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


BACKGROUND
http://www.sanger.ac.uk/genetics/CGP/Software/AutoCSA.
Dicks
E
E
Cancer Genome Project, Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridge, CB10 1SA, UK.
Teague
J W
JW
Stephens
P
P
Raine
K
K
Yates
A
A
Mattocks
C
C
Tarpey
P
P
Butler
A
A
Menzies
A
A
Richardson
D
D
Jenkinson
A
A
Davies
H
H
Edkins
S
S
Forbes
S
S
Gray
K
K
Greenman
C
C
Shepherd
R
R
Stratton
M R
MR
Futreal
P A
PA
Wooster
R
R
D000465:Algorithms; D001483:Base Sequence; D002874:Chromosome Mapping / Q000379:methods*; D004252:DNA Mutational Analysis / Q000379:methods*; D004273:DNA, Neoplasm / Q000235:genetics*; D020022:Genetic Predisposition to Disease / Q000235:genetics; D005820:Genetic Testing / Q000379:methods*; D014644:Genetic Variation / Q000235:genetics; D006801:Humans; D008969:Molecular Sequence Data; D009369:Neoplasms / Q000175:diagnosis* / Q000235:genetics*; D012984:Software
D004273:DNA, Neoplasm