Single-Cell RNA Sequencing for Precision Oncology: Current State-of-Art

Abstract

Tumors exhibit genetic and phenotypic diversity leading to intra-tumor heterogeneity (ITH). Further complex ecosystem (stromal and immune cells) of tumors contributes into the ITH. This ITH allows tumors to overcome various selection pressures such as anti-cancer therapies and metastasis at distant organs. Single-cell RNA-seq (scRNA-seq) has provided unprecedented insights into ITH and its implications in drug resistance and metastasis. As scRNA-seq technology grows and provides many new findings, new tools on different programming platforms are frequently generated. Here, we aim to provide a framework and guidelines for new entrants into the field of scRNA-seq. In this review, we discuss the current state-of-art of scRNA-seq analysis step-by-step including filtering, normalization and analysis. First, we discuss the brief history of experimental methods, followed by data processing and implications in precision oncology.