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I'M Looking For A Bioinformatics Problem Which Could Benefit From A New Or Improved Algorithm, Or From Being Mapped To The Gpu Architecture..

Hello. I am an undergrad majoring in computer science. I am learning GPGPU programming right now, and would like to find a good problem to apply it to. I was wondering if someone can point me in the right direction for finding a relatively simple but important bioinformatics problem, of which I can contribute to the solution by attempting to write an improved, or massively parallel algorithm.

algorithm

For short reads alignment or genome assembly.

3 answers

Some ideas:

  • How about the calculation of Linkage Disequilibrium? It's relatively basic math (check these slides for a quick introduction) and easily done in a second for just a couple of SNPs. However, if you want to do LD-analysis genome-wide over many chromosomes with several hundred thousand SNPs you'll have to wait for hours until you see results as you compare all SNPs with all SNPs. This could benefit from a pre-processing step which splits up the SNPs into several sets and assigns each set to a different thread and then calculates LD using several CPUs (or GPUs).
  • How about BLAST? As far as I know there's already one GPU-BLAST implementation, but that one can only align protein sequences, so you could go for nucleotide-alignment. The problem here might be that the algorithms involved are a bit more complicated (I guess you could skip the database-creation and just go for the alignment itself?).
  • ab initio gene prediction: There are a couple of programs which predict genes based on Hidden Markov Models like SNAP or Augustus, but none of these have parallel (or even GPU) implementations.

+1 for GPU-blastn. I've been trying to get the current blastx running on a CUDA, with a distinct amount of difficulty. but blastn is what i really want!

Thanks for the suggestions. I'm not exactly an expert yet in GPGU programming, but I will look into Blastx and see if it is something I can work towards.

Hello,

There are currently no good publicly available tools for identifying footprints in DNase-Seq data. The algorithm is pretty straight forward, look within areas of DNase Hypersensitivity for short segments of DNA protected from cleavage by bound Transcription factors. It can be done in parallel with many nodes inspecting different locations simultaneously. If you are interested let me know, and I can help get you started.

That sounds like something might be interested in.

I am also interested in this concept. I see some relevant publications, but I suppose you mean there is not available code yet, right? I am asking because there have passed 10 months since this post.

Thanks

Since I wrote this, the following paper was published: http://nar.oxfordjournals.org/content/41/21/e201.long It actually provides software for doing DNase-seq analysis. I have not tried the software yet, but I did speak with the author of the paper, and this should address many of the common DNase-seq analysis questions.

scan_for_matches could really use an overhaul (reimplementation!). Let me know if you are going for this one.

http://blog.theseed.org/servers/2010/07/scan-for-matches.html

Thank you for your suggestion. I'll look into it.

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