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915 results for “metagenomics”
Metagenome assembled genome (MAG) annotations for Columbia River sediment bacteria and archaea
<p>Excel spreadsheet containing all annotations for metagenome assembled genomes (MAGs) that form part of a publication to be submitted titled: "<strong>Microbial genome-resolved metaproteomic analyses frame intertwined carbon and nitrogen cycles in river hyporheic sediments". </strong></p>
Novel canine high-quality metagenome-assembled genomes by long-read metagenomics together with Hi-C proximity ligation
<p>We characterized a canine fecal sample of a healthy dog by combining a long-read metagenomics assembly (Nanopore sequencing) with Hi-C cross-linking data, and further correction of the frameshift errors. We retrieved and characterized 27 HQ MAGs and seven MQ MAGs considering MIMAG criteria.</p> <p>Find in this repository the final Hi-C genomics bins (CanMAG_XX-HiCbin.fa), including both the genome and the extra-chromosomal elements within the bin. </p> <p> </p>
Metagenome-assembled genomes(MAGs) generated from CRC human gut (PRJEB27928).
<p>MAGs generated from CRC human gut (PRJEB27928) with Maxbin2, VAMB, Metabat2, SemiBin(single-sample binning) and VAMB, SemiBin(multi-sample binning).</p> <p>Single-sample binning: Maxbin2.tar.gz, Metabat2.tar.gz, VAMB.tar.gz and SemiBin(_pretrain).tar.gz. </p> <p>Multi-sample binning: VAMB_multi.tar.gz and SemiBin_multi.tar.gz.</p>
Metagenome-assembled genomes(MAGs) generated from dog gut (PRJEB20308).
<p>MAGs generated from dog gut (PRJEB20308) with Maxbin2, VAMB, Metabat2, SemiBin(single-sample binning) and VAMB, SemiBin(multi-sample binning).</p> <p>Single-sample binning: Maxbin2.tar.gz, Metabat2.tar.gz, VAMB.tar.gz and SemiBin(_pretrain).tar.gz. </p> <p>Multi-sample binning: VAMB_multi.tar.gz and SemiBin_multi.tar.gz.</p>
Metagenome-assembled genomes(MAGs) generated from ocean (PRJEB1787).
<p>MAGs generated from ocean (PRJEB1787) with Maxbin2, VAMB, Metabat2, SemiBin(single-sample binning) and VAMB, SemiBin(multi-sample binning).</p> <p>Single-sample binning: Maxbin2.tar.gz, Metabat2.tar.gz, VAMB.tar.gz and SemiBin(_pretrain).tar.gz. </p> <p>Multi-sample binning: VAMB_multi.tar.gz and SemiBin_multi.tar.gz.</p>
Mead's Quarry Coassembly (Metagenomic)
<p>Metagenomic coassembly (final.contigs.fa) of 2022 (n = 2) and 2024 (n = 4) sequencing libraries generated by the 2024 MICR 669 Advanced Techniques in Field Microbiology course (Microbiology Department, University of Tennessee Knoxville). This coassembly was made publicly available to coincide with the manuscript submitted to Harmful Algae. The protein sequences (proteins.faa) and nucleotide sequences (nucleotides.fna) that were determined from called open reading frames are also included. </p>
Metagenomics of Parkinson's disease implicates the gut microbiome in multiple disease mechanisms
<p><strong>Abstract:</strong> Parkinson's disease (PD) may start in the gut and spread to the brain. To investigate the role of gut microbiome, we conducted a large-scale study, at high taxonomic resolution, using uniform standardized methods from start to end. We enrolled 490 PD and 234 control individuals, conducted deep shotgun sequencing of fecal DNA, followed by metagenome-wide association studies requiring significance by two methods (ANCOM-BC and MaAsLin2) to declare disease association at species and genus level, followed by network analysis to identify polymicrobial clusters, and functional profiling based on microbial genes and pathways. Here we show that over 30% of species, genes and pathways tested have altered abundances in PD, depicting a widespread dysbiosis. PD-associated species form polymicrobial clusters that grow or shrink together, and some compete. PD microbiome is disease permissive, evidenced by overabundance of pathogens and immunogenic components, dysregulated neuroactive signaling, preponderance of molecules that induce alpha-synuclein pathology, and over-production of toxicants; with the reduction in anti-inflammatory and neuroprotective factors limiting the capacity to recover. We validate, in human PD, findings that were observed in experimental models; reconcile and resolve human PD microbiome literature, and provide a broad foundation with a wealth of concrete testable hypotheses to discern the role of the gut microbiome in PD. </p> <p><strong>Zenodo contents:</strong> In this Zenodo archive we provide (1) post sequence QC and post taxonomic and functional profiling "Source Data" used to generate tables and figures in the manuscript and (2) "Supplementary Code" that contains the workflow and code used to perform bioinformatic processing of shotgun sequences and statistical analyses of microbial profiles and subject metadata. The code provided here is the same "Supplementary Code" that is provided in the supplement of the manuscript. Individual level raw shotgun sequences and metadata are available on NCBI Sequence Read Archive (SRA) under BioProject ID <a href="https://www.ncbi.nlm.nih.gov/bioproject/834801">PRJNA834801</a>.</p>
Supplemental data for: Longitudinal, multi-platform metagenomics yields a high-quality genomic catalog and guides an in vitro model for cheese communities
<p><span>Microbiomes are intricately intertwined with human health, geochemical cycles, and food production. While many microbiomes of interest are highly complex and experimentally intractable, cheese rind microbiomes have proven powerful model systems for the study of microbial interactions. To provide a more comprehensive view of the genomic potential and temporal dynamics of cheese rind communities, we combine longitudinal, multi-platform metagenomics of three ripening washed-rind cheeses with whole genome sequencing of community isolates. Sequencing-based approaches revealed a highly reproducible microbial succession in each cheese, co-existence of closely related <em>Psychrobacter</em> species, and enabled the prediction of plasmid and phage diversity and their host associations. Combined with culture-based approaches, we established a genomic catalog and a paired 16-member in vitro washed rind cheese system. The combination of multi-platform metagenomic time-series data and an <em>in vitro</em> model provides a rich resource for further investigation of cheese rind microbiomes both computationally and experimentally. </span></p>
Dataset - Campylomics, strain-typing metagenomics data
<p>Raw data files for submission: "Metagenomic Strain-Typing Combined with Isolate <br> Sequencing Provides Increased Resolution of the Genetic <br> Diversity of <em>Campylobacter jejuni</em> Carriage in Wild Birds"</p> <p>strainestDB.tar.xz files expand to rather large file sizes 6-12Gb</p> <p>Code for workflow and additional description:<br> https://git.list.lu/malte.herold/campylomics_pipeline<br> </p> <p>contained:</p> <ul> <li>additional tables (e.g. list of reference genomes, metadata), multiqc data</li> <li>3 Cjejuni strainEST databases</li> <li>Results of the workflow for the 3 databases: strainest_results</li> <li>KMA results (the same for all 3 runs)</li> <li>KMA database</li> <li>sourmash distances of references genomes used for the strainest DBs</li> </ul> <p>some files might still hold references to a 4th database CJC_CGC, not included here.</p> <p> </p> <p> </p>
Expanding the host-range of functional metagenomics reveals resistance threats to novel antibiotics
<p>Expanding the host-range of functional metagenomics reveals resistance threats to novel antibiotics. Sequences.</p>
16S counts of soil metagenomes
<p>Count of 16S matches in soil microbiomes, a subset of the 214K metagenomic collection https://zenodo.org/record/6919377#.Y5hhQnbMJD8</p>
Determinants of associations between codon and amino acid usage patterns of microbial communities and the environment inferred based on a cross-biome metagenomic analysis
<p>Raw data set for npj Bioflims and Microbiome article: “Determinants of associations between codon and amino acid usage patterns of microbial communities and the environment inferred based on a cross-biome metagenomic analysis”</p>
Canine Simulated Metagenome
<p>Composition: five PE 2X 150 nt fastq libraries simulated with ART (Illumina HiSeq 2500 profile).</p>
Supplementary Dataset of Marine Metagenomes from Surface Sediments along the coastline of Kuwait
<p>This dataset was obtained through shot gun metagenomic sequencing conducted on surface sediments in close vicinity of emergency outfalls discharged through the storm outlets. It provides information on the diverse microbial communities and dominant metabolic functions occuring at these sites under a selective force of various contaminants brought in through the effluent discharges.</p>
Fasta format protein sequences from assembled kyphosid fish gut metagenomes
<p>Predicted proteins sequences from kyposid fish gut metagenomic samples F5, F6, F7, and F8, obtained as described in the following study:</p> <p>Podell S, Oliver A, Kelly LW, Sparagon W, Plominsky, A, Nelson RS, Laurens LML, Augyte, S, Sims NA, Nelson CE, Allen EE. Herbivorous fish microbiome adaptations to sulfated dietary polysaccharides (2023)<br> manuscript submitted.</p>
Supplementary Tables and Datasets for publication: Spatial and finely tuned temporal metagenomics of river compartments reveals viral community dynamics in an urban stream
<p>This is a data dump of the tables, genomes, and .faa files that were too large to submit as part of the publication titled: Spatial and finely tuned temporal metagenomics of river compartments reveals viral community dynamics in an urban stream</p> <p> </p> <p>Files here include:</p> <p>-Fasta file containing 1230 vMAGs.</p> <p>-Zip file containing individual fasta files for 125 MAGs</p> <p>-Annotations output for DRAM and DRAM-v for all MAGs and vMAGs</p> <p>-.faa proteins file for the full Freshwater / Wastewater / TARA Oceans dataset that was used for vContact2 biogeography analyses</p>
Gut resistome associations with dyslipidemia using metagenomics
<p>Dataset for the alpha diversity analysis of ARGs and microbial species. "ARG_diversity.txt" is the alpha diversity indices of ARG abundance, and "taxa_div.txt" is the alpha diversity indices of microbial species found in all samples.</p>
HairSplitter: separating strains in metagenome assemblies with long reads
<p>Datasets, command lines and assemblies analyzed in the manuscript "HairSplitter: separating strains in metagenome assemblies with long reads".</p>
Oceanic Prokaryotes Metagenome-Assembled Genomes reconstructed using metagenomic distances
<p>Sets of reconstructed Metagenome-Assembled Genomes (MAGs) from Tara Oceans dataset. The reconstructed MAGs belong to Magneto paper: https://doi.org/10.1128/msystems.00432-22</p> <p>The dataset is composed of 93 oceanic metagenomes sampled from non-polar oceanic regions.</p> <p>The Metagenomic Distance MAGs were reconstructed following a co-assembly protocol driven by nucleotidic composition similarity, as detailed in the publication.</p> <p>The Oceanic Region MAGs were reconstructed by co-assembly of samples belonging to the same Oceanic Regions.</p> <p>The file clusters.tsv sum up the metagenomic distance cluster and the oceanic region each sample belongs to.</p>
Traing Data for "Assembly of metagenomic sequencing data" tutorial
<p>Metagenomics involves the extraction, sequencing and analysis of combined genomic DNA from <strong>entire microbiome</strong> samples. It includes then DNA from <strong>many different organisms</strong>, with different taxonomic background.</p> <p>Reconstructing the genomes of microorganisms in the sampled communities is critical step in analyzing metagenomic data. To do that, we can use <strong>assembly</strong> and assemblers, <em>i.e.</em> computational programs that stich together the small fragments of sequenced DNA produced by sequencing instruments.</p> <p>Assembling seems intuitively similar to putting together a jigsaw puzzle. Essentially, it looks for reads “that work together” or more precisely, reads that overlap. Tasks like this are <strong>not straightforward</strong>, but rather complex because of the complexity of the genomics (specially the repeats), the missing pieces and the errors introduced during sequencing.</p> <p>In this tutorial, we will learn how to run metagenomic assembly tool and evaluate the quality of the generated assemblies. To do that, we will use data from the study: <a href="https://www.ebi.ac.uk/metagenomics/studies/MGYS00005630#overview">Temporal shotgun metagenomic dissection of the coffee fermentation ecosystem</a>. For an in-depth analysis of the structure and functions of the coffee microbiome, a temporal shotgun metagenomic study (six time points) was performed. The six samples have been sequenced with Illumina MiSeq utilizing whole genome sequencing.</p> <p>Based on the 6 original dataset of the coffee fermentation system, we generated mock datasets for this tutorial.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.