title: Beyond Fixed-Resolution Alignment-Free Measures for Mammalian Enhancers Sequence Comparison.
abstract: The cell-type diversity is to a large degree driven by transcription regulation, i.e., enhancers. 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). Even if the binding of transcription factors is sequence-specific, the identification of functionally similar enhancers is very difficult. A similarity measure to detect related regulatory sequences is crucial to understand functional correlation between two enhancers. This will allow large-scale analyses, clustering and genome-wide classifications. In this paper we present Under2, a parameter-free alignment-free statistic based on variable-length words. As opposed to traditional alignment-free methods, which are based on fixed-length patterns or, in other words, tied to a fixed resolution, our statistic is built upon variable-length words, and thus multiple resolutions are allowed. This will capture the great variability of lengths of CRMs. We evaluate several alignment-free statistics on simulated data and real ChIP-seq sequences. The new statistic is highly successful in discriminating functionally related enhancers and, in almost all experiments, it outperforms fixed-resolution methods. Finally, experiments on mouse enhancers show that Under2 can separate enhancers active in different tissues.
  
  
  BACKGROUND
  http://www.dei.unipd.it/~ciompin/main/UnderIICRMS.html.
authors.forename: Matteo
authors.initials: M
authors.lastname: Comin
authors.forename: Davide
authors.initials: D
authors.lastname: Verzotto
mesh_terms: D000818:Animals; D004742:Enhancer Elements, Genetic / Q000235:genetics*; D023281:Genomics / Q000379:methods*; D006801:Humans; D008322:Mammals / Q000235:genetics*; D051379:Mice; D017422:Sequence Analysis, DNA / Q000379:methods*