How good are those RNA-seq data? [feedly]

[Denis Jacob Machado]

How good are those RNA-seq data?
http://www.rna-seqblog.com/how-good-are-those-rna-seq-data/

 -- via my feedly.com reader

The enormous number of public gene expression data sets can turn into research gold when mined for any number of biological questions. But digging into the data of other researchers is often fraught by a lack of metadata. In particular, missing electrophoresis-based RNA quality scores make it impossible to cull poor-quality samples from analysis or to take computational steps to account for RNA degradation. Because degraded RNA samples, such as those collected from post-mortem tissues, can result in distinct expression profiles with potential biases, a particularly important step in mining these data is quality control.

Now, researchers from Tsinghua and Columbia Universities have developed a method named mRIN to directly assess mRNA integrity from RNA-Seq data at the sample and individual gene level. They systematically analyse large-scale RNA-Seq data sets of the human brain transcriptome generated by different consortia. Their analysis demonstrates that 3′ bias resulting from partial RNA fragmentation in post-mortem tissues has a marked impact on global expression profiles, and that mRIN effectively identifies samples with different levels of mRNA degradation. Unexpectedly, this process has a reproducible and gene-specific component, and transcripts with different stabilities are associated with distinct functions and structural features reminiscent of mRNA decay in living cells.

Feng H, Zhang X, Zhang C. (2015) mRIN for direct assessment of genome-wide and gene-specific mRNA integrity from large-scale RNA-sequencing data. Nat Commun 6:7816.