- 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:
- Documentation:
https://csbiology.github.io/ProteomIQon/tools/AlignmentBasedQuantification.html
- Developer docs:
- License:
MIT
- Recipe:
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:
on dotnet-runtime
5.0.*on openssl
1.1.*
- 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 proteomiqon-alignmentbasedquantification
to add into an existing workspace instead, run:
pixi add proteomiqon-alignmentbasedquantification
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 proteomiqon-alignmentbasedquantification
Alternatively, to install into a new environment, run:
conda create -n envname proteomiqon-alignmentbasedquantification
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/proteomiqon-alignmentbasedquantification:<tag>
(see proteomiqon-alignmentbasedquantification/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.
Download stats¶
Link to this page¶
Render an 
badge with the following MarkDown:
[](http://bioconda.github.io/recipes/proteomiqon-alignmentbasedquantification/README.html)
