Dataset Information
Homology-driven assembly of NOn-redundant protEin sequence sets (NOmESS) for mass spectrometry.
Ontology highlight
ABSTRACT: Unlabelled
To enable mass spectrometry (MS)-based proteomic studies with poorly characterized organisms, we developed a computational workflow for the homology-driven assembly of a non-redundant reference sequence dataset. In the automated pipeline, translated DNA sequences (e.g. ESTs, RNA deep-sequencing data) are aligned to those of a closely related and fully sequenced organism. Representative sequences are derived from each cluster and joined, resulting in a non-redundant reference set representing the maximal available amino acid sequence information for each protein. We here applied NOmESS to assemble a reference database for the widely used model organism Xenopus laevis and demonstrate its use in proteomic applications.Availability and implementation
NOmESS is written in C#. The source code as well as the executables can be downloaded from http://www.biochem.mpg.de/cox Execution of NOmESS requires BLASTp and cd-hit in addition.Contact
cox@biochem.mpg.deSupplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Temu T
PROVIDER: S-EPMC4848398 | biostudies-literature | 2016 May
REPOSITORIES: biostudies-literature
Publications
Homology-driven assembly of NOn-redundant protEin sequence sets (NOmESS) for mass spectrometry.
Bioinformatics (Oxford, England) 20160106 9
<h4>Unlabelled</h4>To enable mass spectrometry (MS)-based proteomic studies with poorly characterized organisms, we developed a computational workflow for the homology-driven assembly of a non-redundant reference sequence dataset. In the automated pipeline, translated DNA sequences (e.g. ESTs, RNA deep-sequencing data) are aligned to those of a closely related and fully sequenced organism. Representative sequences are derived from each cluster and joined, resulting in a non-redundant reference s ...[more]