Welcome to the xOmics documentation!

xOmics (eXplainable Omics) is a Python framework developed for interpretable omics analysis, focusing on differential proteomics expression data. It introduces the following key algorithms:

• cImpute: Conditional Imputation - A transparent method for hybrid missing value imputation.

• pRank: Protein-centric ranking of (prote)omic data, including integration with functional enrichment results.

• pIntegrate: Protein-centric integration of multiple (prote)omic datasets for differential analysis.

• QARIP: Quantitative proteomic analysis of regulated intramembrane proteolysis.

In addition, xOmics provides functional capabilities for efficiently loading benchmark proteomics datasets via load_datasets, accompanied by corresponding enrichment data.A suite of supportive functions is also available to facilitate a smooth and efficient (prote)omic analysis pipeline.

Install

xOmics can be installed either from PyPi or conda-forge:

pip install -u xomics
or
conda install -c conda-forge xomics

OVERVIEW

• Introduction
• Usage Principles
• Contributing

EXAMPLES

• Tutorials

REFERENCES

• API
  • Data Handling
  • Imputation
  • Ranking
  • Integration
  • Mapping
  • Plotting
  • Plot Utilities

• Tables
• References

Indices and tables

• Index

• Module Index

• Search Page

Citation

If you use ‘xOmics’ in your work, please cite the respective publication as follows:

xOmics:

[Citation details and link if available]

cImpute:

[Citation details and link if available]

pRank:

[Citation details and link if available]

pIntegrate:

[Citation details and link if available]

QARIP:

QARIP: a web server for quantitative proteomic analysis of regulated intramembrane proteolysis Nucleic Acids Research.