NDLI: Improving detection of copy-number variation by simultaneous bias correction and read-depth segmentation

Content Provider	PubMed Central
Author	Szatkiewicz, Jin P. Wang, Weibo Sullivan, Patrick F. Wang, Wei Sun, Wei
Copyright Year	2012
Abstract	Structural variation is an important class of genetic variation in mammals. High-throughput sequencing (HTS) technologies promise to revolutionize copy-number variation (CNV) detection but present substantial analytic challenges. Converging evidence suggests that multiple types of CNV-informative data (e.g. read-depth, read-pair, split-read) need be considered, and that sophisticated methods are needed for more accurate CNV detection. We observed that various sources of experimental biases in HTS confound read-depth estimation, and note that bias correction has not been adequately addressed by existing methods. We present a novel read-depth–based method, GENSENG, which uses a hidden Markov model and negative binomial regression framework to identify regions of discrete copy-number changes while simultaneously accounting for the effects of multiple confounders. Based on extensive calibration using multiple HTS data sets, we conclude that our method outperforms existing read-depth–based CNV detection algorithms. The concept of simultaneous bias correction and CNV detection can serve as a basis for combining read-depth with other types of information such as read-pair or split-read in a single analysis. A user-friendly and computationally efficient implementation of our method is freely available.
Related Links	http://dx.doi.org/10.1093/nar/gks1363
Ending Page	1532
Page Count	14
Starting Page	1519
File Format	PDF
ISSN	03051048
e-ISSN	13624962
Journal	Nucleic Acids Research
Issue Number	3
Volume Number	41
Language	English
Publisher	Oxford University Press
Publisher Date	2013-02-01
Access Restriction	Open
Rights Holder	Oxford University Press
Subject Keyword	Genetics Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Genetics

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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