jakeyeung/scChIX: Deconvolving Multiplexed Histone Modifications in Single Cells.

This package implements the scChIX algorithm. It takes single-cell immunotethered data (e.g. scChIC-seq, sortChIC, CUT&RUN, CUT&Tag) generated byincubating with a mixture of two antibodies (e.g. to target two different histone modifications) and deconvolving the multiplexed data to infer multiple antibody-tagged chromatin fragments in single cells. scChIX takes as input two single-cell training datasets, each where the sample was incubated by the antibody alone. This allows scChIX to learn the precise relationships between, for example, two histone modifications and how those relationships at the single-cell level. This package includes snakemake workflows to process the training datasets, run the statistical model, and demultiplex the double-incubated count matrices. Furthermore, we provide vignettes to demonstrate how to analyze the downstream analysis to visualize the outputs of the statistical model and generate linked maps between two histone modifications.

Getting started

Package details

Maintainer
LicenseMIT
Version0.0.0.9000
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("jakeyeung/scChIX")
jakeyeung/scChIX documentation built on May 7, 2023, 9:14 a.m.