# HiLDA: "*Hi*erarchical *L*atent *D*irichlet *A*llocation"
[](https://www.bioconductor.org/packages/HiLDA)
[](https://bioconductor.org/packages/stats/bioc/HiLDA)
[](https://doi.org/10.7717/peerj.7557) [](https://image.usc.edu)
## Introduction
The R package `HiLDA` is developed under the Bayesian framework to allow
statistically testing whether there is a change in the mutation burdens of
mutation signatures between two groups. The mutation signature is defined based
on the independent model proposed by Shiraishi's et al.
## Paper
- **Yang Z**, Pandey P, Shibata D, Conti DV, Marjoram P, Siegmund KD. 2019. HiLDA: a statistical approach to investigate differences in mutational signatures. PeerJ 7:e7557 https://doi.org/10.7717/peerj.7557
## Installation
Now you can download the pacakge from Bioconductor https://bioconductor.org/packages/devel/bioc/html/HiLDA.html
```
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("HiLDA")
```
## Documentation
To view documentation for the version of this package installed in your system, start R and enter:
```
browseVignettes("HiLDA")
```
## An introduction to HiLDA
Tutorials:
https://bioconductor.org/packages/devel/bioc/vignettes/HiLDA/inst/doc/HiLDA.html
R Scripts:
https://bioconductor.org/packages/devel/bioc/vignettes/HiLDA/inst/doc/HiLDA.R
## Funding
This work was supported by NCI grant numbers 5P30 CA014089 and P01 CA196569.
