xomics 0.2.0

Python framework for eXplainable Omics analysis

Welcome to the xOmics documentation

xOmics (eXplainable Omics) is a Python framework developed for streamlined and explainable omics analysis, with a spotlight on differential proteomics expression data. It introduces the following key algorithms:

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

• xOmicsIntegrate: Protein-centric integration of multiple (prote)omic datasets to find commonalities and differences.

• xOmicsRank: Protein-centric ranking of (prote)omic data, leveraging functional enrichment results.

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

Contributing

We appreciate bug reports, feature requests, or updates on documentation and code. For details, please refer to Contributing Guidelines. For further questions or suggestions, please email [e-mail].

Citations

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]

xOmicsIntegrate:

[Citation details and link if available]