# 'Best of 2014' - My Personal Opinion

Last year, I assembled a panel of judges, who chose the best bioinformatics contributions of the year from a number of suggestions made by the readers. You can see the results in Announcing the Results of Best of 2013?.

The entire process took quite a bit of time of everyone involved. Moreover, we had an early start to make the effort visible and get the most feedback from readers. This year I got busy and did not find enough time to notify the judges and the readers. So, instead of having the ‘Best of 2014’ in the same way as last year, I will share the ideas I found most interesting and encourage you to do the same in comment section.

**1. Succint de Bruijn Graph**

Variable-Order de Bruijn Graphs

Very recently, two papers came out implementing the succint de Bruijn graph idea of Alex Bowe et al. I found both of them quite interesting. The idea of succint de Bruijn graph merges two concepts - (i) de Bruijn graphs for assembly, (ii) XBW transform for graphs with its associated rank and select structure. The paper on variable order de Bruijn graph showed how succint de Bruijn graph could be used to naturally progress to de Bruijn graphs of multiple kmer sizes and I found that quite elegant.

**2. Minimizer**

On the representation of de Bruijn Graph

KMC 2: Fast and resource-frugal k-mer counting

Chikhi et al’s merger of assembly and minimizer was quite elegant. The aspects of KMC2 paper I found most interesting were - (i) treatment of homopolymer minimizers to adjust bucket sizes, (ii) highly parallel code.

**3. Cache-efficient common kmer finding in DALIGNER**

DALIGNER: Fast and sensitive detection of all pairwise local alignments

In DALIGNER paper, Gene Myers came up with a cache-efficient method for finding common k-mers from two reads, and the method scaled almost linearly with the number of cores. I found that quite elegant. Also, his method to use Pacbio stats to cut down unlikely paths in O(ND) alignment to make it useful for long reads was very good.

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The above is only a subset of a large number of unusual contributions made by bioinformatics researchers. A bigger list of interesting papers on NGS can be found in ASHG/GA4GH Special A Recap of Interesting NGS Algorithms of the Year. Please share in comment section any idea, paper, blog or teaching tool that you enjoyed.