Question: Exon Arrays Vs Rna-Seq
gravatar for Travis
7.5 years ago by
Travis2.8k wrote:

Hi all,

I am wondering if anyone has experience (or has read something relevant) in the area of comparing the pros and cons of RNA-Seq vs Exon arrays.

As a starter, RNA-Seq enables a hypothesis neutral approach whilst exon arrays are more mature/validated etc.

Further thoughts would be appreciated.

next-gen rna exon sequencing • 5.2k views
ADD COMMENTlink written 7.5 years ago by Travis2.8k
gravatar for Neilfws
7.5 years ago by
Sydney, Australia
Neilfws48k wrote:

Quite a few articles have appeared recently on this topic.

They state that RNA-Seq has quite a high error rate for genes with low expression levels.

Just to add more complexity, they employ proteomics as a third measure and state that RNA-Seq agrees better with protein levels.

They suggest that compared with RNA-Seq, exon arrays have a systematic error which leads to over-estimation of alternative transcripts.

Poster from Applied Biosystems: concludes that both approaches are useful and complementary.

ADD COMMENTlink written 7.5 years ago by Neilfws48k

Each have pros and cons for sure. If AB can't even manage to slate exon arrays then they must be ok :)

ADD REPLYlink written 7.5 years ago by Travis2.8k
gravatar for brentp
7.5 years ago by
Salt Lake City, UT
brentp22k wrote:

Have a look at this recent paper Human transcriptome array for high-throughput clinical studies

It gives a favorable view of the 6.9 million feature chip and weighs the pros and cons.

ADD COMMENTlink written 7.5 years ago by brentp22k
gravatar for Malachi Griffith
7.1 years ago by
Washington University School of Medicine, St. Louis, USA
Malachi Griffith17k wrote:

This thread describes the: Expected correlation between Exon Array and RNA-Seq.

The paper Alternative expression analysis by RNA sequencing contains a variety of comparisons between Affymetrix Exon arrays, custom NimbleGen arrays, and RNA-seq. The paper RNA-seq: An assessment of technical reproducibility and comparison with gene expression arrays also seems relevant.

As someone who has worked with both microarrays (including custom designed arrays), and RNA-seq I think you hit the nail on the head with your comment about the hypothesis neutral approach of RNA-seq. IMHO, being locked to extant information at design time is a significant limitation of microarrays (one that is impractical to overcome).

Other pros of RNA-seq over microarrays include: theoretically unlimited dynamic range and better signal-to-noise ratio. Probably the clincher though is the diversity of information your can simultaneously obtain (with appropriate analyses of course): gene expression, alternative isoform detection and quantification, mutation detection, allele specific expression, gene fusion discovery and quantification, RNA editing, etc.

One pro of microarrays is that they have arguably more robust strand specific assays currently. Another is that they are less influenced by a wide expression distribution/range (the difference in copy number between the lowest and highest expressed transcripts in the cell). This is both the blessing and the curse of the finite dynamic range in microarrays. In RNA-seq, the random sampling nature of the assay means that you can burn a large percentage of your data sequencing the top N% of expressed genes. I have seen libraries where >75% of sequenced reads corresponded to the top 5 genes. Microarrays do not suffer from this phenomenon, although you can improve signal by enriching for polyA+ RNA or otherwise removing rRNA species.

ADD COMMENTlink written 7.1 years ago by Malachi Griffith17k
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