%0 Journal Article
%T ReCount: A multi-experiment resource of analysis-ready RNA-seq gene count datasets
%A Alyssa C Frazee
%A Ben Langmead
%A Jeffrey T Leek
%J BMC Bioinformatics
%D 2011
%I BioMed Central
%R 10.1186/1471-2105-12-449
%X ReCount is an online resource of RNA-seq gene count tables and auxilliary data. Tables were built from raw RNA sequencing data from 18 different published studies comprising 475 samples and over 8 billion reads. Using the Myrna package, reads were aligned, overlapped with gene models and tabulated into gene-by-sample count tables that are ready for statistical analysis. Count tables and phenotype data were combined into Bioconductor ExpressionSet objects for ease of analysis. ReCount also contains the Myrna manifest files and R source code used to process the samples, allowing statistical and computational scientists to consider alternative parameter values.By combining datasets from many studies and providing data that has already been processed from. fastq format into ready-to-use. RData and. txt files, ReCount facilitates analysis and methods development for RNA-seq count data. We anticipate that ReCount will also be useful for investigators who wish to consider cross-study comparisons and alternative normalization strategies for RNA-seq.RNA-seq, or short-read sequencing of mRNA, has emerged as a powerful and flexible tool for studying gene expression [1]. As with other new technologies, the analysis of RNA-seq data requires the development of new statistical methods. Data from many RNA-seq experiments are publicly available, but processing raw data into a form suitable for statistical analysis remains challenging [2]. This difficulty together with the high cost of using second-generation sequencing technology means that most computational scientists have only a limited number of samples to work with [3]. However, replication is critical to understanding biological variation in RNA-sequencing [4].The Gene Expression Omnibus [5] is a useful repository that contains both processed and raw microarray data, but there is no comparable resource for processed RNA-seq data. We have compiled a resource, called ReCount, consisting of aligned, preprocessed RNA-seq data from
%U http://www.biomedcentral.com/1471-2105/12/449