The Impact of Heterogeneity on Single-Cell Sequencing

Frontiers in Genetics

Ari M. Melnick¹  Shuxiu Wu³  Christopher E. Mason⁵  Samantha L. Goldman⁶  Matthew MacKay⁶  Ebrahim Afshinnekoo⁷ 

[1] Department of Medicine, Weill Cornell Medicine, New York, NY, United States;Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY, United States;Department of Radiation Oncology, Hangzhou Cancer Hospital, Hangzhou, China;Hangzhou Cancer Institute, Hangzhou Cancer Hospital, Hangzhou, China;The Feil Family Brain and Mind Research Institute, New York, NY, United States;The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, United States;WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, United States;

关键词: single-cell sequencing;    heterogeneity;    scRNA-seq;    NGS;    RNA;    single cells;   

DOI  :  10.3389/fgene.2019.00008

来源: DOAJ

【 摘 要 】

The importance of diversity and cellular specialization is clear for many reasons, from population-level diversification, to improved resiliency to unforeseen stresses, to unique functions within metazoan organisms during development and differentiation. However, the level of cellular heterogeneity is just now becoming clear through the integration of genome-wide analyses and more cost effective Next Generation Sequencing (NGS). With easy access to single-cell NGS (scNGS), new opportunities exist to examine different levels of gene expression and somatic mutational heterogeneity, but these assays can generate yottabyte scale data. Here, we model the importance of heterogeneity for large-scale analysis of scNGS data, with a focus on the utilization in oncology and other diseases, providing a guide to aid in sample size and experimental design.

【 授权许可】

Unknown