Extensions and updates to the BioPlex R and Python packages

1.1 Background

The BioPlex project led by Dr. Huttlin has created two proteome-scale, cell-line-specific protein-protein interaction (PPI) networks: the first in 293T cells, including 120k interactions among 15k proteins; and the second in HCT116 cells, including 70k interactions between 10k proteins. These networks model the interactome whose structure encodes protein function, localization, and complex membership, and together these networks define principles of proteome organization and enable unknown protein characterization. In a recent significant expansion of the BioPlex project, Dr. Huttlin and his team have generated PPI networks for three additional cell lines (RPE1, HeLa, and U2OS). In addition, the five cell lines have also been subjected to (1) protein expression profiling via Tandem Mass Tags (TMT) proteomics, and (2) profiling of post-translational modifications (PTM) including phosphorylation, acetylation, and ubiquitylation.

1.2 Scope of Work

In a previous project, CCB has developed software packages that facilitate working with the BioPlex PPI networks in R and Python. In this project, CCB will work on extending and updating both packages to provide access to the newly generated PPI, TMT, and PTM datasets. Besides providing efficient access to the newly generated datasets, this also includes the implementation of functionality for the integrative analysis of PPI, TMT, and PTM data such as PTM site enrichment testing within protein sets and integration with public PTM databases.