https://github.com/ebecht/MCPcounter
https://github.com/ebecht/MCPcounter
Last synced: 15 days ago
JSON representation
- Host: GitHub
- URL: https://github.com/ebecht/MCPcounter
- Owner: ebecht
- Created: 2016-09-08T10:37:58.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2022-06-21T14:51:01.000Z (almost 3 years ago)
- Last Synced: 2024-11-09T10:38:30.222Z (6 months ago)
- Language: R
- Size: 98.6 KB
- Stars: 54
- Watchers: 6
- Forks: 44
- Open Issues: 6
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-deconvolution - MCPcounter - counter (MCP-counter) method, which allows the robust quantification of the absolute abundance of eight immune and two stromal cell populations in heterogeneous tissues from transcriptomic data (see also: [Becht et al 2016](https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-1070-5)); tags: immune; immune_cell; blood; blood_cell; transcriptomics; microenvironment; human (Methods)
README
# MCPcounter
This repository hosts the source code corresponding to the method described in our 2016 paper published in Genome Biology, [Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression](https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-1070-5)
To install it, the easiest is to use the `R` package `devtools` and its function `install_github`. To do so, open an `R` session and enter
install.packages(c("devtools","curl")) ##Installs devtools and the MCPcounter dependancy 'curl'
library(devtools)
install_github("ebecht/MCPcounter",ref="master", subdir="Source")
Examples on how to run the algorithm on your data are shown in the documentation `?MCPcounter.estimate`