SingerLab/gac: Genetic Analysis of Cells

This package is a framework and toolkit for the analysis of single-cell genomic data. It provides a framework to efficiently carry out the downstream quantative analysis of single cell copy number data by managing concurrent phenotypic and metadata on all the cells and the samples. It applies the state-of-the art methods for identifying clonal structure, VDJ genotyping, recurrently altered regions, and makes use of mixed models used in quantitative genetics to identify causal genes. An additional, convenient feature is that it automatically expands the bin/segment data to genes seamlesly and to facilitate the biological interpretation of results.

Getting started

Package details

AuthorRodrigo Gularte Merida [aut, cre]
MaintainerRodrigo Gularte Merida <gularter@mskcc.org>
LicenseBSD_3_clause + file LICENSE
Version0.0.90022
URL https://github.com/SingerLab/gac/
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("SingerLab/gac")
SingerLab/gac documentation built on July 22, 2021, 3:27 a.m.