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Need A Public Canonical Dna Alignment Problem With Known Good Solution

I am implementing a DNA alignment tool and I want to test it for correctness and performance against the best known tools. The basic alignment problem seems to be "here is this fastq file that we just got out of the sequencing machine; what parts of it align with this known fasta database?" One canonical fasta database seems to be the recent version of the human genome: hg19.fa. I don't want to use any proprietary data; are there public raw sequencing results that I can use somewhere to test against it? What is a good measure of a quality match? The output of BLAST? I'm willing to run a slow tool once to get a quality result that I can then use as a benchmark.

dna alignment
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updated by matted matted • written by daniel.wilkerson • daniel.wilkerson

3 answers

Just an idea for you: Simulate the data. That way you will known the false positive and false negative rates.

There is a lot of well developed alignment software. Bowtie, Bowtie2, BWA, ect....

Why are you trying to re-invent the wheel?

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written by Zev.Kronenberg Zev.Kronenberg

Good luck Daniel. Let me know if you want beta testers.

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written by Zev.Kronenberg Zev.Kronenberg

What I really need is (a) ONE REAL (not artificial) input to use to align against, say, hg19.fa and (b) a known really high quality expected output. If the best quality output can be gotten from a pubic tool, such as blast, then some advice on what parameters to pass to blast would help so I can run it myself.

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written by daniel.wilkerson • daniel.wilkerson

I would agree with @Zev. No need to invest time on re-creating a tool like that

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written by Whetting Whetting

What if my code is an order of magnitude faster? Your thesis seems to be that innovation is not possible. Where is the forum where people work together on innovation in biotechnology? I seem to have wandered onto the Forum of Useless and Unhelpful Remarks.

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written by daniel.wilkerson • daniel.wilkerson

I agree with the other posters in being skeptical about your claims, particularly given the apparent lack of familiarity with competing tools and evaluation metrics suggested by your questions. However, this is an inference based on limited data, and so it might be wrong. Best of luck nevertheless.

To answer your original question, take a look at the evaluation sections of two recent state-of-the-art tools. They use both simulated and published data (freely downloadable on the SRA, with accession codes given in the papers) to evaluate the performance of their algorithms. You could compare your new method against the competitors shown in Tables 1 and 2 in the BWA paper:

http://bioinformatics.oxfordjournals.org/content/25/14/1754.full

Or similarly with Figures 1 and 2 in the Bowtie 2 paper:

http://www.nature.com/nmeth/journal/v9/n4/full/nmeth.1923.html

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written by matted matted

Thanks for the pointers. On your other point, has it occurred to you that someone might know something about computation/algorithms without knowing much biology?

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written by daniel.wilkerson • daniel.wilkerson

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