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I need to know the correct term(s) which are usually used in the parlance of both biology and bioinformatics for this study approach:

About 11 transcripts were investigated using qPCR for a number of samples (about 200) and then the gene expression data were subjected to data mining tools: principal component analysis (PCA), cluster analysis (CA) and the results were interpreted using other supportive data that were not included in PCA in order to reveal the nature of acquired clusters. Clusters obtained were then predicted from the gene expression data using machine learning classifiers. In short, it is a blend of molecular biology, data mining tools, and machine learning classification (predictive modeling).

Please if you have ever done this kind of data analysis, what should be the appropriate term to describe this approach?

Likely candidates

Gene expression profiling study

Transcript profiling study

Transcript Wide Analysis Study or TWAS for short

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I would bet the author is furthering a global screening approach (probably micro arrays). You don't really have enough info given , can you cite the paper? Right now There's a few different things going on here, like you deduced. –  rhill45 May 20 at 13:56
    
it isn't a microarray, it is a 96-well based gene expression analysis using real-time quantitative PCR (sample maximization approach, not gene-maximization). Unfortunately, I am not aware of any paper that did the same thing. –  doctorate May 20 at 16:03
    
I didn't say IT was a microarray, I said the intial study could have been a microarray, and this experiment you describe is now "pin-pointing" genes from that microarray data, as is usually, but not always, the case. As of now I think all this experiment can be parlanced into would be gene expression and linking that to omics data. –  rhill45 May 21 at 14:15

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