ArticlePLoS computational biology2018
Using pseudoalignment and base quality to accurately quantify microbial community composition.
Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 30 citations in OpenAlex.
- Scaling laws of bacterial and archaeal plasmids.Nature communications · 2025Article
- Longitudinal profiling of low-abundance strains in microbiomes with ChronoStrain.Nature microbiology · 2025Article
- Where the Patterns Are: Repetition-Aware Compression for Colored de Bruijn GraphsJournal of computational biology : a journal of computational molecular cell biology · 2024Article
- A metagenomic analysis of the phase 2 Anopheles gambiae 1000 genomes dataset reveals a wide diversity of cobionts associated with field collected mosquitoes.Communications biology · 2024Article
- Fulgor: a fast and compact k-mer index for large-scale matching and color queries.Algorithms for molecular biology : AMB · 2024Article
- Themisto: a scalable colored k-mer index for sensitive pseudoalignment against hundreds of thousands of bacterial genomes.Bioinformatics (Oxford, England) · 2023Article
- Fulgor: A fast and compactbioRxiv : the preprint server for biology · 2023Article
- metaMIC: reference-free misassembly identification and correction of de novo metagenomic assemblies.Genome biology · 2022Article
- Nanopore sequencing of a monkeypox virus strain isolated from a pustular lesion in the Central African Republic.Scientific reports · 2022Article
- AGAMEMNON: an Accurate metaGenomics And MEtatranscriptoMics quaNtificatiON analysis suite.Genome biology · 2022Article
- PuffAligner: a fast, efficient and accurate aligner based on the Pufferfish index.Bioinformatics (Oxford, England) · 2021Article
- Metalign: efficient alignment-based metagenomic profiling via containment min hash.Genome biology · 2020Article
- Detection of Pathogenic Microbe Composition Using Next-Generation Sequencing Data.Frontiers in genetics · 2020Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Pooled DNA from multiple unknown organisms arises in a variety of contexts, for example microbial samples from ecological or human health research. Determining the composition of pooled samples can be difficult, especially at the scale of modern sequencing data and reference databases. Here we propose a novel method for taxonomic profiling in pooled DNA that combines the speed and low-memory requirements of k-mer based pseudoalignment with a likelihood framework that uses base quality information to better resolve multiply mapped reads. We apply the method to the problem of classifying 16S rRNA reads using a reference database of known organisms, a common challenge in microbiome research. Using simulations, we show the method is accurate across a variety of read lengths, with different length reference sequences, at different sample depths, and when samples contain reads originating from organisms absent from the reference. We also assess performance in real 16S data, where we reanalyze previous genetic association data to show our method discovers a larger number of quantitative trait associations than other widely used methods. We implement our method in the software Karp, for k-mer based analysis of read pools, to provide a novel combination of speed and accuracy that is uniquely suited for enhancing discoveries in microbial studies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.