Back to Project List

Tools for Classification and Data Interaction with Labeled RNA-seq Data

Focus Cell Types

Project Goal

To develop novel computational methods and tools for classifying the cell type of cells using RNA-seq data and for human interaction with such data to discover associations between cell type and gene expression features.

Results & Resources

The primary outcome of this project was the publishing of a new machine learning method, CellO, a tool that can be used to predict cell types and perform cellular hierarchical classification from RNA-seq data. This group further developed CellO Viewer, an interactive tool to help users more easily discover associations between cell types of interest.


Lead Investigator

Colin Dewey
Colin Dewey