Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Wertheim cung cấp cho các bạn kiến thức về ngành y đề tài: Cloud-scale RNA-sequencing differential expression analysis with Myrna. | Langmead et al. Genome Biology 2010 11 R83 http content 11 8 R83 Genome Biology SOFTWARE Open Access Cloud-scale RNA-sequencing differential expression analysis with Myrna Ben Langmead Kasper D Hansen Jeffrey T Leek Abstract As sequencing throughput approaches dozens of gigabases per day there is a growing need for efficient software for analysis of transcriptome sequencing RNA-Seq data. Myrna is a cloud-computing pipeline for calculating differential gene expression in large RNA-Seq datasets. We apply Myrna to the analysis of publicly available data sets and assess the goodness of fit of standard statistical models. Myrna is available from http myrna. Rationale As cost and throughput continue to improve second generation sequencing 1 in conjunction with RNA-Seq 2 3 is becoming an increasingly efficient and popular tool for studying gene expression. Currently an RNA-Seq sequencing run generates hundreds of millions of reads derived from coding mRNA molecules in one or more biological samples. A typical RNA-Seq differential-expression analysis proceeds in three stages. First reads are computationally categorized according to the transcribed feature from which each likely originated. Features of interest could be genes exons or isoforms. This categorization might be conducted comparatively with respect to a reference 4 by de novo assembly 5 or a combination of both 6-8 . Second a normalized count of the number of reads assigned to each feature is calculated. The count acts as a proxy for the feature s true abundance in the sample. Third a statistical test is applied to identify which features exhibit differential abundance or expression between samples. Since second generation sequencing produces a very large number of reads distributed across the entire transcriptome RNA-Seq affords greater resolution than expression arrays. Preliminary comparisons of the data from RNA-Seq also suggest that the measurements may more precisely .
