TY - GEN
T1 - Identification of co-occurring insertions in cancer genomes using association analysis
AU - Steinbach, Michael
AU - Yu, Haoyu
AU - Kumar, Vipin
PY - 2010
Y1 - 2010
N2 - Collections of tumor genomes created by insertional mutagenesis experiments, e.g., the Retroviral Tagged Cancer Gene Database, can be analyzed to find connections between mutations of specific genes and cancer. Such connections are found by identifying the locations of insertions or groups of insertions that frequently occur in the collection of tumor genomes. Recent work has employed a kernel density approach to find such commonly occurring insertions or co-occurring pairs of insertions. Unfortunately, this approach is extremely compute intensive for pairs of insertions, and even more intractable for triples, etc. We present a novel approach that combines kernel density and association analysis (frequent pattern mining) techniques to efficiently find commonly co-occurring sets of insertions of any length. More generally, this approach can be used to find other commonly occurring features in collections of genomes.
AB - Collections of tumor genomes created by insertional mutagenesis experiments, e.g., the Retroviral Tagged Cancer Gene Database, can be analyzed to find connections between mutations of specific genes and cancer. Such connections are found by identifying the locations of insertions or groups of insertions that frequently occur in the collection of tumor genomes. Recent work has employed a kernel density approach to find such commonly occurring insertions or co-occurring pairs of insertions. Unfortunately, this approach is extremely compute intensive for pairs of insertions, and even more intractable for triples, etc. We present a novel approach that combines kernel density and association analysis (frequent pattern mining) techniques to efficiently find commonly co-occurring sets of insertions of any length. More generally, this approach can be used to find other commonly occurring features in collections of genomes.
KW - Cancer genomes
KW - Frequent pattern mining
KW - Kernel density
UR - http://www.scopus.com/inward/record.url?scp=79952019158&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79952019158&partnerID=8YFLogxK
U2 - 10.1109/BIBMW.2010.5703851
DO - 10.1109/BIBMW.2010.5703851
M3 - Conference contribution
AN - SCOPUS:79952019158
SN - 9781424483044
T3 - 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2010
SP - 494
EP - 499
BT - 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2010
T2 - 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2010
Y2 - 18 December 2010 through 21 December 2010
ER -