Total-mRNA-Aware Analysis for Droplet-Based Single Cell Sequencing

Date: 2022/12/02 - 2022/12/02

Academic Seminar: Total-mRNA-Aware Analysis for Droplet-Based Single Cell Sequencing

Speaker: Dr. Qiuyu Lian, Postdoctoral Researcher, University of Michigan-Shanghai Jiao Tong University Joint Institute

Time: 10:00 - 10:30, December 2, 2022 (Beijing Time)

Abstract

Controlling total mRNA content differences between cell populations is critical in comparative transcriptomic measurements. Due to poor compatibility with ERCC, a good control for droplet-based scRNA-seq is yet to be discovered. Normalizing cells to a common count distribution has been adopted as a silent compromise. Such practice profoundly confounds downstream analysis and mislead discoveries. We present TOMAS, a computational framework that derives total mRNA content ratios between cell populations via deconvoluting their heterotypic doublets. Experiments showed that cell types can have total mRNA differences by many folds and TOMAS can accurately infer the ratios between them. We demonstrate that TOMAS corrects bias in downstream analysis and rectifies a plethora of previously counter-intuitive or inconclusive analytical results. We argue against the opinion that doublets are undesired scale-limiting factors and revealed the unique value of doublets as controls in scRNA-seq. We advocate for their essential role in future large-scale scRNA-seq experiments.

Biography

Dr. Qiuyu Lian is currently a postdoc at UM-SJTU Joint Institute, Shanghai Jiao Tong University. She received her Ph.D. degree in Control Science and Engineering from Tsinghua University in 2020 and served as a Visiting Scholar in University of Pittsburgh in 2019. Prior to that, she received her B.E. degree in Electronic Information and Engineering from Sichuan University in 2015. Her research interests include  data mining of cancer omics,  precision medicine, single cell multi-omics, explainable models in biomedical data.