recipe fragpipe

Pipeline for comprehensive analysis of shotgun proteomics data

Homepage:

https://github.com/Nesvilab/FragPipe

License:

GPL-3.0 + LICENSE files

Recipe:

/fragpipe/meta.yaml

Links:

biotools: fragpipe, doi: 10.1074/mcp.TIR120.002048

FragPipe is a Java Graphical User Interface (GUI) for a suite of computational tools enabling comprehensive analysis of mass spectrometry-based proteomics data. It is powered by MSFragger - an ultrafast proteomic search engine suitable for both conventional and "open" (wide precursor mass tolerance) peptide identification. FragPipe includes the Philosopher toolkit for downstream post-processing of MSFragger search results (PeptideProphet, iProphet, ProteinProphet), FDR filtering, label-based quantification, and multi-experiment summary report generation. Crystal-C and PTM-Shepherd are included to aid interpretation of open search results. Also included in FragPipe binary are TMT-Integrator for TMT/iTRAQ isobaric labeling-based quantification, IonQuant for label-free quantification with match-between-run (MBR) functionality, spectral library building with EasyPQP, and MSFragger-DIA and DIA-Umpire SE modules for direct analysis of data independent acquisition (DIA) data.

package fragpipe

(downloads) docker_fragpipe

Versions:

24.0-0,  23.1-0,  23.0-0,  22.0-0,  20.0-4,  20.0-3,  20.0-2,  20.0-1,  20.0-0

Depends:

  • on diatracer >=1.2.5

  • on easypqp >=0.1.34

  • on ionquant >=1.11.9

  • on lxml

  • on msfragger >=4.2

  • on openjdk >=9

  • on python 3.11.*

  • on zlib >=1.2.13

Additional platforms:

Installation

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install fragpipe

to add into an existing workspace instead, run:

pixi add fragpipe

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install fragpipe

Alternatively, to install into a new environment, run:

conda create -n envname fragpipe

with envname being the name of the desired environment.

Container

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

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

(see fragpipe/tags for valid values for <tag>).

Integrated deployment

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

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