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Combined Open and Narrow searches via Group Analysis

Project description

CONGA is a tool for discovering peptides in mass spectrometry data with rigourous FDR control. It is designed to allow for unexpected post-translational modifications as well as chimeric spectra. CONGA takes three inputs: (1) the set of top-scoring PSMs from a traditional, narrow-window search against a concatenated target-decoy database, (2) the set of top-k PSMs (or fewer if less than k PSMs exist) from an open search, again against a concatenated target-decoy database, and (3) the pairs of target and decoy peptide sequences from the database. Ideally, an additional option is set which specifies the isolation window used. Given this, CONGA will return a discovery list of peptides.

Documentation

You can find documentation on how to use CONGA over on readtheddocs. Alternatively you can find the same documentation under docs/pages in this respository.

Papers

Analysis of tandem mass spectrometry data with CONGA: Combining Open and Narrow searches with Group-wise Analysis

Re-investigating the correctness of decoy-based false discovery rate control in proteomics tandem mass spectrometry

Installation

To install, first create a virtual environment using conda:

conda create --name conga_env python=3.9

Then activate this virtual environment:

conda activate conga_env

Next download the latest release using pip:

pip install CONGA

Alternatively you can download the latest release from Github, and install using pip in the same directory as setup.py using:

pip install .

Please see the documentation, specifically the tutorial, on how to run CONGA.

Releasing

Releases are published automatically when a tag is pushed to GitHub.

# Set next version number
export RELEASE=x.x.x

# Create tags
git commit --allow-empty -m "Release $RELEASE"
git tag -a $RELEASE -m "Version $RELEASE"

# Push
git push upstream --tags

Project details


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