Statistical Methods and Software for 10x Genomics Data

Single-cell RNA-sequencing (scRNA-seq) has emerged as a revolutionary tool that allows investigators to address scientific questions that were elusive just a few years ago and, as a result, scRNA-seq experiments are now commonly used in thousands of labs across the country. Recognizing the potential of this technology, many UW-Madison labs worked with the UW Biotechnology Center to acquire a 10x genomics machine to facilitate single-cell RNA-seq here on campus.

Unfortunately, the ability to derive useful information from 10x data is very limited due to a lack of statistical and computational methods. This project addresses some of the most critical statistical deficiencies that are currently preventing the scientific community here at UW and beyond from turning valuable 10x scRNA-sequencing measurements into meaningful results

This project will lead to development of statistical methods and a software pipeline to ensure that powerful and efficient tools are available to researchers measuring gene expression in single cells.

 

PRINCIPAL INVESTIGATOR:

Christina Kendziorski, Professor of Biostatistics and Medical Informatics

 

CO-INVESTIGATORS:

Sunduz Keles, Professor of Biostatistics and Medical Informatics

Michael Newton, Professor of Biostatics and Medical Informatics