VarQuest

Description

VarQuest is a novel algorithm for identification of PNP variants via database search of mass spectra, the first high-throughput mutation-tolerant PNP identification method capable of analysing the entire GNPS infrastructure. VarQuest is based on Dereplicator source code, a method aimed at standard PNP identification.

How to run

You can try VarQuest online at GNPS website (registration is needed but it is quick and simple). Our tool is embedded into Dereplicator workflow (use “Search analogs” checkbox to enable VarQuest). See documentation for details.

Also we provide the command line version as part of NPDtools package, see links below. Running instructions are specified in the README file inside the package.

Download NPDtools binaries for Linux (64-bit only)

Download NPDtools binaries for MacOS

News

We publicly released the first command line version of our tool, see download links above.

Our poster (B-363) was presented at ISMB/ECCB 2017 in Prague (Czech Republic).

Examples of VarQuest output

Interactive PSM viewers of VarQuest identifications on various GNPS datasets:

  1. Surugamide-783 identified in MSV000078604 dataset.
  2. Surugamide-769 identified in MSV000078604 dataset.
  3. Pristinamycin-733 identified in MSV000078604 dataset.
  4. Venepeptide-2138 identified in MSV000078839 dataset.
  5. Venepeptide-2154 identified in MSV000078839 dataset.
  6. Wollamide-1017 identified in MSV000078604 dataset.
  7. WS9326C-1036 identified in MSV000078604 dataset.
  8. Massetolide-1252 identified in MSV000079450 dataset.

Example of chemical structures database: PNPdatabase (5021 compounds in MOL V3000 format and the description file needed for VarQuest/Dereplicator).

List of 120 MassIVE accession numbers used in VarQuest benchmarking on the entire GNPS.

Contact

In case of any questions, suggestions, bug reports, please write to .

The tool is developed in collaboration with University of California, San Diego.

Publications

  1. Gurevich A., Mikheenko A., Shlemov A., Korobeynikov A., Mohimani H., Pevzner P. A. Modification-tolerant database search reveals surprising diversity of peptidic natural products. Submitted, 2017