Statistical and Bioinformatics Analysis of Data from Bulk and Single-Cell RNA Sequencing Experiments

Methods Mol Biol. 2021;2194:143-175. doi: 10.1007/978-1-0716-0849-4_9.

Abstract

High-throughput sequencing (HTS) has revolutionized researchers' ability to study the human transcriptome, particularly as it relates to cancer. Recently, HTS technology has advanced to the point where now one is able to sequence individual cells (i.e., "single-cell sequencing"). Prior to single-cell sequencing technology, HTS would be completed on RNA extracted from a tissue sample consisting of multiple cell types (i.e., "bulk sequencing"). In this chapter, we review the various bioinformatics and statistical methods used in the processing, quality control, and analysis of bulk and single-cell RNA sequencing methods. Additionally, we discuss how these methods are also being used to study tumor heterogeneity.

Keywords: Differential expression; High-throughput sequencing; Normalization; Quality control; Single-cell; Transcriptomics; Tumor heterogeneity.

Publication types

  • Review

MeSH terms

  • Computational Biology / methods*
  • Data Interpretation, Statistical
  • Databases, Genetic
  • Gene Expression Profiling
  • Humans
  • Neoplasms / genetics*
  • Quality Control
  • Sequence Analysis, RNA / methods*
  • Single-Cell Analysis / methods*
  • Skin Neoplasms / genetics