BGI's K-mer Analysis Paper

BGI's K-mer Analysis Paper

They always come in three, don’t they? We covered Rayan Chikhi’s KmerGenie (also see here) and Jared Simpson’s assembly preprocessing module (also check here).

Now BGI submitted their paper along the same line to arxiv. (h/t: @lexnederberg)

Background: With the fast development of next generation sequencing technologies, increasing numbers of genomes are being de novo sequenced and assembled. However, most are in fragmental and incomplete draft status, and thus it is often difficult to know the accurate genome size and repeat content. Furthermore, many genomes are highly repetitive or heterozygous, posing problems to current assemblers utilizing short reads. Therefore, it is necessary to develop efficient assembly-independent methods for accurate estimation of these genomic characteristics.

Results: Here we present a framework for modeling the distribution of k-mer frequency from sequencing data and estimating the genomic characteristics such as genome size, repeat structure and heterozygous rate. By introducing novel techniques of k-mer individuals, float precision estimation, and proper treatment of sequencing error and coverage bias, the estimation accuracy of our method is significantly improved over existing methods. We also studied how the various genomic and sequencing characteristics affect the estimation accuracy using simulated sequencing data, and discussed the limitations on applying our method to real sequencing data. Conclusion: Based on this research, we show that the k-mer frequency analysis can be used as a general and assembly-independent method for estimating genomic characteristics, which can improve our understanding of a species genome, help design the sequencing strategy of genome projects, and guide the development of assembly algorithms. The programs developed in this research are written using C/C++ and freely accessible at this ftp URL.

On k-mer counting, we covered four important papers at this link -

Quip, Minia, SlimGene and Titus Browns paper on Scaling Metagenome

Written by M. //