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README.Rmd
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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/",
out.width = "100%",
fig.dpi = 96
)
```
# cinaR <a href='https://eonurk.github.io/cinaR/'><img src='man/figures/cinaR.png' align="right" alt="" width="139" /></a>
<!-- badges: start -->
![RMD check](https://github.com/eonurk/cinaR/actions/workflows/R-CMD-check.yaml/badge.svg)
[![CRAN version](https://www.r-pkg.org/badges/version/cinaR)](https://cran.r-project.org/package=cinaR)
[![CRAN download](https://cranlogs.r-pkg.org/badges/cinaR?color=orange)](https://cran.r-project.org/package=cinaR?color=orange)
<!-- badges: end -->
## Overview
`cinaR` is a single wrapper function for end-to-end computational analyses of
bulk ATAC-seq (or RNA-seq) profiles. Starting from a consensus peak file, it outputs
differentially accessible peaks, enrichment results, and provides users with various configurable visualization options. For more details, please see the [preprint](https://www.biorxiv.org/content/10.1101/2021.03.05.434143v2).
![](man/figures/[email protected])
## Installation
```{r, eval=FALSE}
# CRAN mirror
install.packages("cinaR")
```
### Development version
To get bug fix and use a feature from the development version:
```{r, eval=FALSE}
# install.packages("devtools")
devtools::install_github("eonurk/cinaR")
```
### Known Installation Issues
Sometimes bioconductor related packages may not be installed automatically.
Therefore, you may need to install them manually:
```{r, eval=FALSE}
BiocManager::install(c("ChIPseeker", "DESeq2", "edgeR", "fgsea","GenomicRanges", "limma", "preprocessCore", "sva", "TxDb.Hsapiens.UCSC.hg38.knownGene", "TxDb.Hsapiens.UCSC.hg19.knownGene", "TxDb.Mmusculus.UCSC.mm10.knownGene"))
```
## Usage
```{r setup, include=FALSE}
knitr::opts_chunk$set(dpi=300,fig.width=6)
```
```{r}
library(cinaR)
# create contrast vector which will be compared.
contrasts<- c("B6", "B6", "B6", "B6", "B6", "NZO", "NZO", "NZO", "NZO", "NZO", "NZO",
"B6", "B6", "B6", "B6", "B6", "NZO", "NZO", "NZO", "NZO", "NZO", "NZO")
# If reference genome is not set hg38 will be used!
results <- cinaR(bed, contrasts, reference.genome = "mm10")
pca_plot(results, contrasts, show.names = F)
```
> For more details please go to our site from [here!](https://eonurk.github.io/cinaR/articles/cinaR.html)
## Citation
```
@article {Karakaslar2021.03.05.434143,
author = {Karakaslar, E Onur and Ucar, Duygu},
title = {cinaR: A comprehensive R package for the differential analyses and
functional interpretation of ATAC-seq data},
year = {2021},
doi = {10.1101/2021.03.05.434143},
publisher = {Cold Spring Harbor Laboratory},
URL = {https://www.biorxiv.org/content/early/2021/03/08/2021.03.05.434143.1},
journal = {bioRxiv}
}
```
## Contribution
You can send pull requests to make your contributions.
## License
- GNU General Public License v3.0