extracting entropy positional values from RNAfold output?

Question

[phil.biotec]

Dear All,

I have 3000+ RNA sequences in which I have mapped sites of putative endonuclease cleavage. I hypothesize that cleavage site nucleotides are located within regions relatively free of secondary structure. I obtained the RNA sequence 50 bases upstream and 50 downstream for each candidate cleavage site nucleotide, giving me input sequences 101 nt long. I then used the standalone version of RNAfold to predict the RNA foldings of each sequence. This program can give me the positional entropy for each position, as shown by mountain plot in the web version. I would like to extract the entropy positional values for all the calculated foldings so that I can plot the positional entropy averaged over all sequences. However, I cannot find the entropy positional values in the outputted .ps files in the standalone version. How can I get this information?

Thanks,

Philip.

[h.mon]

Can you show the command you are using? Are the .ps files images?

[phil.biotec]

I used the command: rnafold -o -p --MEA < cec1sample.txt

where cec1sample.txt is the file of my sequences in fasta format.

I got 2 postscript files and a FOLD file for each sequence. The output of the FOLD file looks something like this:

Pf3D7_01_v3,349268,+ GAGAAAAACAUCAAGCGAAAAUUCCAGACCUUGUAACCGAUGAAAAUGAGAAAACAAAUGUCGAAGAAACUCAACCUGUGGAAAAUGUAAACAAUGUUAAU ......(((((..........(((((.(..(((....((((..................))))........)))..).)))))..........)))))... ( -7.00) ......(((((..........(((((.(..(((....({{(,....{,......},...})))........)))..).)))))..........)))))... [ -9.17] ......(((((..........(((((.(..(((....((((..................))))........)))..).)))))..........)))))... { -7.00 d=8.41} ......(((((..........(((((.(..(((....((((..................))))........)))..).)))))..........)))))... { -7.00 MEA=86.56} frequency of mfe structure in ensemble 0.0295194; ensemble diversity 12.91

Answer 1

[h.mon]

The entropy positional values are obtained with the mountain.pl script. Check A short Tutorial on RNA Bioinformatics.