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OmicScope: from quantitative proteomics to systems biology.

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OmicScope: OmicScope: from quantitative proteomics to systems biology.

OmicScope is a comprehensive workflow designed to analyse and provide insights regarding quantitative proteomics data. Todate, OmicScope works with data generated from Progenesis QI for Proteomics, MaxQuant, and PatternLab V. Additionally, a fourth generical input can be used for further analysis, allowing users to run software coming from different plataforms (including transcriptomics and metabolomics).

OmicScope can perform differential expression analysis in both static and longitudinal experimental designs. For static experiments, proteins differentially regulated are determined by t-tests (2 group comparison) or One-way ANOVA (>2 group comparison); while for longitudinal analysis, OmicScope perform the pipeline suggested by Storey, 2005.

Once obtained differential expression data, user can perform Over-Representation Analysis (ORA) or Gene-Set Enrichment Analysis (GSEA), which were implementated according to GSEApy.

Both diferential expression and enrichment analyses have a compreehensive toolset of figures generated by OmicScope, including dotplots, networks, heatmaps, etc.

Finally, for each experiment performed by OmicScope, it is possible to download the an omics file (.omics extension) for further use in Nebula workflow. Nebula is an specialized module that unables analysis of multiple studies or comparions, providing several types of analysis to compare those groups and find similarities among them.

Installation

pip install omicscope

You can also install the in-development version with:

pip install https://github.com/guireiso/omicscope/archive/main.zip

Documentation

https://omicscope.readthedocs.io/

Changelog

1.0.0 (2022-11-10)

  • First release on PyPI.

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omicscope-1.0.5.tar.gz (28.4 MB view hashes)

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