Abstract
Genomes computationally inferred from large metagenomic data sets are often incomplete and may be missing functionally important content and strain variation. We introduce an information retrieval system for large metagenomic data sets that exploits the sparsity of DNA assembly graphs to efficiently extract subgraphs surrounding an inferred genome. We apply this system to recover missing content from genome bins and show that substantial genomic sequence variation is present in a real metagenome. Our software implementation is available at https://github.com/spacegraphcats/ spacegraphcats under the 3-Clause BSD License.
Footnotes
DM, MPO, FR, and BDS designed and implemented algorithms; CTB, DM, MPO, and FR developed software; CTB and TR conducted biological data analysis; CTB and BDS supervised work. All authors interpreted results, wrote text, created figures, and approved the submitted paper.
