New Methods for Detecting Lineage-Specific Selection

Siepel, Adam, Pollard, Katherine, Haussler, David (2006) New Methods for Detecting Lineage-Specific Selection. In: Research in Computational Molecular Biology. Lecture Notes in Computer Science, 3909 . Springer Berlin Heidelberg, pp. 190-205. ISBN 978-3-540-33295-4

URL: http://link.springer.com/chapter/10.1007/11732990_...
DOI: 10.1007/11732990_17

Abstract

So far, most methods for identifying sequences under selection based on comparative sequence data have either assumed selectional pressures are the same across all branches of a phylogeny, or have focused on changes in specific lineages of interest. Here, we introduce a more general method that detects sequences that have either come under selection, or begun to drift, on any lineage. The method is based on a phylogenetic hidden Markov model (phylo-HMM), and does not require element boundaries to be determined a priori, making it particularly useful for identifying noncoding sequences. Insertions and deletions (indels) are incorporated into the phylo-HMM by a simple strategy that uses a separately reconstructed “indel history.” To evaluate the statistical significance of predictions, we introduce a novel method for computing P-values based on prior and posterior distributions of the number of substitutions that have occurred in the evolution of predicted elements. We derive efficient dynamic-programming algorithms for obtaining these distributions, given a model of neutral evolution. Our methods have been implemented as computer programs called DLESS (Detection of LinEage-Specific Selection) and phyloP (phylogenetic P-values). We discuss results obtained with these programs on both real and simulated data sets.

Item Type: Book Section
Subjects: bioinformatics
bioinformatics > computational biology
CSHL Authors:
Communities: CSHL labs > Siepel lab
Depositing User: Matt Covey
Date Deposited: 15 Jan 2015 20:31
Last Modified: 15 Jan 2015 20:31
URI: http://repository.cshl.edu/id/eprint/31040

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