Is it possible to compare RPKM values across studies? This question is something I have been thinking about during my own analyses. I tend to think that under the conditions of standard poly-A enrichment and approximately equal coverage during sequencing runs, then RPKM values for genes between separate studies can be compared. However, if study X used a transcript enrichment setup in which a select number of mRNAs from a subset of genes were being selected for sequencing, can the RPKM values obtained from this study be reliably compared to study Y in which poly-A enrichment was used?
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Part II for those who are feeling ambitious: If I were to selectively enrich for a set of transcripts (A,B,C), sequence these, and obtain high RPKM measurements and attempt to compare these to a poly-A enriched sample set in which I have a fair expression measurement of most of the transcriptome (although in this case transcripts A, B, and C were unaccounted for due to low abundance) is it possible to extrapolate the normal physiological mRNA abundance of these transcripts from the enriched data series?
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Researchers using sequencing and genomics tools often have to make trade-offs. They can choose between speed or scale, short reads or long-range information, or targeted panels or a view of the whole transcriptome. New technologies that have been released this year are built to address those tough choices.
We asked six companies the same four questions to learn about their latest products. The new technologies bring a lot to the table, including rethinking sequencing...
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