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Published on: February 2, 2021
CAMML with the Integration of Marker Proteins (ChIMP)
Courtney Schiebout1, H Robert Frost1
1Department of Biomedical Data Science, Dartmouth College, Hanover, NH 03755, USA.
Motivation:
Cell typing is a critical task in the analysis of single-cell data, particularly when studying complex diseased tissues. Unfortunately, the sparsity and noise of single-cell data make accurate cell typing of individual cells difficult. To address these challenges, we previously developed the CAMML method for multi-label cell typing of single-cell RNA-sequencing (scRNA-seq) data. CAMML uses weighted gene sets to score each profiled cell for multiple potential cell types. While CAMML outperforms other scRNA-seq cell typing techniques, it only leverages transcriptomic data so cannot take advantage of newer multi-omic single-cell assays that jointly profile gene expression and protein abundance (e.g. joint scRNA-seq/CITE-seq).
Results:
We developed the CAMML with the Integration of Marker Proteins (ChIMP) method to support multi-label cell typing of individual cells jointly profiled via scRNA-seq and CITE-seq. ChIMP combines cell type scores computed on scRNA-seq data via the CAMML approach with discretized CITE-seq measurements for cell type marker proteins. The multi-omic cell type scores generated by ChIMP allow researchers to more precisely and conservatively cell type joint scRNA-seq/CITE-seq data.
Availability And Implementation:
An implementation of this work is available on CRAN at https://cran.r-project.org/web/packages/CAMML/.
Supplementary Information:
Supplementary data are available at Bioinformatics online.
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