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https://github.com/lieberinstitute/megadepth

R interface to megadepth: BigWig and BAM related utilities
https://github.com/lieberinstitute/megadepth

bam bigwig daspter megadepth recount2 recount3 rstats

Last synced: 6 months ago
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R interface to megadepth: BigWig and BAM related utilities

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README 

          
---

output: github_document

---



```{r, include = FALSE}

knitr::opts_chunk$set(

    collapse = TRUE,

    comment = "#>",

    fig.path = "man/figures/README-",

    out.width = "100%"

)

```



# megadepth



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The goal of `megadepth` is to provide an R interface to the command line tool [Megadepth](https://github.com/ChristopherWilks/megadepth) for BigWig and BAM related utilities created by [Christopher Wilks](https://twitter.com/chrisnwilks). This R package enables **fast** processing of BigWig files on downstream packages such as [dasper](https://bioconductor.org/packages/dasper) and [recount3](https://bioconductor.org/packages/recount3). The [Megadepth](https://github.com/ChristopherWilks/megadepth) software also provides utilities for processing BAM files and extracting coverage information from them.



Here is an illustration on how fast `megadepth` is compared to other tools for processing local and remote BigWig files.






Throughout the documentation we use a capital `M` to refer to the software by Christopher Wilks and a lower case `m` to refer to this R/Bioconductor package.



## Installation instructions



Get the latest stable `R` release from [CRAN](http://cran.r-project.org/). Then install `megadepth` from [Bioconductor](http://bioconductor.org/) using the following code:



```{r 'install', eval = FALSE}

if (!requireNamespace("BiocManager", quietly = TRUE)) {

    install.packages("BiocManager")

}



BiocManager::install("megadepth")

```



And the development version from [GitHub](https://github.com/) with:



```{r 'install_dev', eval = FALSE}

BiocManager::install("LieberInstitute/megadepth")

```



## Example



In the following example, we install [Megadepth](https://github.com/ChristopherWilks/megadepth) with `install_megadepth()`, which downloads a binary for your OS (Linux, Windows or macOS). We can then use with an example BigWig file to compute the coverage at a set of regions.



```{r example, eval = requireNamespace('megadepth')}

## Load the R package

library("megadepth")



## Install Megadepth's pre-compiled binary on your system

install_megadepth()



## Next, we locate the example BigWig and annotation files

example_bw <- system.file("tests", "test.bam.all.bw",

    package = "megadepth", mustWork = TRUE

)

annotation_file <- system.file("tests", "testbw2.bed",

    package = "megadepth", mustWork = TRUE

)



## We can then use megadepth to compute the coverage

bw_cov <- get_coverage(example_bw, op = "mean", annotation = annotation_file)

bw_cov

```



## Full set of utilities



[Megadepth](https://github.com/ChristopherWilks/megadepth) is very powerful and can do a lot of different things. The R/Bioconductor package provides two functions for interfacing with [Megadepth](https://github.com/ChristopherWilks/megadepth), `megadepth_cmd()` and `megadepth_shell()`. For the first one, `megadepth_cmd()`, you need to know the actual command syntax you want to use and format it accordingly. If you are more comfortable with R functions, `megadepth_shell()` uses `r BiocStyle::CRANpkg("cmdfun")` to power this interface and capture the standard output stream into R.



To make it easier to use, `megadepth` includes functions that simplify the number of arguments, read in the output files, and converts them into R/Bioconductor friendly objects, such as `get_coverage()` illustrated above.



We hope that you'll find `megadepth` and [Megadepth](https://github.com/ChristopherWilks/megadepth) useful for your work. If you are interested in checking how **fast** `megadepth` is, check out the [**speed analysis**](https://github.com/LieberInstitute/megadepth/tree/devel/analysis) comparison against other tools. Note that the size of the files used and the number of genomic regions queried will affect the speed comparisons.



```{r "interface_options"}

## R-like interface

## that captures the standard output into R

head(megadepth_shell(help = TRUE))



## Command-like interface

megadepth_cmd("--help")

```



```{r "show_help", echo = FALSE}

x <- megadepth_shell(help = TRUE)

cat(paste0(x, "\n"))

```



## Citation



Below is the citation output from using `citation('megadepth')` in R. Please

run this yourself to check for any updates on how to cite __megadepth__.



```{r 'citation', eval = requireNamespace('megadepth')}

print(citation("megadepth"), bibtex = TRUE)

```



Please note that the `megadepth` was only made possible thanks to many other R and bioinformatics software authors, which are cited either in the vignettes and/or the paper(s) describing this package.



## Code of Conduct



Please note that the `megadepth` project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.



## Development tools



* Continuous code testing is possible thanks to [GitHub actions](https://www.tidyverse.org/blog/2020/04/usethis-1-6-0/)  through `r BiocStyle::CRANpkg('usethis')`, `r BiocStyle::CRANpkg('remotes')`, `r BiocStyle::Githubpkg('r-hub/sysreqs')` and `r BiocStyle::CRANpkg('rcmdcheck')` customized to use [Bioconductor's docker containers](https://www.bioconductor.org/help/docker/) and `r BiocStyle::Biocpkg('BiocCheck')`.

* Code coverage assessment is possible thanks to [codecov](https://codecov.io/gh) and `r BiocStyle::CRANpkg('covr')`.

* The [documentation website](http://LieberInstitute.github.io/megadepth) is automatically updated thanks to `r BiocStyle::CRANpkg('pkgdown')`.

* The code is styled automatically thanks to `r BiocStyle::CRANpkg('styler')`.

* The documentation is formatted thanks to `r BiocStyle::CRANpkg('devtools')` and `r BiocStyle::CRANpkg('roxygen2')`.



For more details, check the `dev` directory.



This package was developed using `r BiocStyle::Biocpkg('biocthis')`.



## `ReCount` project



The **main documentation website** for all the `recount3`-related projects is available at [**recount.bio**](https://LieberInstitute/github.io/recount3-docs). Please check that website for more information about how this R/Bioconductor package and other tools are related to each other.



## Teams involved



`r BiocStyle::Biocpkg('megadepth')` was made possible to [David Zhang](https://twitter.com/dyzhang32), the author of `r BiocStyle::Biocpkg("dasper")`, and a member of the [Mina Ryten](https://snca.atica.um.es/)'s lab at UCL.



The `ReCount` family involves the following teams:



* [Ben Langmead's lab](http://www.langmead-lab.org/) at JHU Computer Science

* [Kasper Daniel Hansen's lab](https://www.hansenlab.org/)  at JHBSPH Biostatistics Department

* [Leonardo Collado-Torres](http://lcolladotor.github.io/) and [Andrew E. Jaffe](http://aejaffe.com/) from [LIBD](https://www.libd.org/)

* [Abhinav Nellore's lab](http://nellore.bio/)  at OHSU

* [Jeff Leek's lab](http://jtleek.com/) at JHBSPH Biostatistics Deparment

* Data hosted by [SciServer from IDIES at JHU](https://www.sciserver.org/)



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