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We are are legion.

Detection of differential splicing in cancer using gene expression arrays is the 1000^th poster to be published at our open poster repository, https://posters.f1000.com/. Gene expression arrays have been a workhorse of biology for a number of years now, and there are vast sets of data. What happens when the same genes, subject to multiple probesets, give different answers?

Some say this may be indicative of alternative splicing, and many researchers simply take an average of the different values. (Some of us, especially those working on exon arrays, are more likely to swear softly and cry into our beers.) Fong Chun Chan, a Masters student with Randy Gascoyne at the BC Cancer Agency, Vancouver, has come up with an algorithm that can check discordant data for the likelihood of alternative splicing.

What’s the point of this? Fong Chun says, “The general feeling is that sequencing data is the future and that arrays are a thing of the past,” but with half a million samples in the Gene Expression Omnibus that’s a lot of data to ignore. Fong Chun hopes to create a cross-platform alternative splicing metric applicable to any platform that collects exon-level expression levels, and reckons arrays are still a valuable source of information that can “be used for detecting differential isoform expression between two groups of samples.”

Fong Chun Chan is funded by the CIHR/MSFHR Strategic Training Program in Bioinformatics.