Developing Single-Cell Interactomes to Identify Molecular Determinants of Single-Cell State

To assemble context-specific gene regulatory networks for the systematic reconstruction of single-cell states and their molecular determinants.

The Califano lab developed a new algorithm, Protein activity Inference in Single-Cells (PISCES), which transforms highly variable and noisy single-cell gene expression profiles into robust and reproducible protein activity profiles. Analysis of T-cell data, from five tissues across four donors, revealed tissue-specific patterns of T-cell activation that is more detectable via protein activity based analysis, as gene expression data is too sparse to generate a robust signature.