Speaker：Professor Chien-Wei (Masaki) Lin (Medical College of Wisconsin)
Topic：FastQDesign: A realistic FASTQ-based framework for ScRNA-seq study design issues
Speaker：Professor Chien-Wei (Masaki) Lin
(Medical College of Wisconsin)
Date Time：Fri. Dec 20, 2024, 11:10-12:00
Place： 4F-427, Assembly Building I
Online Seminars- Google Meet
Abstract
Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful technology for characterizing transcriptomic profiles at single-cell resolution. When planning such experiments, it is crucial to consider both the number of cells and sequencing depth. While existing literature addresses this need, they are primarily simulation-based methods and rely on Unique Molecular Identifier (UMI) matrix, which has critical limitations such as ignoring the actual number of reads provided by raw FastQ files, Here we propose the first FastQ-based study design framework for scRNA-seq data, named "FastQDesign," which leverages raw FastQ files from publicly available scRNA-seq datasets as references and suggests an optimal design within a fixed budget. We demonstrate the feasibility of this framework through a synthetic dataset in simulations and applications to nine real-world datasets. Our study highlights the necessity of an appropriate design to study the biology underlying heterogeneous cell populations and provides practical guidance while considering the cost-benefit balance. A high-efficiency software suite, written in C and R languages, is available at https://github.com/yuw444/FastQDesign.