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 Li earned his Ph.D. in Neurobiology from the University of Wisconsin–Madison and an M.S. in Computer Science from the University of Houston, following a B.S. in Biophysics. He served as an Assistant Professor at the University of Minnesota Medical School (2004–2009) and as Chief Bioinformatics Officer at LC Sciences (2009–2013) before joining AccuraScience as Lead Bioinformatician in 2013. Justin has published around 50 research papers and led the development of 12 bioinformatics databases and tools - including miRecords, siRecords, and PepCyber - while securing over $3.4M in research funding between 2004 and 2009 as PI, co-PI, or co-I. He has worked on NGS data analysis since 2007, with broad expertise in genome assembly, RNA-seq, scRNA-seq, scATAC-seq, Multiome, ChIP-seq and epigenomics, metagenomics, and long-read technologies. His recent work includes machine learning applications in genomics, AlphaFold modeling, structural bioinformatics, immune repertoire analysis, and multi-omics integration.

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!

Send us an inquiry, chat with us online (during our business hours 9-5 Mon-Fri U.S. Central Time), or reach us in other ways!