Category Archives: RNA-seq
CGS: Spike-In Cooperative
July 10, 2015
The S.I.C. is a group of like-minded investigators who sometimes need to borrow a little bit of sequencing, and who are sometimes willing to lend a little sequencing. The S.I.C. is made possible by the Center for Genome Sciences & Systems Biology.
The short version:
- Make a library using unique 9bp indexes assigned to your lab.
- Submit the library to Jess at the CGS&SB to spike-into a MiSeq 2×250 sequencing run.
- You will receive demultiplexed fastq files of your spike-in sample.
- Cost? $150, for about 500,000 reads.
Details could be found:https://genomesciences.wustl.edu/sic
Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data
April 21, 2015
Abstract
A large number of computational methods have been developed for analyzing differential gene expression in RNA-seq data. We describe a comprehensive evaluation of common methods using the SEQC benchmark dataset and ENCODE data. We consider a number of key features, including normalization, accuracy of differential expression detection and differential expression analysis when one condition has no detectable expression. We find significant differences among the methods, but note that array-based methods adapted to RNA-seq data perform comparably to methods designed for RNA-seq. Our results demonstrate that increasing the number of replicate samples significantly improves detection power over increased sequencing depth.
http://genomebiology.com/2013/14/9/r95
Comparison of signal-to-noise ratio and differential expression (DE) for genes expressed in only one condition.