xcore

xcore models transcription factor activity using known molecular signatures and user gene expression data.

Key Features:

• Ridge regression modeling: xcore models changes in expression as a linear combination of molecular signatures to find unknown transcription factor activities.
• Significance testing: Obtained estimates can be tested for significance to select molecular signatures with the highest predicted effect on observed expression changes.
• Molecular signature collection: The accompanying xcoredata package provides molecular signatures constructed from publicly available ChiP-seq experiments.

Scientific Applications:

• Transcription factor activity inference: xcore enables inference of transcription factor activities from gene expression data using known molecular signatures.
• Gene expression analysis: xcore identifies molecular signatures with the highest predicted effect on observed expression changes through significance testing of model estimates.

Methodology:

xcore uses ridge regression to model changes in expression as a linear combination of molecular signatures and find their unknown activities.