Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
915
datasets available to search
ShareScore release 0.7.1
Dataset results
915 results for “metagenomics”
Supplementary material 2 from: Garrido-Sanz L, Senar MÀ, Piñol J (2020) Estimation of the relative abundance of species in artificial mixtures of insects using low-coverage shotgun metagenomics. Metabarcoding and Metagenomics 4: e48281. https://doi.org/10.3897/mbmg.4.48281
: Data type: Excel table
Supplementary material 1 from: Garrido-Sanz L, Senar MÀ, Piñol J (2020) Estimation of the relative abundance of species in artificial mixtures of insects using low-coverage shotgun metagenomics. Metabarcoding and Metagenomics 4: e48281. https://doi.org/10.3897/mbmg.4.48281
: Data type: Boxplot
Raw metagenomic data from gut contents of Dallia pectoralis specimens collected in Kenai, Alaska, in 2019
<p>Gut contents were dissected from five Alaska blackfish (<em>Dallia pectoralis</em> T. H. Bean, 1880) specimens from Kenai, Alaska. Specimen data and associated images have been made available via an Arctos project at <a href="http://arctos.database.museum/project/10003367">http://arctos.database.museum/project/10003367</a>.</p> <p>Vials of gut contents were sent to RTL Genomics in Lubbock, Texas (<a href="https://rtlgenomics.com/">https://rtlgenomics.com/</a>) for RTL Genomics' standard microbial diversity assay using the <em>mlCOIint</em>/<em>jgHCO2198</em> (GGWACWGGWTGAACWGTWTAYCCYCC/TAIACYTCIGGRTGICCRAARAAYCA) primer set.</p> <p>This dataset includes specimen data downloaded from Arctos and DNA extraction methods, DNA sequencing methods, resulting raw metagenomic data, and related files from RTL Genomics.</p>
Supplementary material 8 from: Zizka VMA, Weiss M, Leese F (2020) Can metabarcoding resolve intraspecific genetic diversity changes to environmental stressors? A test case using river macrozoobenthos. Metabarcoding and Metagenomics 4: e51925. https://doi.org/10.3897/mbmg.4.51925
Table S1. Number of macroinvertebrate individuals per sample and season
Sequences of microbial eukaryotic genes obtained from the metagenome of the Mariana Trench
<p>nonredundant_eukaryotic_genes.faa contains the non-redundant amino acid sequences of predicted eukaryotic genes in all samples by MetaEuk.</p> <p>nonredundant_eukaryotic_genes.fna contains the non-redundant nucleotide sequences of predicted eukaryotic genes in all samples by MetaEuk.</p> <p>tax_for_per_gene.txt contains the taxonomic information of per non-redundant gene.</p>
Supplementary material 1 from: Duarte S, Vieira PE, Costa FO (2020) Assessment of species gaps in DNA barcode libraries of non-indigenous species (NIS) occurring in European coastal regions. Metabarcoding and Metagenomics 4: e55162. https://doi.org/10.3897/mbmg.4.55162
Supplementary figures and tables used to analyse the data
Supporting data for the manuscript "metaFlye: scalable long-read metagenome assembly using repeat graphs"
<p>Genome assemblies, simulated datasets and evaluations described in the manuscript "metaFlye: scalable long-read metagenome assembly using repeat graphs".</p>
Unmasking viral sequences by metagenomic next-generation sequencing in adult human blood samples during steroid-refractory/dependent graft-versus-host disease
<p><b>Background: </b>Viral infections are common complications following allogeneic hematopoietic stem cell transplantation (allo-HSCT<b>)</b>. Allo-HSCT recipients<b> </b>with steroid-refractory/dependent graft-versus-host disease (GvHD) are highly immunosuppressed and are more vulnerable to infections with weakly pathogenic or commensal viruses. Here, twenty-five adult allo-HSCT recipients from 2016 to 2019 with acute or chronic steroid-refractory/dependent GvHD were enrolled in a prospective cohort of patients at Geneva University Hospitals. We performed metagenomics next-generation sequencing (mNGS) analysis using a validated viral pipeline and <i>de novo</i> analysis on pooled stored routine plasma samples collected throughout the period of intensive steroid treatment or second-line GvHD therapy to identify weakly pathogenic, commensal and unexpected viruses.</p> <p><b>Results: </b>Median duration of intensive immunosuppression was 5.1 months (IQR 5.5).<b> </b>GvHD-related mortality rate was 36%.<b> </b>mNGS analysis detected viral nucleotide sequences in 24/25 patients. Sequences of ≥3 distinct viruses were detected in 16/25 patients, <i>Anelloviridae</i> (24/25) and human pegivirus-1 (9/25) were the most prevalent. In 7/25 patients with fatal outcomes, unexpected viral sequences, not assessed by routine investigations, were identified with mNGS and confirmed by RT-PCR. These cases included usutu virus (1), rubella virus (1 vaccine-strain and 1 wild-type), novel human astrovirus (HAstV) MLB2 (1), classic HAstV (1), human polyomavirus 6 and 7 (2), cutavirus (1), and bufavirus (1).</p> <p><b>Conclusions: </b>Unexpected, opportunistic and protracted viral infections were identified in 28% of highly immunocompromised allo-HSCT recipients with steroid refractory/dependent GvHD. These identified viruses have all been previously described in humans, but have poorly understood clinical significance. Rubella virus identification raises the possibility of re-emergence from past infections or vaccinations.</p>
Supplementary material 1 from: Snyder MR, Stepien CA (2020) Increasing confidence for discerning species and population compositions from metabarcoding assays of environmental samples: case studies of fishes in the Laurentian Great Lakes and Wabash River. Metabarcoding and Metagenomics 4: e53455. https://doi.org/10.3897/mbmg.4.53455
Supplementary material: Additional methods, results, figures, and tables
Supplementary material 2 from: Laini A, Beermann AJ, Bolpagni R, Burgazzi G, Elbrecht V, Zizka VMA, Leese F, Viaroli P (2020) Exploring the potential of metabarcoding to disentangle macroinvertebrate community dynamics in intermittent streams. Metabarcoding and Metagenomics 4: e51433. https://doi.org/10.3897/mbmg.4.51433
Table S1, Figures S1–S5
Supplementary material 1 from: Laini A, Beermann AJ, Bolpagni R, Burgazzi G, Elbrecht V, Zizka VMA, Leese F, Viaroli P (2020) Exploring the potential of metabarcoding to disentangle macroinvertebrate community dynamics in intermittent streams. Metabarcoding and Metagenomics 4: e51433. https://doi.org/10.3897/mbmg.4.51433
Raw data
Supplementary data (simulated metagenome set 1) to accompany "phyloFlash – Rapid SSU rRNA profiling and targeted assembly from metagenomes"
<p>Comparison of SSU rRNA read extraction and targeted assembly from simulated shotgun metagenome of divergent bacterial species.</p> <p>The phyloFlash software is available from https://github.com/HRGV/phyloFlash. Examples were generated with phyloFlash v3.3b.</p>
Supplementary data (comparison of multiple metagenomes) to accompany "phyloFlash – Rapid SSU rRNA profiling and targeted assembly from metagenomes"
<p>Usage example for phyloFlash, comparison of multiple metagenomes by SSU rRNA taxonomic profile. </p> <p>The phyloFlash software is available from https://github.com/HRGV/phyloFlash. Examples were generated with phyloFlash v3.3b.</p>
Supplementary data (low-diversity metagenome and reference database completeness) to accompany "phyloFlash – Rapid SSU rRNA profiling and targeted assembly from metagenomes"
<p>Comparison of phyloFlash and Matam on low-diversity platyhelminth metagenome, showing effect of reference database completeness on results. </p> <p>The phyloFlash software is available from https://github.com/HRGV/phyloFlash. Examples were generated with phyloFlash v3.3b.</p>
Supplementary data (Tara Oceans metagenomes) to accompany "phyloFlash – Rapid SSU rRNA profiling and targeted assembly from metagenomes"
<p>Comparison of SSU rRNA read extraction and targeted assembly by phyloFlash and Matam from environmental metagenomes from the Tara Oceans dataset.</p> <p>The phyloFlash software is available from https://github.com/HRGV/phyloFlash. Examples were generated with phyloFlash v3.3b.</p>
Supplementary material 1 from: Nugent CM, Adamowicz SJ (2020) Alignment-free classification of COI DNA barcode data with the Python package Alfie. Metabarcoding and Metagenomics 4: e55815. https://doi.org/10.3897/mbmg.4.55815
File S1 – Training, test, and validation data sets used in model training and analysis
Supplementary material 1 from: Macher J-N, Drakou K, Papatheodoulou A, Hoorn B, Vasquez M (2020) The mitochondrial genomes of 11 aquatic macroinvertebrate species from Cyprus. Metabarcoding and Metagenomics 4: e58259. https://doi.org/10.3897/mbmg.4.58259
Scripts used for Megahit and Spades assemly of mitochornial genomes and nuclear 18S and 28S rRNAs
Supplementary material 1 from: Di Muri C, Lawson Handley L, Bean CW, Li J, Peirson G, Sellers GS, Walsh K, Watson HV, Winfield IJ, Hänfling B (2020) Read counts from environmental DNA (eDNA) metabarcoding reflect fish abundance and biomass in drained ponds. Metabarcoding and Metagenomics 4: e56959. https://doi.org/10.3897/mbmg.4.56959
Table S1 and Figure S1
Supplementary material 2 from: Di Muri C, Lawson Handley L, Bean CW, Li J, Peirson G, Sellers GS, Walsh K, Watson HV, Winfield IJ, Hänfling B (2020) Read counts from environmental DNA (eDNA) metabarcoding reflect fish abundance and biomass in drained ponds. Metabarcoding and Metagenomics 4: e56959. https://doi.org/10.3897/mbmg.4.56959
Table S2. Fish taxonomic assignment metaBEAT
Supplementary material 3 from: Di Muri C, Lawson Handley L, Bean CW, Li J, Peirson G, Sellers GS, Walsh K, Watson HV, Winfield IJ, Hänfling B (2020) Read counts from environmental DNA (eDNA) metabarcoding reflect fish abundance and biomass in drained ponds. Metabarcoding and Metagenomics 4: e56959. https://doi.org/10.3897/mbmg.4.56959
Table S3. Unassigned blast 1.0
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.