Skip to Main content Skip to Navigation
New interface
Journal articles

X!TandemPipeline: a tool to manage sequence redundancy for protein inference and phosphosite identification

Abstract : X!TandemPipeline is a software designed to perform protein inference and to manage redundancy in the results of phosphosite identification by database search. It provides the minimal list of proteins or phosphosites that are present in a set of samples using grouping algorithms based on the principle of parsimony. Regarding proteins, a two-level classification is performed, where groups gather proteins sharing at least one peptide and subgroups gather proteins that are not distinguishable according to the identified peptides. Regarding phosphosites, an innovative approach based on the concept of phosphoisland is used to gather overlapping phosphopeptides. The graphical interface of X!TandemPipeline allows the users to launch X!tandem identification, to inspect spectra and to manually validate their assignment to peptides, to launch the grouping program, and to visualize elementary data as well as grouping and redundancy information. Identification results obtained from other search engines can also be processed. X!TandemPipeline results can be exported as ready-to-use tabulated files or as XML files that can be directly used by the PROTICdb database or by the MassChroQ quantification software. X!TandemPipeline runs fast, is easy to use, and can process hundreds of samples simultaneously. It is freely available under the GNU General Public License v3.0 at .
Document type :
Journal articles
Complete list of metadata
Contributor : Archive Ouverte ProdInra Connect in order to contact the contributor
Submitted on : Monday, March 6, 2017 - 8:37:06 PM
Last modification on : Monday, October 17, 2022 - 1:29:40 PM



Olivier Langella, Benoît Valot, Thierry Balliau, Melisande Blein-Nicolas, Ludovic Bonhomme, et al.. X!TandemPipeline: a tool to manage sequence redundancy for protein inference and phosphosite identification. Journal of Proteome Research, 2017, 16 (2), pp.494-503. ⟨10.1021/acs.jproteome.6b00632⟩. ⟨hal-01484169⟩



Record views