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Computational methods for transcriptome annotation and quantification using RNA-seq

Garber, Manuel and Grabherr, Manfred G. and Guttman, Mitchell and Trapnell, Cole (2011) Computational methods for transcriptome annotation and quantification using RNA-seq. Nature Methods, 8 (6). pp. 469-477. ISSN 1548-7091.

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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.

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Guttman, Mitchell0000-0003-4748-9352
Additional Information:© 2011 Macmillan Publishers Limited. Published online 27 May 2011; Corrected online 15 June 2011. We thank L. Gaffney for help with figures; B. Haas for making available scripts to run transAbyss and for many discussions; Y. Katz, C. Nusbaum, A. Pauli and M. Zody for helpful discussions and comments on the manuscript; and J. Alfoldi, C. Burge, M. Cabili, K. Lindblad-Toh, J. Rinn, L. Pachter, S. Salzberg and O. Zuk for helpful comments on the manuscript. The authors declare no competing financial interests.
Errata:Corrected online 15 June 2011 In the html version of this article initially published, the corresponding author was listed as Manfred G. Grabherr instead of Manuel Garber. The error has been corrected in the HTML version of the article.
Subject Keywords:RNA sequencing; Sequence annotation; Transcriptomics
Issue or Number:6
Record Number:CaltechAUTHORS:20161122-084822107
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:72239
Deposited By: Tony Diaz
Deposited On:22 Nov 2016 18:27
Last Modified:03 Oct 2019 16:15

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