Publications by authors named "Rouayda Cavin Périer"

3 Publications

  • Page 1 of 1

MGA repository: a curated data resource for ChIP-seq and other genome annotated data.

Nucleic Acids Res 2018 01;46(D1):D175-D180

Swiss Institute of Bioinformatics (SIB), CH-1015 Lausanne, Switzerland.

The Mass Genome Annotation (MGA) repository is a resource designed to store published next generation sequencing data and other genome annotation data (such as gene start sites, SNPs, etc.) in a completely standardised format. Each sample has undergone local processing in order the meet the strict MGA format requirements. The original data source, the reformatting procedure and the biological characteristics of the samples are described in an accompanying documentation file manually edited by data curators. 10 model organisms are currently represented: Homo sapiens, Mus musculus, Danio rerio, Drosophila melanogaster, Apis mellifera, Caenorhabditis elegans, Arabidopsis thaliana, Zea mays, Saccharomyces cerevisiae and Schizosaccharomyces pombe. As of today, the resource contains over 24 000 samples. In conjunction with other tools developed by our group (the ChIP-Seq and SSA servers), it allows users to carry out a great variety of analysis task with MGA samples, such as making aggregation plots and heat maps for selected genomic regions, finding peak regions, generating custom tracks for visualizing genomic features in a UCSC genome browser window, or downloading chromatin data in a table format suitable for local processing with more advanced statistical analysis software such as R. Home page: http://ccg.vital-it.ch/mga/.
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http://dx.doi.org/10.1093/nar/gkx995DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5753388PMC
January 2018

The Eukaryotic Promoter Database: expansion of EPDnew and new promoter analysis tools.

Nucleic Acids Res 2015 Jan 6;43(Database issue):D92-6. Epub 2014 Nov 6.

Swiss Institute of Bioinformatics (SIB), CH-1015 Lausanne, Switzerland Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, Swiss Federal Institute of Technology (EPFL), CH-1015 Lausanne, Switzerland

We present an update of EPDNew (http://epd.vital-it.ch), a recently introduced new part of the Eukaryotic Promoter Database (EPD) which has been described in more detail in a previous NAR Database Issue. EPD is an old database of experimentally characterized eukaryotic POL II promoters, which are conceptually defined as transcription initiation sites or regions. EPDnew is a collection of automatically compiled, organism-specific promoter lists complementing the old corpus of manually compiled promoter entries of EPD. This new part is exclusively derived from next generation sequencing data from high-throughput promoter mapping experiments. We report on the recent growth of EPDnew, its extension to additional model organisms and its improved integration with other bioinformatics resources developed by our group, in particular the Signal Search Analysis and ChIP-Seq web servers.
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http://dx.doi.org/10.1093/nar/gku1111DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4383928PMC
January 2015

EPD and EPDnew, high-quality promoter resources in the next-generation sequencing era.

Nucleic Acids Res 2013 Jan 27;41(Database issue):D157-64. Epub 2012 Nov 27.

Swiss Institute of Bioinformatics (SIB), CH-1015 Lausanne, Switzerland.

The Eukaryotic Promoter Database (EPD), available online at http://epd.vital-it.ch, is a collection of experimentally defined eukaryotic POL II promoters which has been maintained for more than 25 years. A promoter is represented by a single position in the genome, typically the major transcription start site (TSS). EPD primarily serves biologists interested in analysing the motif content, chromatin structure or DNA methylation status of co-regulated promoter subsets. Initially, promoter evidence came from TSS mapping experiments targeted at single genes and published in journal articles. Today, the TSS positions provided by EPD are inferred from next-generation sequencing data distributed in electronic form. Traditionally, EPD has been a high-quality database with low coverage. The focus of recent efforts has been to reach complete gene coverage for important model organisms. To this end, we introduced a new section called EPDnew, which is automatically assembled from multiple, carefully selected input datasets. As another novelty, we started to use chromatin signatures in addition to mRNA 5'tags to locate promoters of weekly expressed genes. Regarding user interfaces, we introduced a new promoter viewer which enables users to explore promoter-defining experimental evidence in a UCSC genome browser window.
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http://dx.doi.org/10.1093/nar/gks1233DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3531148PMC
January 2013