MADAP, a flexible clustering tool for the interpretation of one-dimensional genome annotation data.
Détails
Etat: Public
Version: Final published version
ID Serval
serval:BIB_9EA1163EDBF0
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
MADAP, a flexible clustering tool for the interpretation of one-dimensional genome annotation data.
Périodique
Nucleic Acids Research
ISSN
1362-4962 (Electronic)
ISSN-L
0305-1048
Statut éditorial
Publié
Date de publication
2007
Volume
35
Numéro
Web Server issue
Pages
W201-W205
Langue
anglais
Résumé
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/.
Mots-clé
Algorithms, Chromatin Immunoprecipitation, Cluster Analysis, Computational Biology/methods, Databases, Genetic/utilization, Genome, Humans, Internet, Models, Statistical, Open Reading Frames, Promoter Regions, Genetic, Software
Pubmed
Web of science
Open Access
Oui
Création de la notice
22/04/2013 9:12
Dernière modification de la notice
20/08/2019 16:04