CACO-2
Experimental Design and Analytical Strategies for RNA-Seq experiments
Background  Whole transcriptome sequencing using massively parallel sequencing technology (RNA-Seq) is a novel and powerful method to comprehensively investigate gene expression levels and splicing patterns. While many studies have been successfully conducted using this technology, the influence of many experimental and analytical parameters on the robustness of the findings remains poorly defined.   Methodology and Principal Findings  Here we use extensive in silico analyses to comprehensively characterize the influence of the experimental design on the inferences of the transcript structures and quantification. We simulate RNA-Seq data under a wide range of experimental designs and show that the length of the sequence reads and the usage of paired end reads greatly influence the sensitivity and specificity of the RNA-Seq results, especially with regards to the reconstruction of splice isoforms. We then use data generated from Caco-2 cells to show that, using stringent quality filters, one lane of RNA-Seq data is sufficient to provide a robust description of the transcriptome, an extensive catalogue of coding polymorphisms as well a digital karyotype of the cells highlighting heterozygous deletions of large chromosomal regions.  Conclusions  We conclude that stringent filters are necessary to limit spurious findings from RNA-Seq experiments and that by combining long reads with paired end sequences, a tremendous amount of genetic information can be extracted from a single lane of RNA-Seq experiment.