RT Journal Article
SR Electronic
T1 Metagenomic Binning through Multi-resolution Genomic Binary Patterns
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 096719
DO 10.1101/096719
A1 Samaneh Kouchaki
A1 Avraam Tapinos
A1 David L Robertson
YR 2016
UL http://biorxiv.org/content/early/2016/12/24/096719.abstract
AB Motivation High-throughput sequencing has facilitated the analysis of complex microbial communities. Consequently, an enormous number of sequences have been generated containing various regions of bacterial and viral genomes. Image processing offers a rich source of descriptors for data analysis. Here, we introduce a feature space called multi-resolution local binary patterns (MLBP) from image processing as a feature descriptor to extract local ‘texture’ changes from nucleotide sequences. We demonstrate its applicability to the alignmentfree binning of metagenomic data.Results The effectiveness of our approach is tested using both simulated and real human gut microbial communities. We compared the performance of our method with several existing techniques that are based on k-mer frequency to show it outperforms existing techniques. In addition, we provide a time-series study of the abundance pattern of each bin to help refine the formed clusters automatically and to find relations that may exist among the clusters. Although the main aim is to introduce the use of genomic signatures using an alternative feature space (MLBP), our results show its application to the analysis of contigs from a metagenomic study.Availability The source code for our Multi-resolution Genomic Binary Patterns method can be found at https://github.com/skouchaki/MrGBP