title: MADAP, a flexible clustering tool for the interpretation of one-dimensional genome annotation data.
abstract: A recurring task in the analysis of mass genome annotation data from high-throughput technologies is the identification of peaks or clusters in a noisy signal profile. Examples of such applications are the definition of promoters on the basis of transcription start site profiles, the mapping of transcription factor binding sites based on ChIP-chip data and the identification of quantitative trait loci (QTL) from whole genome SNP profiles. Input to such an analysis is a set of genome coordinates associated with counts or intensities. The output consists of a discrete number of peaks with respective volumes, extensions and center positions. We have developed for this purpose a flexible one-dimensional clustering tool, called MADAP, which we make available as a web server and as standalone program. A set of parameters enables the user to customize the procedure to a specific problem. The web server, which returns results in textual and graphical form, is useful for small to medium-scale applications, as well as for evaluation and parameter tuning in view of large-scale applications, requiring a local installation. The program written in C++ can be freely downloaded from ftp://ftp.epd.unil.ch/pub/software/unix/madap. The MADAP web server can be accessed at http://www.isrec.isb-sib.ch/madap/.
authors.affiliation: Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland. christoph.schmid@isb-sib.ch
authors.forename: Christoph D
authors.initials: CD
authors.lastname: Schmid
authors.forename: Thierry
authors.initials: T
authors.lastname: Sengstag
authors.forename: Philipp
authors.initials: P
authors.lastname: Bucher
authors.forename: Mauro
authors.initials: M
authors.lastname: Delorenzi
mesh_terms: D000465:Algorithms; D047369:Chromatin Immunoprecipitation; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic / Q000706:statistics & numerical data; D016678:Genome; D006801:Humans; D020407:Internet; D015233:Models, Statistical; D016366:Open Reading Frames; D011401:Promoter Regions, Genetic; D012984:Software