Field of Science

One line of Perl code changed = new data!

This afternoon the post-doc and I were discussing the uptake-sequence analysis we're proposing for the CIHR grant. We wanted a way to compare the actual uptake of genome fragments with that predicted by their scores with the matrix I'd derived from the genome sequence using the Gibbs motif sampler. I realized that we might be able to use my existing Perl program (the one that evolves uptake sequences in simulated genomes) to score these.

So, after I burned out on rewriting paragraphs in the proposal, I opened up the giant Perl program In the 965 lines of code I found just the spot I wanted, and told the program to print the score it had just calculated. I put the first 10 kb of the H. influenzae genome sequence into a text file, and changed the program's settings file so it would score this sequence but wouldn't try to evolve it. And I created a scoring matrix using the output from one of my old Gibbs runs on the H. influenzae genome.

It ran! I pasted the output into a Word file and converted the '-' signs of the exponents of the scores (range -32 to -8) to a tab mark, and reopened the file in Excel. I then subtracted these values from 32, so now the lowest pseudoscore value was zero and the highest was 24. Then I plotted this 'score' against the row numbers

And here's the result (black bars). To check that I hadn't screwed up, I looked up the position of the highest score in the Excel file (score = 24, at position 5319) and checked the sequence I'd started with. Sure enough, at position 5319 I found AAAGTGCGGTCAATTTTTCTGGTATTTTTT, a near-perfect match to the USS consensus.

What this graph doesn't show very well is the large number of positions with very low scores. So here's another graph (blue bars) to the same scale, but showing only the first 300 positions. Now we see that most positions have scores less than 10.

Versions of these figures will go in the Appendix of the proposal, as preliminary data.

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