Revive old microarray data linking it to new gene annotations
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3.5 years ago
lessismore ★ 1.3k

Dear all, i'm dealing with a plant species with old microarray experiments from before 2010. As i want to integrate this data with new data corresponding to annotations from its brand new genome, what do you recommend to do? A simple best-blast-hit against the new transcript file would do the job? Is there maybe a (plant) database with the goal of linking this old data to new generated annotations ? Thanks in advance

microarray annotations integration • 862 views
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never done this myself (== creating or updating those CDF files) but I remember someone from my lab has done it like a decade ago and if I recall correctly she spend a considerable amount of time on it (talking months here) and unfortunately a simple blast did not cut it (you for instance have to take probe combinations into account etc).

I'll see if I can dig up some more info on what she exactly did.

what kind of microarray are we talking here btw?

EDIT: Not 100% sure but I think in this paper (or at least starting from this one) you can find some methods on how it was done: Casneuf T, Van de Peer Y, Huber W (2007) In situ analysis of cross-hybridisation on microarrays and the inference of expression correlation. BMC Bioinformatics 8: 461.

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Thank you, lll have a look at this. I was referring to GeneChip/DNA Chip

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The Ensembl annotation pipeline also maps microarray probes. Check first if your array and species are available in Ensembl plant. The Ensembl microarray probe mapping page describes the workflow they use for this.

The paper Probe mapping across multiple microarray platforms may also be of interest. From the abstract:

Based on the evaluation from the empirical data set, the BLAST alignment of the probe sequences to a recent revision of the Transcriptome generated better results than using annotations provided by Vendors or from Bioconductor's Annotate package. However, a combination of all three methods (deemed the ‘Consensus Annotation’) yielded the most consistent expression measurement across platforms.

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Thanks, this is actually super useful.

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