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Dataset results
17 results for “16S metagenomics”
Example 16S Metagenomics Dataset
<p>This is a 16S Metagenomics example dataset obtained by transforming data originally from Batista et al. (2015). It consists of data corresponding to 2 conditions (WT untreated and WT after Streptomycin treatment) with 5 replicates each, where exactly 10000 reads were obtained from the original forward raw reads of each sample. This dataset includes a metadata file, sequencing reads as well as the greengenes reference dataset, which is given here for convenience and reproducibility.</p>
Training datasets for 16S Metagenomics analysis with FROGS
<p>This training dataset is from 2 imaginary microbiome samples. Each one is from a paired end 16S amplicon sequencing run and contains 2 fastq files (forwards and reverse.)</p> <p>It is a useful dataset for demonstrating:</p> <ul> <li>16S metagenomics analysis techniques</li> <li>Differences between microbiome samples</li> </ul>
Comparative seagulls of gut microbiota by using metagenomics and 16S rDNA sequencing
<p><span>Shotgun</span><span> metagenomic and 16S rDNA sequencing are commonly used methods to identify the taxonomic composition of microbial communities. </span><span>We compared the metagenome and 16S rDNA amplicon results to demonstrate the features of this animal. </span><span>In general, </span><span>relatively </span><span>consistent patterns and reliability could be identified by both sequencing methods, but the results varied </span><span>following </span><span>the refinement of taxonomic levels. </span><span>Metagenomic </span><span>sequencing was more suitable for the discovery and detection of pathogenic bacteria of gut microbiota in seagulls.</span><span> Although there were large differences in the numbers and abundance of </span><span>bacterial </span><span>species of</span><span> the</span><span> two methods in terms of taxonomic levels, the patterns and reliability results of </span><span>the </span><span>samples were consistent.</span></p>
Comparative seagulls of gut microbiota by using metagenomics and 16S rDNA sequencing
Open the record for dataset details and reuse information.
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>
Metagenomics 16S data
<p>from Igor Makunin. </p>
Data from: A comparison between transcriptome sequencing and 16S metagenomics for detection of bacterial pathogens in wildlife
Open the record for dataset details and reuse information.
NGS amplicon metagenomic 16S seq of soybean rhizosphere under contrasting nutrient-deficient and acidic-stress soils
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Supplementary material 1 from: Sogawa S, Tsuchiya K, Nagai S, Shimode S, Kuwahara VS (2022) Annual dynamics of eukaryotic and bacterial communities revealed by 18S and 16S rRNA metabarcoding in the coastal ecosystem of Sagami Bay, Japan. Metabarcoding and Metagenomics 6: e78181. https://doi.org/10.3897/mbmg.6.78181
Figures S1–S8
Supplementary material 4 from: Hintikka S, Carlsson JE, Carlsson J (2022) The bacterial hitchhiker's guide to COI: Universal primer-based COI capture probes fail to exclude bacterial DNA, but 16S capture leaves metazoa behind. Metabarcoding and Metagenomics 6: e80416. https://doi.org/10.3897/mbmg.6.80416
COI library ASV tax
Supplementary material 1 from: Hintikka S, Carlsson JE, Carlsson J (2022) The bacterial hitchhiker's guide to COI: Universal primer-based COI capture probes fail to exclude bacterial DNA, but 16S capture leaves metazoa behind. Metabarcoding and Metagenomics 6: e80416. https://doi.org/10.3897/mbmg.6.80416
File S1
Supplementary material 3 from: Hintikka S, Carlsson JE, Carlsson J (2022) The bacterial hitchhiker's guide to COI: Universal primer-based COI capture probes fail to exclude bacterial DNA, but 16S capture leaves metazoa behind. Metabarcoding and Metagenomics 6: e80416. https://doi.org/10.3897/mbmg.6.80416
16S library ASV tax
Supplementary material 5 from: Hintikka S, Carlsson JE, Carlsson J (2022) The bacterial hitchhiker's guide to COI: Universal primer-based COI capture probes fail to exclude bacterial DNA, but 16S capture leaves metazoa behind. Metabarcoding and Metagenomics 6: e80416. https://doi.org/10.3897/mbmg.6.80416
Unassigned COIASVs krona
Supplementary material 2 from: Hintikka S, Carlsson JE, Carlsson J (2022) The bacterial hitchhiker's guide to COI: Universal primer-based COI capture probes fail to exclude bacterial DNA, but 16S capture leaves metazoa behind. Metabarcoding and Metagenomics 6: e80416. https://doi.org/10.3897/mbmg.6.80416
Metadata all
Study of the Composition and Bacterial Diversity of the Vaginal Microbiota in Healthy Versus Pathological Conditions (Bacterial Vaginosis) Using a Targeted Metagenomic Approach (RNA 16s)
ClinicalTrials.gov study NCT04989543. IPD Sharing: NO. Countries: 1. Publications: 0.
Microbial Profiling in Pockets Related to Chronic Periodontitis Patients Using 16s RNA Metagenomics Sequencing
ClinicalTrials.gov study NCT04425343. IPD Sharing: NO. Countries: 1. Publications: 0.
Metagenomic sequencing and 16S rRNA sequence of gut microbiota associated with autism spectrum disorders patients
GEO Series GSE113701. feces metagenome. 346 samples. Type: Other.
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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.
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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.