In DALIGN Paper, Gene Myers Delivers a Major Blow to His Biggest Competitor

In DALIGN Paper, Gene Myers Delivers a Major Blow to His Biggest Competitor


While Gene Myers was busy working on neural images of fruitflies, he noticed the bioinformatics land being taken over by search algorithm originating from a ‘competitor’. Now he comes back with an outstanding paper (DALIGN) to show why he is still the master.

That competitor of Gene Myers is none other than Gene Myers, 20 years younger. In early 90s, he and Udi Manber (currently leading the search group at Google) introduced the concept of suffix arrays. Fast forward by two decades, every nucleotide search program for new sequencing technologies uses suffix arrays, combined with BWT transform and FM indices. We covered that history in an earlier commentary (check this blog post from 2011).

Myers tried to use BLASR, which incorporated suffix arrays, for aligning PacBio reads and found it to be too slow. The troubles come from memory bandwidth and cache incoherence. Modern processors have three levels of cache (L1, L2, L3) and the speed difference between having all data in L1 cache vs DRAM can be 100x. BWT-based FM index algorithm makes effectively random accesses to memory locations and therefore the search process gets highly dependent on DRAM access. Especially when one tries to scale BWT-based alignment programs with multiple cores, memory bandwidth becomes the major bottleneck. Our readers are well familiar with that drawback (Check “The Future of Computers Multicore and the Memory Wall”).

The algorithm proposed by Myers overcomes that bottleneck in two steps. They are so elegant that even the memory-heavy part of his algorithm sees 3.6x scaleup in a 4-core machine, whereas the less memory-intensive part sees 3.88x scaleup. The steps are - (i) finding read pairs highly likely to align based on matching seeds and (ii) alignment. Even though they sound innocuous, the beauty is in the details. The memory-intensive rapid seed detection part introduces a highly cache-coherent radix sort algorithm that attempts to keep relevant bits in L1 cache. The rapid local alignment part uses Myers’ own O(nd) algorithm from mid-80s (see “How Does the Unix Diff Algorithm Work?”) , but with several optimization steps to limit the rapidly expanding parallel waves at every step of search. Especially it makes use of random distribution of errors in PacBio reads.

What next after this formidable accomplishment of speeding up PacBio alignment 25X over BLASR and thus making large assemblies possible? There are rumors that Gene Myers plans to demonstrate one or more of the following three - (i) walk over water on river Elbe, (ii) design a perfect assembler, (iii) finish the zebrafish genome. Given how difficult (ii) and (iii) turned out to be so far, we believe he will go for (i).

If, instead, Myers plans to finish Danio and thousands of other recently published incomplete genomes, he needs to hurry up. We heard that Udi Manber, who is currently at Google, is working on a different solution for those bad genomes. Google plans to replace all NNNNNN regions with targeted ads, and there is a possibility that Google will buy a short-read company, because more gaps, the better.



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The full article by Myers will appear in WABI 2014 (Workshop on Algorithms in Bioinformatics), Sept 8-10, Wroclaw, Poland. In the meanwhile, readers interested to know more about his developments can check his blog. The code of DALIGNER is available from github.

Written by M. //