
Complete documentation for cinaR
Functions, R codes and Examples using
the cinaR R package
Some associated functions: GSEA . HPEA . annotatePeaks . bed . cinaR . color_values . differentialAnalyses . dot_plot . filterConsensus . grch37 . grch38 . grcm38 . heatmap_differential . heatmap_var_peaks . normalizeConsensus . pca_plot . run_enrichment . scale_rows . show_comparisons . verboseFn . vp2008 .
Some associated R codes: cinaR.R . color_values.R . enrichment_functions.R . example-data.R . utils.R . visualization_functions.R . Full cinaR package functions and examples
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