Fast DNA search and [host] depletion using minimizers - bede/deacon

Abstract. Microbes differ greatly in their organismal structure, physiology, and environmental adaptation, yet information about these phenotypic traits is

Differences in genomic GC content skew species abundances in microbial communities. Here, the authors develop GuaCAMOLE, a computational method that quantifies this GC bias from metagenomic sequencing data and corrects abundances accordingly, showing its application increases abundances of some pathogenic bacteria up to twofold in human gut microbiomes.

Background The characterization of complex microbial communities is a critical challenge in microbiome research, as it is essential for understanding the intricate relationships between microorganisms and their environments. Metagenomic profiling has advanced into a multifaceted approach, combining taxonomic, functional, and strain-level profiling (TFSP) of microbial communities. Here, we present Meteor2, a tool that leverages compact, environment-specific microbial gene catalogues to deliver comprehensive TFSP insights from metagenomic samples. Results Meteor2 currently supports 10 ecosystems, gathering 63,494,365 microbial genes clustered into 11,653 metagenomic species pangenomes (MSPs). These genes are extensively annotated for KEGG orthology, carbohydrate-active enzymes (CAZymes) and antibiotic-resistant genes (ARGs). In benchmark tests, Meteor2 demonstrated strong performance in TFSP, particularly excelling in detecting low-abundance species. When applied to shallow-sequenced datasets, Meteor2 improved species detection sensitivity by at least 45% for both human and mouse gut microbiota simulations compared to MetaPhlAn4 or sylph. For functional profiling, Meteor2 improved abundance estimation accuracy by at least 35% compared to HUMAnN3 (based on Bray–Curtis dissimilarity). Additionally, Meteor2 tracked more strain pairs than StrainPhlAn, capturing an additional 9.8% on the human dataset and 19.4% on the mouse dataset. Furthermore, in its fast configuration, Meteor2 emerges as one of the fastest available tools for profiling, requiring only 2.3 min for taxonomic analysis and 10 min for strain-level analysis against the human microbial gene catalogue when processing 10 M paired reads — operating within a modest 5 GB RAM footprint. We further validated Meteor2 using a published faecal microbiota transplantation (FMT) dataset, demonstrating its ability to deliver an extensive and actionable metagenomic analysis. The unified database design also simplifies the integration of TFSP outputs, making it straightforward for researchers to interpret and compare results. Conclusions These results highlight Meteor2 as a robust and versatile tool for advancing microbiome research and applications. As an open-source, easy-to-install, and accurate analysis platform, Meteor2 is highly accessible to researchers, facilitating the exploration of complex microbial ecosystems. Video Abstract

An extension of ggplot2 for creating complex genomic maps. It builds on the power of ggplot2 and tidyverse adding new ggplot2-style geoms & positions and dplyr-style verbs to manipulate the…

Abstract. Metagenomic sequencing enables the in-depth study of microbes and their functions in humans, animals, and the environment. While sequencing data

Abstract. The Genome Taxonomy Database (GTDB; https://gtdb.ecogenomic.org) provides a phylogenetically consistent and rank normalized genome-based taxonomy

We introduce Mapping-friendly Sequence Reduction (MSR) sketches, a sketching method for high-fidelity (HiFi) long reads, and Alice, an assembler that operates directly on these sketches. MSR produces ...

MetaGraph enables scalable indexing of large sets of DNA, RNA or protein sequences using annotated de Bruijn graphs.

AbstractMotivation. Long-read sequencing enables complete bacterial genome assemblies, but individual assemblers are imperfect and often produce sequence-l

a blog for miscellaneous bioinformatics stuff

Microbial co-occurrence network inference is often hindered by low accuracy and tool dependency. We introduce microbetag, a comprehensive software ecosystem designed to annotate microbial networks. No...

Metagenomic analyses of microbial communities have unveiled a substantial level of interspecies and intraspecies genetic diversity by reconstructing metagenome-assembled genomes (MAGs). The MAG database (MAGdb) boasts an impressive collection of 74 representative research papers, spanning clinical, environmental, and animal categories and comprising 13,702 paired-end run accessions of metagenomic sequencing and 99,672 high quality MAGs with manually curated metadata. MAGdb provides a user-friendly interface that users can browse, search, and download MAGs and their corresponding metadata information. It represents a valuable resource for researchers in discovering potential novel microbial lineages and understanding their ecological roles. MAGdb is publicly available at https://magdb.nanhulab.ac.cn/ .

LexicMap uses a fixed set of probes to efficiently query gene sequences for fast and low-memory alignment.