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- Publisher Website: 10.1093/bioinformatics/btab358
- Scopus: eid_2-s2.0-85118364372
- PMID: 33963851
- WOS: WOS:000733374500039
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Article: Cellsnp-lite: an efficient tool for genotyping single cells
Title | Cellsnp-lite: an efficient tool for genotyping single cells |
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Authors | |
Issue Date | 2021 |
Publisher | Oxford University Press. The Journal's web site is located at http://bioinformatics.oxfordjournals.org/ |
Citation | Bioinformatics, 2021, v. 37 n. 23, p. 4569-4571 How to Cite? |
Abstract | 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.
Availability and implementation:
The source code is freely available at https://github.com/single-cell-genetics/cellsnp-lite.
Supplementary information:
Supplementary data are available at Bioinformatics online. |
Persistent Identifier | http://hdl.handle.net/10722/304617 |
ISSN | 2023 Impact Factor: 4.4 2023 SCImago Journal Rankings: 2.574 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Huang, X | - |
dc.contributor.author | Huang, Y | - |
dc.date.accessioned | 2021-10-05T02:32:42Z | - |
dc.date.available | 2021-10-05T02:32:42Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | Bioinformatics, 2021, v. 37 n. 23, p. 4569-4571 | - |
dc.identifier.issn | 1367-4803 | - |
dc.identifier.uri | http://hdl.handle.net/10722/304617 | - |
dc.description.abstract | 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. Availability and implementation: The source code is freely available at https://github.com/single-cell-genetics/cellsnp-lite. Supplementary information: Supplementary data are available at Bioinformatics online. | - |
dc.language | eng | - |
dc.publisher | Oxford University Press. The Journal's web site is located at http://bioinformatics.oxfordjournals.org/ | - |
dc.relation.ispartof | Bioinformatics | - |
dc.rights | This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Bioinformatics following peer review. The definitive publisher-authenticated version Bioinformatics, 2021, v. 37 n. 23, p. 4569-4571 is available online at: https://doi.org/10.1093/bioinformatics/btab358 | - |
dc.title | Cellsnp-lite: an efficient tool for genotyping single cells | - |
dc.type | Article | - |
dc.identifier.email | Huang, X: hxj5@hku.hk | - |
dc.identifier.email | Huang, Y: yuanhua@hku.hk | - |
dc.identifier.authority | Huang, Y=rp02649 | - |
dc.description.nature | postprint | - |
dc.identifier.doi | 10.1093/bioinformatics/btab358 | - |
dc.identifier.pmid | 33963851 | - |
dc.identifier.scopus | eid_2-s2.0-85118364372 | - |
dc.identifier.hkuros | 325779 | - |
dc.identifier.volume | 37 | - |
dc.identifier.issue | 23 | - |
dc.identifier.spage | 4569 | - |
dc.identifier.epage | 4571 | - |
dc.identifier.isi | WOS:000733374500039 | - |
dc.publisher.place | United Kingdom | - |