%0 Journal Article
%T GPAT: Retrieval of genomic annotation from large genomic position datasets
%A Arnaud Krebs
%A Mattia Frontini
%A L¨¤szl¨° Tora
%J BMC Bioinformatics
%D 2008
%I BioMed Central
%R 10.1186/1471-2105-9-533
%X To address this problem, we have developed a Genomic Position Annotation Tool (GPAT) with a simple web interface that allows the rapid and systematic labelling of thousands of genomic positions with several types of annotations. GPAT automatically extracts gene annotation information around the submitted positions from different public databases (Refseq or ENSEMBL). In addition, GPAT provides access to the expression status of the corresponding genes from either existing transcriptomic databases or from user generated expression data sets. Furthermore, GPAT allows the localisation of the genomic coordinates relative to the chromosome bands and the well characterised ENCODE regions. We successfully used GPAT to analyse ChIP on chip data and to identify genes functionally regulated by the TATA binding protein (TBP).GPAT provides a quick, convenient and flexible way to annotate large sets of genomic positions obtained after pre-analysis of ChIP-chip, ChIP-seq or other high throughput sequencing-based techniques. Through the different annotation data displayed, GPAT facilitates the interpretation of genome wide datasets for molecular biologists.One of the major issues in genomics is the genome wide mapping of transcription factor binding sites in order to study their function at the scale of the genome. The chromatin immunoprecipitation (ChIP) technique uses antibodies that are specific for a transcription factor or a chromatin modification, to isolate the DNA to which this factor or modified histone is bound in a cell at a given time. The recent appearance of several genome wide analysis techniques, where ChIP is either followed by DNA microarray analysis (ChIP on chip) or coupled to high throughput sequencing (ChIP-seq), made the genome wide mapping of DNA bound factors technically possible. However, these analyses generate tremendous amounts of genomic location data in the form of one-dimensional series of signals.Recently, efforts have been made to develop academic
%U http://www.biomedcentral.com/1471-2105/9/533