TY - JOUR
T1 - ClinSeK
T2 - A targeted variant characterization framework for clinical sequencing
AU - Zhou, Wanding
AU - Zhao, Hao
AU - Chong, Zechen
AU - Mark, Routbort J.
AU - Eterovic, Agda K.
AU - Meric-Bernstam, Funda
AU - Chen, Ken
N1 - Funding Information:
We thank Kenna Shaw, Gordon Mills and John Mendelsohn for leadership, members of the IPCT for providing targeted exome-sequencing data, members of the Molecular Diagnostic Laboratory for providing CLIA-validation data, Lee Ann Chastain for grammatical proofreading, Tenghui Chen and Xian Fan for assistance. The results published here are in part based upon data generated by TCGA established by the NCI and NHGRI. Information about TCGA and the investigators and institutions who constitute TCGA research network can be found at http://cancergenome.nih.gov/. This work was supported in part by the National Institutes of Health (grant number R01 CA172652, U01 CA180964, UL1 TR000371), the MD Anderson Cancer Center Sheikh Khalifa Ben Zayed Al Nahyan Institute of Personalized Cancer Therapy grant (U54 CA112970) and the National Cancer Institute Cancer Center Support Grant (P30 CA016672).
Publisher Copyright:
© Zhou et al.; licensee BioMed Central.
PY - 2015/3/31
Y1 - 2015/3/31
N2 - Applying genomics to patient care demands sensitive, unambiguous and rapid characterization of a known set of clinically relevant variants in patients' samples, an objective substantially different from the standard discovery process, in which every base in every sequenced read must be examined. Further, the approach must be sufficiently robust as to be able to detect multiple and potentially rare variants from heterogeneous samples. To meet this critical objective, we developed a novel variant characterization framework, ClinSeK, which performs targeted analysis of relevant reads from high-throughput sequencing data. ClinSeK is designed for efficient targeted short read alignment and is capable of characterizing a wide spectrum of genetic variants from single nucleotide variation to large-scale genomic rearrangement breakpoints. Applying ClinSeK to over a thousand cancer patients demonstrated substantively better performance, in terms of accuracy, runtime and disk storage, for clinical applications than existing variant discovery tools. ClinSeK is freely available for academic use at http://bioinformatics.mdanderson.org/main/clinsek.
AB - Applying genomics to patient care demands sensitive, unambiguous and rapid characterization of a known set of clinically relevant variants in patients' samples, an objective substantially different from the standard discovery process, in which every base in every sequenced read must be examined. Further, the approach must be sufficiently robust as to be able to detect multiple and potentially rare variants from heterogeneous samples. To meet this critical objective, we developed a novel variant characterization framework, ClinSeK, which performs targeted analysis of relevant reads from high-throughput sequencing data. ClinSeK is designed for efficient targeted short read alignment and is capable of characterizing a wide spectrum of genetic variants from single nucleotide variation to large-scale genomic rearrangement breakpoints. Applying ClinSeK to over a thousand cancer patients demonstrated substantively better performance, in terms of accuracy, runtime and disk storage, for clinical applications than existing variant discovery tools. ClinSeK is freely available for academic use at http://bioinformatics.mdanderson.org/main/clinsek.
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U2 - 10.1186/s13073-015-0155-1
DO - 10.1186/s13073-015-0155-1
M3 - Article
C2 - 25918555
AN - SCOPUS:84928397005
SN - 1756-994X
VL - 7
JO - Genome medicine
JF - Genome medicine
IS - 1
M1 - 34
ER -