>X=RNA_seq_variable_of_interest

>p=ecdx(x)

#returns value close to 0.5

>p(0.0)

#draw the CDF

>plot (p)

Dear Sébastien Hébert ,

Firstly, I should say that I am not certain what you are asking. I think you are saying that you would like a CDF plot from RNA-sequencing data which demonstrates the differing effects of the treatment (i.e. miRNA knockout) on two or more different groups of transcripts? And that one of these groups is related to identified or predicted miRNA target sites.

If so, execute the following steps:

1. Perform transcript quantification for all transcripts/genes used in your analysis

2. Use some form of differential expression analysis to calculate the change in expression of your genes between WT and KO conditions. For example, DESeq2 will give you a measure of log fold change between conditions.

3. Once you have your fold change (or whatever differential expression metric you are using) - divide your dataset into constituent groups e.g. predicted miRNA targets and predicted miRNA non-targets.

4. Plot an ECDF for one of your groups with the following in R:

plot(ecdf(x))

*where x is an array of log fold change values for your first group.

5. Now add additional curves to this plot using:

plot(ecdf(y), add=T)

*where y is an array of log fold change values for your second group.

I hope this helps.