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README.Rmd
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---
output: github_document
---
[](http://www.repostatus.org/#active)
[](https://travis-ci.org/TeamMacLean/atacr)
[](https://codecov.io/gh/TeamMacLean/atacr)
---
[](https://cran.r-project.org/)
[](https://cran.r-project.org/package=atacr)
[](commits/master)
---
[)`-yellowgreen.svg)](/commits/master)
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, echo = FALSE, warnings=FALSE, message=FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "README-"
)
devtools::load_all("~/Desktop/atacr")
```
# atacR
Helps with the analysis of count data from RNA-capture-seq and ATAC-capture-seq experiments. Using BioConductor RangedSummarizedExperiment objects, atacr implements a set of helper functions and quality control plots specific to the analysis of counts of reads in windows across genomes. Especially, atacr is useful for performing sample normalizations and for easily running bootstrap and Bayes factor tests for differentially accessible windows in common reference designs.
## Installation
You can install atacR from github with:
```{r gh-installation, eval = FALSE}
# install.packages("devtools")
devtools::install_github("TeamMacLean/atacr")
```
## Documentation
You can read documentation on the following topics
1. [Tutorial - A worked example](https://teammaclean.github.io/atacr)
2. [atacR - General Overview](https://teammaclean.github.io/atacr/atacr.html)
3. [Loading Data](https://teammaclean.github.io/atacr/loading.html)
3. [Summaries of Data](https://teammaclean.github.io/atacr/summaries.html)
4. [Normalising Data](https://teammaclean.github.io/atacr/normalisations.html)
5. [Differential Windows](https://teammaclean.github.io/atacr/differential_windows.html)
6. [Subsetting Data](https://teammaclean.github.io/atacr/atacr_which.html)
## Quick start:
```{r example, echo=TRUE, fig.height=7, fig.width=7}
library(atacr)
summary(sim_counts)
```
```{r}
plot(sim_counts)
```