Finding recurrent copy number alterations preserving within-sample homogeneity
Author(s) -
Sandro Morganella,
Stefano Maria Pagnotta,
Michele Ceccarelli
Publication year - 2011
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btr488
Subject(s) - bioconductor , computer science , homogeneity (statistics) , comparative genomic hybridization , computational biology , identification (biology) , biology , machine learning , genetics , genome , gene , botany
Copy number alterations (CNAs) represent an important component of genetic variation and play a significant role in many human diseases. Development of array comparative genomic hybridization (aCGH) technology has made it possible to identify CNAs. Identification of recurrent CNAs represents the first fundamental step to provide a list of genomic regions which form the basis for further biological investigations. The main problem in recurrent CNAs discovery is related to the need to distinguish between functional changes and random events without pathological relevance. Within-sample homogeneity represents a common feature of copy number profile in cancer, so it can be used as additional source of information to increase the accuracy of the results. Although several algorithms aimed at the identification of recurrent CNAs have been proposed, no attempt of a comprehensive comparison of different approaches has yet been published.
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