DIGGIT identify genetic variants associated with drivers of specific physiopathologic states. I computes the statistical association between the presence of genetic variants (CNV or SNP) and the activity of proteins driving physiologic or pathologic phenotype. It requires large gene expression and genetic variants datasets and depends on context-specific regulatory networks including transcriptional interactomes (usually reverse engineered by the ARACNe algorithm) and post-translational interactomes (usually generated by the MINDy algorithm). Regulatory protein activity is inferred by the VIPER algorithm (available as an R package from bioconductor).

Project Activity

See All Activity >

Follow diggit

diggit Web Site

You Might Also Like
Red Hat Enterprise Linux on Microsoft Azure Icon
Red Hat Enterprise Linux on Microsoft Azure

Deploy Red Hat Enterprise Linux on Microsoft Azure for a secure, reliable, and scalable cloud environment, fully integrated with Microsoft services.

Red Hat Enterprise Linux (RHEL) on Microsoft Azure provides a secure, reliable, and flexible foundation for your cloud infrastructure. Red Hat Enterprise Linux on Microsoft Azure is ideal for enterprises seeking to enhance their cloud environment with seamless integration, consistent performance, and comprehensive support.
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of diggit!

Additional Project Details

Registered

2014-08-22