recipe proteomiqon-psmstatistics

The PSMStatistics tool utilizes semi supervised machine learning techniques to integrate search engine scores as well as the mentioned quality scores into one single consensus score.

Homepage:

https://csbiology.github.io/ProteomIQon/

Documentation:

https://csbiology.github.io/ProteomIQon/tools/PSMStatistics.html

Developer docs:

https://github.com/CSBiology/ProteomIQon

License:

MIT

Recipe:

/proteomiqon-psmstatistics/meta.yaml

To measure the similarity of in silico generated spectra and measured MS/MS scans we use our own implementations of three established search enginge scores: SEQUEST, Andromeda and XTandem. Additionally, we also record quality control parameters such as the mass difference between the precursor ion and the theoretically calulated mass or the uniquness of each score in comparison to 'competing' peptides within the search space. The PSMStatistics tool utilizes semi supervised machine learning techniques to integrate search engine scores as well as the mentioned quality scores into one single consensus score. Since the search space is extended by so called decoys - reversed counterparts of peptides within the search space - we can estimate the distribution of 'true negatives' and calculate local (PEP values) and global (Q values) false discovery rates at each consensus score. The reported peptides at user defined local and global FDR cutoffs can then be used as inputs for any downstream analysis be it ProteinInference or PSMBasedQuantification.

package proteomiqon-psmstatistics

versions:

0.0.8-0,  0.0.7-1,  0.0.7-0,  0.0.6-0,  0.0.5-0,  0.0.4-0,  0.0.3-0

depends dotnet-runtime:

5.0.*

depends openssl:

1.1.*

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 proteomiqon-psmstatistics

and update with::

   mamba update proteomiqon-psmstatistics

To create a new environment, run:

mamba create --name myenvname proteomiqon-psmstatistics

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/proteomiqon-psmstatistics:<tag>

(see `proteomiqon-psmstatistics/tags`_ for valid values for ``<tag>``)

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