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Quantification of aneuploidy in targeted sequencing data using ASCETS
- Source :
- Bioinformatics
- Publication Year :
- 2020
- Publisher :
- Oxford University Press (OUP), 2020.
-
Abstract
- Summary The expansion of targeted panel sequencing efforts has created opportunities for large-scale genomic analysis, but tools for copy-number quantification on panel data are lacking. We introduce ASCETS, a method for the efficient quantitation of arm and chromosome-level copy-number changes from targeted sequencing data. Availability and implementation ASCETS is implemented in R and is freely available to non-commercial users on GitHub: https://github.com/beroukhim-lab/ascets, along with detailed documentation. Supplementary information Supplementary data are available at Bioinformatics online.
- Subjects :
- Statistics and Probability
Computer science
Sequencing data
MEDLINE
Aneuploidy
ComputerApplications_COMPUTERSINOTHERSYSTEMS
Documentation
Computational biology
Biochemistry
03 medical and health sciences
0302 clinical medicine
medicine
Humans
Molecular Biology
030304 developmental biology
0303 health sciences
Genome
Genomics
medicine.disease
Applications Notes
Computer Science Applications
Computational Mathematics
Computational Theory and Mathematics
030220 oncology & carcinogenesis
Software
Subjects
Details
- ISSN :
- 13674811 and 13674803
- Volume :
- 37
- Database :
- OpenAIRE
- Journal :
- Bioinformatics
- Accession number :
- edsair.doi.dedup.....40d06e93926f7161523f1ee0c2aec422
- Full Text :
- https://doi.org/10.1093/bioinformatics/btaa980