Computational methods for transcriptome annotation and quantification using RNA-seq

Nat Methods. 2011 Jun;8(6):469-77. doi: 10.1038/nmeth.1613. Epub 2011 May 27.


High-throughput RNA sequencing (RNA-seq) promises a comprehensive picture of the transcriptome, allowing for the complete annotation and quantification of all genes and their isoforms across samples. Realizing this promise requires increasingly complex computational methods. These computational challenges fall into three main categories: (i) read mapping, (ii) transcriptome reconstruction and (iii) expression quantification. Here we explain the major conceptual and practical challenges, and the general classes of solutions for each category. Finally, we highlight the interdependence between these categories and discuss the benefits for different biological applications.

Publication types

  • Review

MeSH terms

  • Animals
  • Computational Biology / methods
  • Gene Expression Profiling / statistics & numerical data*
  • Genomics / statistics & numerical data
  • High-Throughput Nucleotide Sequencing / statistics & numerical data*
  • Humans
  • Sequence Alignment / statistics & numerical data
  • Sequence Analysis, RNA / statistics & numerical data*