recipe proteomiqon-alignmentbasedquantification

Given an MS run in the mzLite or mzml format and a list of a list of peptides deduced by alignment, this tool iterates accross all and performs an XIC extration and quantification in similar to the PSMbasedQuantification tool.

Homepage:

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

Documentation:

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

Developer docs:

https://github.com/CSBiology/ProteomIQon

License:

MIT

Recipe:

/proteomiqon-alignmentbasedquantification/meta.yaml

Given an MS run in the mzLite or mzml format and a list of a list of peptides deduced by alignment., this tool iterates accross all and performs an XIC extration and quantification in similar to the PSMbasedQuantification tool. One of the drawbacks of data-dependent acquisition is the stochastic nature of peptide ion selection for MSMS fragmentation as a prerequisite for peptide identification and quantification. A way to overcome this drawback is the transfer of identified ions from one run to another using the assumption that the run is merely lacking a successful MSMS scan, but still containing the peptide itself. For each peptide ion the tools uses the scan time prediction derived using the quant based alignment tool to extract a XIC. To refine the derived scan time estimate, we then locally align the extracted XIC to the XIC of the aligned peptide using dynamic time warping. Using this scan time estimate, we use wavelet based peak detection techniques to identify all peaks present in the XIC and select the most probable peak as our target for quantification. Using parameter estimation techniques we subsequently use peak fitting to fit a set of two gaussian models to the detected peak, from whom the one with the better fit is selected. This allows us not only to report how well the signal fitted to the theoretical expected peak shape but also to obtain accurate estimates for the peak area, our estimator for peptide ion abundance.

package proteomiqon-alignmentbasedquantification

versions:

0.0.2-0

depends dotnet-runtime:

5.0.*

depends openssl:

1.1.*

requirements:

additional platforms:

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-alignmentbasedquantification

and update with::

   mamba update proteomiqon-alignmentbasedquantification

To create a new environment, run:

mamba create --name myenvname proteomiqon-alignmentbasedquantification

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-alignmentbasedquantification:<tag>

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

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