title: On the comparison of regulatory sequences with multiple resolution Entropic Profiles.
abstract: BACKGROUND
  Enhancers are stretches of DNA (100-1000 bp) that play a major role in development gene expression, evolution and disease. It has been recently shown that in high-level eukaryotes enhancers rarely work alone, instead they collaborate by forming clusters of cis-regulatory modules (CRMs). Although the binding of transcription factors is sequence-specific, the identification of functionally similar enhancers is very difficult and it cannot be carried out with traditional alignment-based techniques.
  
  
  RESULTS
  The use of fast similarity measures, like alignment-free measures, to detect related regulatory sequences is crucial to understand functional correlation between two enhancers. In this paper we study the use of alignment-free measures for the classification of CRMs. However, alignment-free measures are generally tied to a fixed resolution k. Here we propose an alignment-free statistic, called [Formula: see text], that is based on multiple resolution patterns derived from the Entropic Profiles (EPs). The Entropic Profile is a function of the genomic location that captures the importance of that region with respect to the whole genome. As a byproduct we provide a formula to compute the exact variance of variable length word counts, a result that can be of general interest also in other applications.
  
  
  CONCLUSIONS
  We evaluate several alignment-free statistics on simulated data and real mouse ChIP-seq sequences. The new statistic, [Formula: see text], is highly successful in discriminating functionally related enhancers and, in almost all experiments, it outperforms fixed-resolution methods. We implemented the new alignment-free measures, as well as traditional ones, in a software called EP-sim that is freely available: http://www.dei.unipd.it/~ciompin/main/EP-sim.html .
authors.affiliation: Department of Information Engineering, University of Padova, Padova, Italy. comin@dei.unipd.it.
authors.forename: Matteo
authors.initials: M
authors.lastname: Comin
authors.affiliation: Department of Information Engineering, University of Padova, Padova, Italy.
authors.forename: Morris
authors.initials: M
authors.lastname: Antonello
mesh_terms: D000818:Animals; D004330:Drosophila / Q000235:genetics; D004742:Enhancer Elements, Genetic; D019277:Entropy; D023281:Genomics / Q000379:methods; D051379:Mice; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software
keywords: Alignment-free; Entropic profiles; Sequence comparison