Design and validation issues in RNA-seq experiments
Zhide Fang obtained his PhD in Statistics in 1999. He is currently an Associate Professor in Biostatistics Program, School of Public Health, at Louisiana State University Health Sciences Center at New Orleans.
Xiangqin Cui obtained her PhD in Genetics in 2001 and did her postdoctoral training in Statistical Genetics from 2001 to 2004. She is currently an assistant professor in Department of Biostatistics, Section on Statistical Genetics, at the University of Alabama at Birmingham.
Corresponding author. Xiangqin Cui, Assistant Professor, Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, 327 Ryals Public Health Building, 1665 University BLVD, Birmingham, AL 35294, USA. Tel: +1-205-996-4154; Fax: +1-205-975-2540; E-mail: email@example.com
Received August 30, 2010.
Revision received February 2, 2011.
The next-generation sequencing technologies are being rapidly applied in biological research. Tens of millions of short sequences generated in a single experiment provide us enormous information on genome composition, genetic variants, gene expression levels and protein binding sites depending on the applications. Various methods are being developed for analyzing the data generated by these technologies. However, the relevant experimental design issues have rarely been discussed. In this review, we use RNA-seq as an example to bring this topic into focus and to discuss experimental design and validation issues pertaining to next-generation sequencing in the quantification of transcripts.