A signal processing method for alignment-free metagenomic binning: multi-resolution genomic binary patterns.

ABSTRACT: Algorithms in bioinformatics use textual representations of genetic information, sequences of the characters A, T, G and C represented computationally as strings or sub-strings. Signal and related image processing methods offer a rich source of alternative descriptors as they are designed to work in the presence of noisy data without the need for exact matching. Here we introduce a method, multi-resolution local binary patterns (MLBP) adapted from image processing to extract local 'texture' changes from nucleotide sequence data. We apply this feature space to the alignment-free binning of metagenomic data. The effectiveness of MLBP is demonstrated using both simulated and real human gut microbial communities. Sequence reads or contigs can be represented as vectors and their 'texture' compa

SUBMITTER: Kouchaki S 

PROVIDER: S-EPMC6377666 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature