GraphBin: refined binning of metagenomic contigs using assembly graphs
Author(s) -
Vijini Mallawaarachchi,
Anuradha Wickramarachchi,
Yu Lin
Publication year - 2020
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btaa180
Subject(s) - contig , metagenomics , de bruijn graph , computer science , source code , graph , data mining , computational biology , biology , theoretical computer science , genome , genetics , gene , operating system
The field of metagenomics has provided valuable insights into the structure, diversity and ecology within microbial communities. One key step in metagenomics analysis is to assemble reads into longer contigs which are then binned into groups of contigs that belong to different species present in the metagenomic sample. Binning of contigs plays an important role in metagenomics and most available binning algorithms bin contigs using genomic features such as oligonucleotide/k-mer composition and contig coverage. As metagenomic contigs are derived from the assembly process, they are output from the underlying assembly graph which contains valuable connectivity information between contigs that can be used for binning.
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