Genome Biologyrecently published an article fromAlicia Oshlackand colleagues in which they describean approach for performing Gene Ontology analysison RNA-seq data. RNA-seq is an emerging technology for monitoring gene expression levels by directly sequencing the mRNA molecules in a sample, and is likely to overtake microarrays as the technique of choice for gene expression profiling. Now,Genome Biologyhas published another innovative method, this time fornormalizing RNA-seq data。这个方法是急需的,会拥抱by the genomics community as, until now, methods for normalizing RNA-seq data have often relied on tools that were based on those developed for microarray data.

A common approach for normalizing RNA-seq data has been to consider the expression of an individual gene relative to the global gene expression levels. In her latest paper, Oshlack, at theWalter and Eliza Hall Institutein Melbourne, Australia, shows that this is not always appropriate. In particular, if one tissue has a small number of genes that are significantly differentially expressed compared with another tissue then these can affect whether or not other genes in the sample are determined as being differentially expressed, often leading to implausible results. The paper demonstrates again the need for new statistical techniques to fully exploit the powerful RNA-seq technology, as well as providing a useful tool for doing this.

• About
• Latest Posts

Andrew Cosgrove

Andrew obtained his PhD in molecular biology from the University of Dundee in 2005. He joined Genome Biology in 2009 after a post doctoral research position at the University of Sheffield investigating chromosome positioning during meiosis in yeast.

Latest posts by Andrew Cosgrove(see all)

• Exploring the history of smallpox vaccination with 19th Century American vaccination kits- 16th November 2020
• The fascination of plant genomes- 20th May 2019
• Genome Biology at Genome Informatics- 18th February 2019