title: Multiple alignment-free sequence comparison.
abstract: BACKGROUND
  Recently, a range of new statistics have become available for the alignment-free comparison of two sequences based on k-tuple word content. Here, we extend these statistics to the simultaneous comparison of more than two sequences. Our suite of statistics contains, first, C(*)1 and C(S)1, extensions of statistics for pairwise comparison of the joint k-tuple content of all the sequences, and second, C(*)2, C(S)2 and C(geo)2, averages of sums of pairwise comparison statistics. The two tasks we consider are, first, to identify sequences that are similar to a set of target sequences, and, second, to measure the similarity within a set of sequences.
  
  
  RESULTS
  Our investigation uses both simulated data as well as cis-regulatory module data where the task is to identify cis-regulatory modules with similar transcription factor binding sites. We find that although for real data, all of our statistics show a similar performance, on simulated data the Shepp-type statistics are in some instances outperformed by star-type statistics. The multiple alignment-free statistics are more sensitive to contamination in the data than the pairwise average statistics.
  
  
  BACKGROUND
  Our implementation of the five statistics is available as R package named 'multiAlignFree' at be http://www-rcf.usc.edu/∼fsun/Programs/multiAlignFree/multiAlignFreemain.html.
  
  
  BACKGROUND
  reinert@stats.ox.ac.uk.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: School of Mathematics, Peking University, Beijing 100871, PR China, Molecular and Computational Biology, University of Southern California, Los Angeles, CA 90089-2910, USA, MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, PR China and Department of Statistics, University of Oxford, 1 South Parks Road, Oxford OX1 3TG, UK.
authors.forename: Jie
authors.initials: J
authors.lastname: Ren
authors.forename: Kai
authors.initials: K
authors.lastname: Song
authors.forename: Fengzhu
authors.initials: F
authors.lastname: Sun
authors.forename: Minghua
authors.initials: M
authors.lastname: Deng
authors.forename: Gesine
authors.initials: G
authors.lastname: Reinert
mesh_terms: D000818:Animals; D001665:Binding Sites; D003627:Data Interpretation, Statistical; D051379:Mice; D050436:Regulatory Elements, Transcriptional; D016415:Sequence Alignment; D017422:Sequence Analysis, DNA / Q000379:methods*; D014157:Transcription Factors / Q000378:metabolism
chemical_list: D014157:Transcription Factors