HoneyBADGER (hidden Markov model integrated Bayesian approach for detecting CNV and LOH events from single-cell RNA-seq data) identifies and infers the presence of CNV and LOH events in single cells and reconstructs subclonal architecture using allele and expression information from single-cell RNA-sequencing data.
The overall approach is detailed in the following publication: COMING SOON!
HoneyBADGER, we recommend using
JAGS (Just Another Gibbs Sampler) through
JAGS must be installed per your operating system requirements. Please see this R-bloggers tutorial for additional tips for installing
Additional dependencies may need to be installed from
Biocondcutor such as
GenomicRanges and others:
## try http:// if https:// URLs are not supported source("https://bioconductor.org/biocLite.R") biocLite("GenomicRanges")
We welcome any bug reports, enhancement requests, and other contributions. To submit a bug report or enhancement request, please use the
HoneyBADGER GitHub issues tracker. For more substantial contributions, please fork this repo, push your changes to your fork, and submit a pull request with a good commit message.