TY - JOUR
T1 - Studying Cancer Genomics Through Next-Generation DNA Sequencing and Bioinformatics
AU - Doyle, Maria A.
AU - Li, Jason
AU - Doig, Ken
AU - Fellowes, Andrew
AU - Wong, Stephen Q.
N1 - Publisher Copyright:
© Springer Science+Business Media New York 2014.
PY - 2014
Y1 - 2014
N2 - Cancer is a complex disease driven by multiple mutations acquired over the lifetime of the cancer cells. These alterations, termed somatic mutations to distinguish them from inherited germline mutations, can include single-nucleotide substitutions, insertions, deletions, copy number alterations, and structural rearrangements. A patient’s cancer can contain a combination of these aberrations, and the ability to generate a comprehensive genetic profile should greatly improve patient diagnosis and treatment. Next-generation sequencing has become the tool of choice to uncover multiple cancer mutations from a single tumor source, and the falling costs of this rapid high-throughput technology are encouraging its transition from basic research into a clinical setting. However, the detection of mutations in sequencing data is still an evolving area and cancer genomic data requires some special considerations. This chapter discusses these aspects and gives an overview of current bioinformatics methods for the detection of somatic mutations in cancer sequencing data.
AB - Cancer is a complex disease driven by multiple mutations acquired over the lifetime of the cancer cells. These alterations, termed somatic mutations to distinguish them from inherited germline mutations, can include single-nucleotide substitutions, insertions, deletions, copy number alterations, and structural rearrangements. A patient’s cancer can contain a combination of these aberrations, and the ability to generate a comprehensive genetic profile should greatly improve patient diagnosis and treatment. Next-generation sequencing has become the tool of choice to uncover multiple cancer mutations from a single tumor source, and the falling costs of this rapid high-throughput technology are encouraging its transition from basic research into a clinical setting. However, the detection of mutations in sequencing data is still an evolving area and cancer genomic data requires some special considerations. This chapter discusses these aspects and gives an overview of current bioinformatics methods for the detection of somatic mutations in cancer sequencing data.
KW - Bioinformatics
KW - Cancer
KW - Copy number alterations
KW - Next-generation sequencing
KW - Somatic mutations
KW - Structural rearrangements
UR - http://www.scopus.com/inward/record.url?scp=84922311454&partnerID=8YFLogxK
U2 - 10.1007/978-1-4939-0847-9_6
DO - 10.1007/978-1-4939-0847-9_6
M3 - Article
C2 - 24870132
AN - SCOPUS:84922311454
SN - 1064-3745
VL - 1168
SP - 83
EP - 98
JO - Methods in Molecular Biology
JF - Methods in Molecular Biology
ER -