Using PQ trees for comparative genomics

Research output: Contribution to journalConference articlepeer-review

Abstract

Permutations on strings representing gene clusters on genomes have been studied earlier in [3, 12, 14, 17, 18] and the idea of a maximal permutation pattern was introduced in [12]. In this paper, we present a new tool for representation and detection of gene clusters in multiple genomes, using PQ trees [6]: this describes the inner structure and the relations between clusters succinctly, aids in filtering meaningful from apparently meaningless clusters and also gives a natural and meaningful way of visualizing complex clusters. We identify a minimal consensus PQ tree and prove that it is equivalent to a maximal πpattern [12] and each subgraph of the PQ tree corresponds to a non-maximal permutation pattern. We present a general scheme to handle multiplicity in permutations and also give a linear time algorithm to construct the minimal consensus PQ tree. Further, we demonstrate the results on whole genome data sets. In our analysis of the whole genomes of human and rat we found about 1.5 million common gene clusters but only about 500 minimal consensus PQ trees, and, with E Coli K-12 and B Subtilis genomes we found only about 450 minimal consensus PQ trees out of about 15,000 gene clusters. Further, we show specific instances of functionally related genes in the two cases.

Original languageEnglish
Pages (from-to)128-143
Number of pages16
JournalLecture Notes in Computer Science
Volume3537
DOIs
StatePublished - 2005
EventOt16th Annual Symposium on Combinatorial Pattern Matching, CPM 2005 - Jeju Island, Korea, Republic of
Duration: 19 Jun 200522 Jun 2005

Keywords

  • Clusters
  • Comparative genomics
  • Data mining
  • Evolutionary analysis
  • Motifs
  • PQ trees
  • Pattern discovery
  • Patterns
  • Permutation patterns
  • Whole genome analysis

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)

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