Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Minireview cung cấp cho các bạn kiến thức về ngành y đề tài: EpiGRAPH: user-friendly software for statistical analysis and prediction of (epi)genomic data. | Open Access EpiGRAPH user-friendly software for statistical analysis and prediction of epi genomic data Christoph Bock Konstantin Halachev Joachim Buch and Thomas Lengauer Address Max-Planck-Institut fur Informatik Campus 66123 Saarbrucken Germany. Correspondence Christoph Bock. Email cbock@ Published 10 February 2009 Genome Biology 2009 10 R14 doi gb-2009- l0-2-rl4 The electronic version of this article is the complete one and can be found online at http 2009 l0 2 Rl4 Received 18 June 2008 Revised 3 December 2008 Accepted l0 February 2009 2009 Bock et al. licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract The EpiGRAPH web service http enables biologists to uncover hidden associations in vertebrate genome and epigenome datasets. Users can upload sets of genomic regions and EpiGRAPH will test multiple attributes including DNA sequence chromatin structure epigenetic modifications and evolutionary conservation for enrichment or depletion among these regions. Furthermore EpiGRAPH learns to predictively identify similar genomic regions. This paper demonstrates EpiGRAPH s practical utility in a case study on monoallelic gene expression and describes its novel approach to reproducible bioinformatic analysis. Rationale EpiGRAPH addresses two tasks that are common in genome biology discovering novel associations between a set of genomic regions with a specific biological role for example experimentally mapped enhancers hotspots of epigenetic regulation or sites exhibiting disease-specific alterations and the bulk of genome annotation data that are available from public databases and assessing whether it is possible to pre-dictively identify additional genomic
