TY - GEN
T1 - Genome-wide survival analysis of somatic mutations in cancer
AU - Vandin, Fabio
AU - Papoutsaki, Alexandra
AU - Raphael, Benjamin J.
AU - Upfal, Eli
N1 - Funding Information:
This work is supported by NSF grant IIS-1016648.
PY - 2013
Y1 - 2013
N2 - Motivation. Next-generation DNA sequencing technologies now enable the measurement of exomes, genomes, and mRNA expression in many samples. The next challenge is to interpret these large quantities of DNA and RNA sequence data. In many human and cancer genomics studies, a major goal is to discover associations between an observed phenotype and a particular variable from genome-wide measurements of many such variables. In this work we consider the problem of testing the association between a DNA sequence variant and the survival time, or length of time that patients live following diagnosis or treatment. This problem is relevant to many cancer sequencing studies, in which one aims to discover somatic variants that distinguish patients with fast-growing tumors that require aggressive treatment from patients with better prognosis [1].
AB - Motivation. Next-generation DNA sequencing technologies now enable the measurement of exomes, genomes, and mRNA expression in many samples. The next challenge is to interpret these large quantities of DNA and RNA sequence data. In many human and cancer genomics studies, a major goal is to discover associations between an observed phenotype and a particular variable from genome-wide measurements of many such variables. In this work we consider the problem of testing the association between a DNA sequence variant and the survival time, or length of time that patients live following diagnosis or treatment. This problem is relevant to many cancer sequencing studies, in which one aims to discover somatic variants that distinguish patients with fast-growing tumors that require aggressive treatment from patients with better prognosis [1].
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U2 - 10.1007/978-3-642-37195-0_26
DO - 10.1007/978-3-642-37195-0_26
M3 - Conference contribution
AN - SCOPUS:84875526491
SN - 9783642371943
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 285
EP - 286
BT - Research in Computational Molecular Biology - 17th Annual International Conference, RECOMB 2013, Proceedings
T2 - 17th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2013
Y2 - 7 April 2013 through 10 April 2013
ER -