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Title: cellCounts: an R function for quantifying 10x Chromium single-cell RNA sequencing data.
Austin Authors: Liao, Yang;Raghu, Dinesh;Pal, Bhupinder;Mielke, Lisa A;Shi, Wei
Affiliation: Olivia Newton-John Cancer Research Institute
School of Cancer Medicine, La Trobe University, Bundoora, Victoria 3086, Australia.
Issue Date: 1-Jul-2023
Publication information: Bioinformatics (Oxford, England) 2023-07-01; 39(7)
Abstract: The 10x Genomics Chromium single-cell RNA sequencing technology is a powerful gene expression profiling platform, which is capable of profiling expression of thousands of genes in tens of thousands of cells simultaneously. This platform can produce hundreds of million reads in a single experiment, making it a very challenging task to quantify expression of genes in individual cells due to the massive data volume. Here, we present cellCounts, a new tool for efficient and accurate quantification of Chromium data. cellCounts employs the seed-and-vote strategy to align reads to a reference genome, collapses reads to Unique Molecular Identifiers (UMIs) and then assigns UMIs to genes based on the featureCounts program. Using both simulation and real datasets for evaluation, cellCounts was found to compare favourably to cellRanger and STARsolo. cellCounts is implemented in R, making it easily integrated with other R programs for analysing Chromium data. cellCounts was implemented as a function in R package Rsubread that can be downloaded from Data and analysis code used in this study can be freely accessed via La Trobe University's Institutional Repository at
DOI: 10.1093/bioinformatics/btad439
ORCID: 0000-0003-1182-7735
Journal: Bioinformatics (Oxford, England)
PubMed URL: 37462540
ISSN: 1367-4811
Type: Journal Article
Appears in Collections:Journal articles

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