AutoCSA, an algorithm for high throughput DNA sequence variant detection in cancer genomes

Dicks, E., Teague, J. W., Stephens, P., Raine, K., Yates, A., Mattocks, C., Tarpey, P., Butler, A., Menzies, A., Richardson, D., Jenkinson, A., Davies, H., Edkins, S., Forbes, S., Gray, K., Greenman, C., Shepherd, R., Stratton, M. R., Futreal, P. A. and Wooster, R. (2007) AutoCSA, an algorithm for high throughput DNA sequence variant detection in cancer genomes. Bioinformatics, 23 (13). pp. 1689-1691. ISSN 1367-4803

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Abstract

The undertaking of large-scale DNA sequencing screens for somatic variants in human cancers requires accurate and rapid processing of traces for variants. Due to their often aneuploid nature and admixed normal tissue, heterozygous variants found in primary cancers are often subtle and difficult to detect. To address these issues, we have developed a mutation detection algorithm, AutoCSA, specifically optimized for the high throughput screening of cancer samples.

Item Type:	Article
Uncontrolled Keywords:	sdg 3 - good health and well-being ,/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Computational Biology
Depositing User:	Pure Connector
Date Deposited:	11 Jun 2014 13:18
Last Modified:	19 Apr 2023 00:09
URI:	https://ueaeprints.uea.ac.uk/id/eprint/48587
DOI:	10.1093/bioinformatics/btm152

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