TY - GEN
T1 - GraphBin2
T2 - 20th International Workshop on Algorithms in Bioinformatics, WABI 2020
AU - Mallawaarachchi, Vijini G.
AU - Wickramarachchi, Anuradha S.
AU - Lin, Yu
PY - 2020/8/25
Y1 - 2020/8/25
N2 - Metagenomic sequencing allows us to study structure, diversity and ecology in microbial communities without the necessity of obtaining pure cultures. In many metagenomics studies, the reads obtained from metagenomics sequencing are first assembled into longer contigs and these contigs are then binned into clusters of contigs where contigs in a cluster are expected to come from the same species. As different species may share common sequences in their genomes, one assembled contig may belong to multiple species. However, existing tools for contig binning only support non-overlapped binning, i.e., each contig is assigned to at most one bin (species). In this paper, we introduce GraphBin2 which refines the binning results obtained from existing tools and, more importantly, is able to assign contigs to multiple bins. GraphBin2 uses the connectivity and coverage information from assembly graphs to adjust existing binning results on contigs and to infer contigs shared by multiple species. Experimental results on both simulated and real datasets demonstrate that GraphBin2 not only improves binning results of existing tools but also supports to assign contigs to multiple bins.
AB - Metagenomic sequencing allows us to study structure, diversity and ecology in microbial communities without the necessity of obtaining pure cultures. In many metagenomics studies, the reads obtained from metagenomics sequencing are first assembled into longer contigs and these contigs are then binned into clusters of contigs where contigs in a cluster are expected to come from the same species. As different species may share common sequences in their genomes, one assembled contig may belong to multiple species. However, existing tools for contig binning only support non-overlapped binning, i.e., each contig is assigned to at most one bin (species). In this paper, we introduce GraphBin2 which refines the binning results obtained from existing tools and, more importantly, is able to assign contigs to multiple bins. GraphBin2 uses the connectivity and coverage information from assembly graphs to adjust existing binning results on contigs and to infer contigs shared by multiple species. Experimental results on both simulated and real datasets demonstrate that GraphBin2 not only improves binning results of existing tools but also supports to assign contigs to multiple bins.
KW - Assembly graphs
KW - Contigs
KW - Metagenomics binning
KW - Overlapped binning
KW - GraphBin2
UR - http://www.scopus.com/inward/record.url?scp=85092791279&partnerID=8YFLogxK
U2 - 10.4230/LIPIcs.WABI.2020.8
DO - 10.4230/LIPIcs.WABI.2020.8
M3 - Conference contribution
AN - SCOPUS:85092791279
T3 - Leibniz International Proceedings in Informatics, LIPIcs
BT - 20th International Workshop on Algorithms in Bioinformatics, WABI 2020
A2 - Kingsford, Carl
A2 - Pisanti, Nadia
PB - Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
Y2 - 7 September 2020 through 9 September 2020
ER -