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FBA: feature barcoding analysis for single cell RNA-Seq.

Authors :
Duan, Jialei
Hon, Gary C
Source :
Bioinformatics; 11/15/2021, Vol. 37 Issue 22, p4266-4268, 3p
Publication Year :
2021

Abstract

Motivation Single cell RNA-Seq (scRNA-Seq) has broadened our understanding of cellular heterogeneity and provided valuable insights into cellular functions. Recent experimental strategies extend scRNA-Seq readouts to include additional features, including cell surface proteins and genomic perturbations. These 'feature barcoding' strategies rely on converting molecular and cellular features to unique sequence barcodes, which are then detected with the transcriptome. Results Here, we introduce FBA, a flexible and streamlined package to perform quality control, quantification, demultiplexing, multiplet detection, clustering and visualization of feature barcoding assays. Availabilityand implementation FBA is available on PyPi at https://pypi.org/project/fba and on GitHub at https://github.com/jlduan/fba. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13674803
Volume :
37
Issue :
22
Database :
Complementary Index
Journal :
Bioinformatics
Publication Type :
Academic Journal
Accession number :
153738361
Full Text :
https://doi.org/10.1093/bioinformatics/btab375