Significance of single-cell analysis

The ability to identify and characterize functional subpopulations of cells is increasingly seen as essential for understanding the mechanisms of diseases and developing effective therapeutics. In cancer research, it is widely recognized that most tumors are a mixture of multiple clones in constant competition for growth advantage, and effective treatment must take into account the subpopulation structure of the tumor cells. In many genetic diseases, it is increasingly evident that the malfunction of a very minor subpopulation of cells leads to the pathogenic phenotype. The Multiome technique and the data analysis methods described here, as well as refined experimental cloning techniques that enable the identification and characterization of functional subpopulations of cells within a tissue, could lead to significant advances in our understanding and treatment of these diseases in the coming decade.

- Intro to scRNA-seq, scATAC-seq and Multiome
- Steps to take to analyze scRNA-seq, scATAC-seq and Multiome data
- Significance of single-cell analysis
-- About the author

About the Author: Justin T. Li received his Ph.D. in Neurobiology from the University of Wisconsin-Madison in 2000 and a M.S. in Computer Science from the University of Houston in 2001. Between 2004 and 2009, he served as an Assistant Professor in the Medical School at the University of Minnesota Twin Cities campus. From 2009 to 2013, he was the Chief Bioinformatics Officer at LC Sciences in Houston. In June 2013, Justin joined AccuraScience as a Lead Bioinformatician. He has published over 40 research articles in bioinformatics, computational biology, and related fields. More information about Justin can be found at https://www.accurascience.com/our_team.html.

Need assistance in your scRNA-seq, scATAC-seq or Multiome data analysis project? We may be able to help. Take a look at the intro to our bioinformatician team, see some of the advantages of using our team's help here, and check out our FAQ page!