Cellsnp-lite: An efficient tool for genotyping single cells

Summary: Single-cell sequencing is an increasingly used technology and has promising applications in basic research and clinical translations. However, genotyping methods developed for bulk sequencing data have not been well adapted for single-cell data, in terms of both computational parallelizatio...

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Bibliographic Details
Main Authors: Huang, X. (Author), Huang, Y. (Author)
Format: Article
Language:English
Published: Oxford University Press 2021
Online Access:View Fulltext in Publisher
LEADER 01442nam a2200145Ia 4500
001 10.1093-bioinformatics-btab358
008 220427s2021 CNT 000 0 und d
020 |a 13674803 (ISSN) 
245 1 0 |a Cellsnp-lite: An efficient tool for genotyping single cells 
260 0 |b Oxford University Press  |c 2021 
856 |z View Fulltext in Publisher  |u https://doi.org/10.1093/bioinformatics/btab358 
520 3 |a Summary: Single-cell sequencing is an increasingly used technology and has promising applications in basic research and clinical translations. However, genotyping methods developed for bulk sequencing data have not been well adapted for single-cell data, in terms of both computational parallelization and simplified user interface. Here, we introduce a software, cellsnp-lite, implemented in C/C++ and based on well-supported package htslib, for genotyping in single-cell sequencing data for both droplet and well-based platforms. On various experimental datasets, it shows substantial improvement in computational speed and memory efficiency with retaining highly concordant results compared to existing methods. Cellsnp-lite, therefore, lightens the genetic analysis for increasingly large single-cell data. © 2021 The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. 
700 1 |a Huang, X.  |e author 
700 1 |a Huang, Y.  |e author 
773 |t Bioinformatics