Tutorial on RNA-seq mapping and data analysis. Seq Data Analysis – Poll Results. Protocol – Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. RNA-Seq Data Analysis – Where To Start? In our last reader poll, we asked: Do we yet have a firm handle on the most appropriate/accurate pipeline for analysis of RNA-Seq datasets? The overwhelming result was: NO. N=72 We’re hearing feedback now from scientists developing data analysis methods for RNA-Seq. Would very much like to hear from more of you. Please send your comments to contribute@rna-seqblog.com. by Dr. Concerning the poll results I perfectly understand the frustration of the researchers. Although RNA-seq seems to be an extremely powerful technique, only now we are getting information on bias and criticality. In my opinion a keyword for pipeline optimization is “benchmark dataset”.
On the basis of previous works, it is evident that we desperately need experimental benchmark datasets to optimize RNA-seq pipelines. Seq Poll Results. HtSeqTools – Quality Control, Visualization and Processing for High-Throughput Sequencing data. HtSeqTools is a Bioconductor package with quality assessment, processing and visualization tools for high-throughput sequencing data, with emphasis in ChIP-seq and RNA-seq studies. It includes detection of outliers and biases, inefficient immuno-precipitation and overamplification artifacts, de novo identification of read-rich genomic regions and visualization of the location and coverage of genomic region lists. Availability: Contact: david.rossell@irbbarcelona.org Planet E, Stephan-Otto Attolini C, Reina O, Flores O, Rossell D. (2011) htSeqTools: High-Throughput Sequencing Quality Control, Processing and Visualization in R. Bioinformatics [Epub ahead of print].
RNA-Seq Data Analysis Online Course. Open Source RNA-Seq Data Analysis Tools from Google Project Hosting. Advanced RNA-Seq and ChiP-Seq Data Analysis.
Databases. Torrents. Portals.