recipe msfragger

Ultrafast, comprehensive peptide identification for mass spectrometry–based proteomics

Homepage:

https://github.com/Nesvilab/MSFragger

License:

Academic License (https://msfragger.arsci.com/upgrader/MSFragger-LICENSE.pdf)

Recipe:

/msfragger/meta.yaml

Links:

doi: 10.1038/nmeth.4256, doi: 10.1038/s41467-020-17921-y, doi: 10.1038/s41592-020-0967-9

MSFragger is an ultrafast database search tool for peptide identification in mass spectrometry-based proteomics. It has demonstrated excellent performance across a wide range of datasets and applications. MSFragger is suitable for standard shotgun proteomics analyses as well as large datasets (including timsTOF PASEF data), enzyme unconstrained searches (e.g., peptidome), open database searches (e.g., precursor mass tolerance set to hundreds of Daltons) for identification of modified peptides, and glycopeptide identification (N-linked and O-linked).

MSFragger is available freely for academic research and educational purposes only, in accordance with the terms at https://msfragger.arsci.com/upgrader/MSFragger-LICENSE.pdf.

package msfragger

(downloads) docker_msfragger

versions:

4.0-1,  4.0-0

depends mono:

>=5,<6

depends openjdk:

>=11

depends python:

>=3.9

depends zlib:

>=1.2.13

requirements:

Installation

You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install msfragger

and update with::

   mamba update msfragger

To create a new environment, run:

mamba create --name myenvname msfragger

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull quay.io/biocontainers/msfragger:<tag>

(see `msfragger/tags`_ for valid values for ``<tag>``)

Notes

The "msfragger" command runs the MSFragger java program.

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