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deep learning predict gene expression

how to utilize deep learning to predict (differential) gene expression based on RNAseq, ChIPseq and HiC?

rna-seq
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updated by i.sudbery i.sudbery • written by BenHu • BenHu

Do you mean predict based on covariates? What is your objective?

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written by jamietmorton • jamietmorton

I want to know which epigenetic features, such as promoter, enhancer, or promoter-enhancer interactions, affect gene expression?

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written by BenHu • BenHu

All of the above and more.

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written by russhh russhh

yes. But I want to systematically to predict these elements.

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written by BenHu • BenHu

No ml tools can do these tasks now. You may develop one by your own..

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written by shoujun.gu shoujun.gu

2 answers

A very interesting topic IMO. I think there is no easy answer to your question because you would need a lot of multi-dimensional data to say that element A is regulating gene B - and you would need functional validation with wet-lab experiments. However, what came to my mind is ChromHMM (http://compbio.mit.edu/ChromHMM/). This characterizes your genomic elements based on ChIP-seq data - however interpretation of the elements is on you. Another paper which i found is this one: https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-019-5997-2. Hope it helps & best wishes

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written by sim.j.baum sim.j.baum

thanks. I am reading that paper. best

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written by BenHu • BenHu

This is obviously an interesting topic, but it is not a solved question currently. I would investigate the work of Anshul Kundaje, who's group works in this area. https://sites.google.com/site/anshulkundaje/Home

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written by i.sudbery i.sudbery

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