TY - JOUR
T1 - Expanding the computational toolbox for mining cancer genomes
AU - Ding, Li
AU - Wendl, Michael C.
AU - McMichael, Joshua F.
AU - Raphael, Benjamin J.
N1 - Funding Information:
This work was supported by the US National Human Genome Research Institute (grants U01HG006517 to L.D.; R01HG005690 and R01HG007069 to B.J.R.) and by the US National Cancer Institute (grant R01CA180006 to L.D.). The authors thank K. Ye and M. D. McLellan for comments.
PY - 2014/8
Y1 - 2014/8
N2 - High-throughput DNA sequencing has revolutionized the study of cancer genomics with numerous discoveries that are relevant to cancer diagnosis and treatment. The latest sequencing and analysis methods have successfully identified somatic alterations, including single-nucleotide variants, insertions and deletions, copy-number aberrations, structural variants and gene fusions. Additional computational techniques have proved useful for defining the mutations, genes and molecular networks that drive diverse cancer phenotypes and that determine clonal architectures in tumour samples. Collectively, these tools have advanced the study of genomic, transcriptomic and epigenomic alterations in cancer, and their association to clinical properties. Here, we review cancer genomics software and the insights that have been gained from their application.
AB - High-throughput DNA sequencing has revolutionized the study of cancer genomics with numerous discoveries that are relevant to cancer diagnosis and treatment. The latest sequencing and analysis methods have successfully identified somatic alterations, including single-nucleotide variants, insertions and deletions, copy-number aberrations, structural variants and gene fusions. Additional computational techniques have proved useful for defining the mutations, genes and molecular networks that drive diverse cancer phenotypes and that determine clonal architectures in tumour samples. Collectively, these tools have advanced the study of genomic, transcriptomic and epigenomic alterations in cancer, and their association to clinical properties. Here, we review cancer genomics software and the insights that have been gained from their application.
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U2 - 10.1038/nrg3767
DO - 10.1038/nrg3767
M3 - Review article
C2 - 25001846
AN - SCOPUS:84907067643
SN - 1471-0056
VL - 15
SP - 556
EP - 570
JO - Nature Reviews Genetics
JF - Nature Reviews Genetics
IS - 8
ER -