Tuning parameters of dimensionality reduction methods for single-cell RNA-seq analysis

摘要

Single-cell RNA sequencing (scRNA-seq) is a powerful technology to characterize the transcriptomic profile of individual cells within a population [1]. By allowing researchers to identify cell types based on their transcriptomic signatures instead of pre-defined markers, it is rapidly establishing itself as a standard tool to answer a variety of biological questions, ranging from characterizing the heterogeneity of complex tissues [2, 3] to discovering new cell types [4] or elucidating cell differentiation processes [5].