Discovering similar (epi)genomics feature patterns in multiple genome browser tracks.

Next Generation Sequencing (NGS), with the high amount of heterogeneous data that it is generating, is opening many interesting practical and theoretical computational problems. Genome browsers, e.g. UCSC Genome Browser (Kuhn et al., 2013) or Integrated Genome Browser (IGB) (Nicol et al., 2009), allow visual inspection and identification of interesting patterns on multiple genome browser tracks, i.e. of sets of (epi)genomic regions/peaks at given distances from each other in different tracks. For example, such patterns can describe gene expression regulatory DNA areas including heterogeneous (epi)genomic features (e.g. histone modification and/or different transcription factor binding regions). Yet, once such patterns are visually identified in a genome section, the search of their occurrences along the whole genome is a complex computational task that is currently not supported, despite their discovery along the whole genome is very important for the biological interpretation of NGS experimental results and comprehension of biomolecular phenomena. We defined an optimized pattern-search algorithm able to find efficiently, within a large set of (epi)genomic data, genomic region sets which are similar to a given pattern. We implemented it within an IGB plugin, which allows intuitive user interaction in both the visual selection of an interesting pattern on the loaded IGB tracks, and the visualization of occurrences of similar patterns identified along the entire genome.