This chapter will review the statistical methods used in RNA sequenc- ing data analysis, including bulk RNA sequencing and single-cell RNA sequenc- ing. RNA sequencing data analysis has been widely used in biomedical and biological research to identify genes associated with certain conditions or diseases. Many statistical methods have been proposed to analyze bulk and single-cell RNA sequencing data. Several studies have compared the performance of different sta- tistical methods for RNA sequencing data analysis through simulation studies and real data evaluations. This chapter will summarize the statistical methods and the evaluation results for comparing different statistical analysis methods used for RNA sequencing data analysis. It will cover the statistical models, model assump- tions, and challenges encountered in the RNA sequencing data analysis. It is hoped that this chapter will help researchers learn more about the statistical per- spective of the RNA sequencing data analysis and enable them to choose appro- priate statistical analysis methods for their own RNA sequencing data analysis.
CITATION STYLE
Li, D. (2019). Statistical Methods for RNA Sequencing Data Analysis. In Computational Biology (pp. 85–99). Codon Publications. https://doi.org/10.15586/computationalbiology.2019.ch6
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