Literature DB >> 18324742

Two plus two does not equal three: statistical tests for multiple genome comparison.

Narayanan Raghupathy1, Rose Hoberman, Dannie Durand.   

Abstract

Gene clusters that span three or more chromosomal regions are of increasing importance, yet statistical tests to validate such clusters are in their infancy. Current approaches either conduct several pairwise comparisons or consider only the number of genes that occur in all of the regions. In this paper, we provide statistical tests for clusters spanning exactly three regions based on genome models of typical comparative genomics problems, including analysis of conserved linkage within multiple species and identification of large-scale duplications. Our tests are the first to combine evidence from genes shared among all three regions and genes shared between pairs of regions. We show that our tests of clusters spanning three regions are more sensitive than existing approaches, and can thus be used to identify more diverged homologous regions.

Mesh:

Year:  2008        PMID: 18324742     DOI: 10.1142/s0219720008003242

Source DB:  PubMed          Journal:  J Bioinform Comput Biol        ISSN: 0219-7200            Impact factor:   1.122


  3 in total

1.  Statistics for approximate gene clusters.

Authors:  Katharina Jahn; Sascha Winter; Jens Stoye; Sebastian Böcker
Journal:  BMC Bioinformatics       Date:  2013-12-13       Impact factor: 3.169

2.  Gene cluster statistics with gene families.

Authors:  Narayanan Raghupathy; Dannie Durand
Journal:  Mol Biol Evol       Date:  2009-01-15       Impact factor: 16.240

3.  PhylDiag: identifying complex synteny blocks that include tandem duplications using phylogenetic gene trees.

Authors:  Joseph M E X Lucas; Matthieu Muffato; Hugues Roest Crollius
Journal:  BMC Bioinformatics       Date:  2014-08-08       Impact factor: 3.169

  3 in total

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