visualizing gene and microarray expression datasets together

Question: visualizing gene and microarray expression datasets together

4.6 years ago by

Abhi • 1.5k

United States

Abhi • 1.5k wrote:

Hi Folks

I am trying to think of ways in which I can display microRNA and gene expression datasets. For now I am doing two separate interactive heatmaps.

here is gene expression

and microRNA expression

I think it would be more powerful if one could summarize them together and show how the microRNA and genes expression interacts with each other.Looking for ideas and any existing methods/tools that could help.

Cheers!

-Abhi

microrna rna-seq visualization • 1.3k views

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modified 4.6 years ago by Asaf ♦ 5.2k • written 4.6 years ago by Abhi • 1.5k

could you add the heatmaps themselves so what you are trying to do would be more clear

ADD REPLY • link written 4.6 years ago by oganm • 60

sure done..see the initial post

ADD REPLY • link written 4.6 years ago by Abhi • 1.5k

Seems like a pretty open question. Here my suggestion: miR-gene networks. MiRs and Genes are nodes. Edges can be drawn between them if e.g. A) strong negative correlation, B) miR is predicted to target gene...etc

ADD REPLY • link written 4.6 years ago by lkmklsmn • 860

4.6 years ago by

Charles Warden ♦ 6.1k

Duarte, CA

Charles Warden ♦ 6.1k wrote:

For a given miRNA-target interaction (predicted by a tool like targetScan), you could create a scatter plot between paired measurements (which should hopefully have a negative correlation; otherwise, I wouldn't consider this a plausible interaction in your own dataset).

ADD COMMENT • link written 4.6 years ago by Charles Warden ♦ 6.1k

4.6 years ago by

Asaf ♦ 5.2k

Israel

Asaf ♦ 5.2k wrote:

I doubt it that you will see correlation between miRNAs and their target mRNAs since they have very little influence on mRNA levels. You should expect to see similar patterns of miRNAs and mRNAs in similar cells (or cultures, conditions or whatever you're looking at) but this will tell you more about the TFs that set the pattern of the mRNAs and miRNAs.

An intuitive way of combining the data would be to rank the miRNAs in each sample according to the expression and rank the miRNAs in the sample and then you can plot both of them on the same figure. You can then try and do biclustering (e.g. Tanay et al: http://bioinformatics.oxfordjournals.org/content/18/suppl_1/S136.short ) to discover sets of miRNAs and mRNAs that determine a specific or a set of conditions.

If you don't want to use ranking and you assume the data in both datasets is normally distributed you can take the STD from the mean as the expression level in each dataset and they will be comparable between the two.

ADD COMMENT • link written 4.6 years ago by Asaf ♦ 5.2k

Are you sure about that? Because shRNA's effect can be clearly seen by disappearence of mRNAs. I'd expect miRNAs to act in a comparable manner

ADD REPLY • link written 4.6 years ago by oganm • 60

Yes, miRNAs have a slight effect, e.g. http://www.pnas.org/content/106/8/2735.full Fig. 2A the target genes change in less than 2 fold.

ADD REPLY • link written 4.6 years ago by Asaf ♦ 5.2k

this is certainly hitting on the other side of my intuition and now even more excited to see if there are any patterns in miRNA and mRNA expression in this datasets. I sort of thought we would see some negative correlation.

ADD REPLY • link written 4.6 years ago by Abhi • 1.5k

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