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miRNA analysis: ranking

Hi I have data for deferentially expressed miRNAs for two different cultivars of a crop under two different treatments. (2 cultivars X 2 treatments = 4 sets of data)

-Can I use log2Fold change values for Heat map construction using all the miRNAs detected commonly in all four sets?

-How to rank the expression data to find the best responsive miRNA? The best responsive miRNA should be determined on the basis of activities in all 4 sets, not in single set. There is R based tool named as "RobustRankAggreg" for such thing I guess. But is there any other simple alternative for that?

Thanks.

sequencing rna-seq
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written by tushar131189 • tushar131189

A heatmap in (mi)RNA-seq is typically create from the differential RNAs. I personally prefer to convert data to the Z-scale based on the log2-transformed normalized counts. Say you have your count matrix with normalized and log-transformed values you can do t(scale(t(matrix))) to get the Z-scores. Then filter for the differential miRNAs you want.

RobustRankAggreg is a meta-analysis tool to e.g. compare different studies, I think it is not what you want. You could rank by signed nominal p-value (not FDR/p.adj). So e.g. sign(logFC)*pvalue. Ranking by fold change alone is problematic because genes with low counts tend to have higher FCs even though these FCs are not reliable. Ranking by FDR produces many ties for non-significant genes. Nominal pvalue is probably the most trushworthy ranking to choose.

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written by ATpoint ATpoint

Hello everyone....

Is there any method available for ranking the miRNAs/genes other than "R". Because "R" based statistics is far from user friendly for newcomer. Please any kind of help/suggestion is appreciated .

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written by tushar131189 • tushar131189

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