KOMB: K-core based de novo characterization of copy number variation in microbiomes.
CDI, Clostridium Difficile Infection
CNV, Copy Number Variation
Copy number variation (CNV)
DBG, De Bruijn Graphs
De Bruijn graph
ENA, European Nucleotide Archive
FMT, Fecal Matter Transplantation
FPR, False Positive Rate
Functional characterization
GO, Gene Ontology
GPL, (GNU) General Public License
Graph-based analysis
K-core decomposition
MAGs, Metagenome assembled genomes
Metagenome
ROC, Receiver Operating Curve
Repeats
SAM, Sequence Alignment Map
SRA, Sequence Read Archive
SVs, Structural Variants
TPR, True Positive Rate
Unitigs
Journal
Computational and structural biotechnology journal
ISSN: 2001-0370
Titre abrégé: Comput Struct Biotechnol J
Pays: Netherlands
ID NLM: 101585369
Informations de publication
Date de publication:
2022
2022
Historique:
received:
31
03
2022
revised:
08
06
2022
accepted:
09
06
2022
entrez:
14
7
2022
pubmed:
15
7
2022
medline:
15
7
2022
Statut:
epublish
Résumé
Characterizing metagenomes via kmer-based, database-dependent taxonomic classification has yielded key insights into underlying microbiome dynamics. However, novel approaches are needed to track community dynamics and genomic flux within metagenomes, particularly in response to perturbations. We describe KOMB, a novel method for tracking genome level dynamics within microbiomes. KOMB utilizes K-core decomposition to identify Structural variations (SVs), specifically, population-level Copy Number Variation (CNV) within microbiomes. K-core decomposition partitions the graph into shells containing nodes of induced degree at least K, yielding reduced computational complexity compared to prior approaches. Through validation on a synthetic community, we show that KOMB recovers and profiles repetitive genomic regions in the sample. KOMB is shown to identify functionally-important regions in Human Microbiome Project datasets, and was used to analyze longitudinal data and identify keystone taxa in Fecal Microbiota Transplantation (FMT) samples. In summary, KOMB represents a novel graph-based, taxonomy-oblivious, and reference-free approach for tracking CNV within microbiomes. KOMB is open source and available for download at https://gitlab.com/treangenlab/komb.
Identifiants
pubmed: 35832621
doi: 10.1016/j.csbj.2022.06.019
pii: S2001-0370(22)00233-1
pmc: PMC9249589
doi:
Types de publication
Journal Article
Langues
eng
Pagination
3208-3222Subventions
Organisme : NIAID NIH HHS
ID : U01 AI124290
Pays : United States
Informations de copyright
© 2022 The Author(s).
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