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.de
Supplementary information: Supplementary data are available at Bioinformatics online.
© The Author 2016. Published by Oxford University Press.