multiseq: multiscale Poisson process approaches for differential or association analysis of high-throughput sequencing data

This R package implements multiscale Poisson process approaches for differential or association analysis of high-throughput sequencing data. Key features that distinguish the multiseq from typical differential or association analysis are to 1) better exploit high-resolution information in the high-throughput sequencing data, and 2) directly model the count nature of the data. See Shim et al. (2021) for the details of the motivations, approaches, and comparison with other methods.

If you find a bug, please post an issue.

License

Copyright (c) 2021-2023, Heejung Shim, Zhengrong Xing, Ester Pantaleo, and Matthew Stephens.

All source code and software in this repository is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 3 of the License, or (at your option) any later version. See the LICENSE file for the full text of the license.

Citing this work

If you find that this R package useful for your work, please cite our paper:

Heejung Shim, Zhengrong Xing, Ester Pantaleo, Francesca Luca, Roger Pique-Regi, and Matthew Stephens (2021). Multi-scale Poisson process approaches for differential expression analysis of high-throughput sequencing data. Shim et al. (2021).

Dependency

This package depends on the ashr R package v1.0.12. In R, you can install the ashr v1.0.12 using devtools:

install.packages("devtools")
library(devtools)
install_github("stephens999/[email protected]")

Quick Start

Follow these steps to quickly get started using multiseq.

1. In R, install the latest version of multiseq using devtools:

   install.packages("devtools")
   library(devtools)
   install_github("heejungshim/multiseq")

   This will build the multiseq package without the vignettes. To build with the vignettes, do this instead:

   install_github("heejungshim/multiseq",build_vignettes = TRUE)

2. Load the multiseq package:

   library(multiseq)

3. To learn more, see the multiseq vignette (which you can also view here):

   vignette("multiseq")