How To Find The Microarray Experiment With The Most Similar Expression Profile To My Experiment?

Question

[Betatubulin]

I have an RNA-Seq experiement for a mouse single gene knock down. There are about 2K genes that are significantly up/down regulated compared to controls. Because we are not sure what the gene does I would like to know what exisiting microarray experiments the expression profile is most similar to. Is there an efficient way to search my expression profile against ArrayExpress or another database? It is really just a question of running lots of correlations but I'd rather not have to pull down every dataset myself.

Any thoughts appreciated.

Thanks!

Answer 1

[User 59]

Most approaches for this have been list vs list comparisons between experiments that I've seen (see a previous answer here regarding L2L and LOLA). However you might be interested in this paper which purports to do what you want in a more expression dependent manner:

"With the expansion of public repositories such as the Gene Expression Omnibus (GEO), we are rapidly cataloging cellular transcriptional responses to diverse experimental conditions. Methods that query these repositories based on gene expression content, rather than textual annotations, may enable more effective experiment retrieval as well as the discovery of novel associations between drugs, diseases, and other perturbations.

We develop methods to retrieve gene expression experiments that differentially express the same transcriptional programs as a query experiment. Avoiding thresholds, we generate differential expression profiles that include a score for each gene measured in an experiment. We use existing and novel dimension reduction and correlation measures to rank relevant experiments in an entirely data-driven manner, allowing emergent features of the data to drive the results. A combination of matrix decomposition and p-weighted Pearson correlation proves the most suitable for comparing differential expression profiles. We apply this method to index all GEO DataSets, and demonstrate the utility of our approach by identifying pathways and conditions relevant to transcription factors Nanog and FoxO3."

[Betatubulin]

thanks Daniel. the paper was just what I was thinking. very useful.