sc2DAT

sc2DAT predicts cell surface targets and therapeutic compounds tailored to target-specific cell types automatically identified from scRNA-seq and bulk RNA-seq datasets.

Key Features:

• Cell Type Identification: sc2DAT identifies cell types from uploaded RNA-seq data.
• Cell-Surface Target Discovery: sc2DAT discovers cell-surface targets specific to identified cell types.
• Therapeutic Compound Prediction: sc2DAT finds therapeutic compounds specific to cell types, outputting ranked drugs and targets.
• Gene Expression Signature Analysis: sc2DAT uses compounds from the LINCS L1000 dataset that are hypothesized to either reverse or mimic the direction of changes in gene expression signatures.

Scientific Applications:

• Cancer Malignant Subpopulation Targeting: sc2DAT develops hypotheses about selectively eliminating malignant subpopulations of cells in cancer.
• Disease Tissue Reprogramming: sc2DAT develops hypotheses about reprogramming disease tissues toward a healthier phenotype by restoring subpopulations of cells towards a healthier phenotype.

Methodology:

sc2DAT automatically identifies cell types from scRNA-seq and bulk RNA-seq datasets, then predicts cell surface targets and therapeutic compounds tailored to those cell types using the LINCS L1000 dataset.