Dataset Information
Spliceman2: a computational web server that predicts defects in pre-mRNA splicing.
Ontology highlight
ABSTRACT: Summary
Most pre-mRNA transcripts in eukaryotic cells must undergo splicing to remove introns and join exons, and splicing elements present a large mutational target for disease-causing mutations. Splicing elements are strongly position dependent with respect to the transcript annotations. In 2012, we presented Spliceman, an online tool that used positional dependence to predict how likely distant mutations around annotated splice sites were to disrupt splicing. Here, we present an improved version of the previous tool that will be more useful for predicting the likelihood of splicing mutations. We have added industry-standard input options (i.e. Spliceman now accepts variant call format files), which allow much larger inputs than previously available. The tool also can visualize the locations-within exons and introns-of sequence variants to be analyzed and the predicted effects on splicing of the pre-mRNA transcript. In addition, Spliceman2 integrates with RNAcompete motif libraries to provide a prediction of which trans -acting factors binding sites are disrupted/created and links out to the UCSC genome browser. In summary, the new features in Spliceman2 will allow scientists and physicians to better understand the effects of single nucleotide variations on splicing.Availability and implementation
Freely available on the web at http://fairbrother.biomed.brown.edu/spliceman2 . Website implemented in PHP framework-Laravel 5, PostgreSQL, Apache, and Perl, with all major browsers supported.Contact
william_fairbrother@brown.edu.Supplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Cygan KJ
PROVIDER: S-EPMC5870721 | biostudies-literature | 2017 Sep
REPOSITORIES: biostudies-literature
Publications
Spliceman2: a computational web server that predicts defects in pre-mRNA splicing.
Bioinformatics (Oxford, England) 20170901 18
<h4>Summary</h4>Most pre-mRNA transcripts in eukaryotic cells must undergo splicing to remove introns and join exons, and splicing elements present a large mutational target for disease-causing mutations. Splicing elements are strongly position dependent with respect to the transcript annotations. In 2012, we presented Spliceman, an online tool that used positional dependence to predict how likely distant mutations around annotated splice sites were to disrupt splicing. Here, we present an impro ...[more]