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1,076
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1,076 results for “Metabarcoding”
Data from: Veronica officinalis product authentication using DNA metabarcoding and HPLC-MS reveals widespread adulteration with Veronica chamaedrys
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Data from: Combined use of eDNA metabarcoding and video surveillance for the assessment of fish biodiversity
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Data from: Evaluating NGS methods for routine monitoring of wild bees: metabarcoding, mitogenomics or NGS barcoding
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A comprehensive and comparative evaluation of primers for metabarcoding eDNA from fish
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Data from: Evaluation of plant contamination in metabarcoding diet analysis of a herbivore
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16S metabarcoding, a powerful tool to compare environmental and culture-derived bacterial communities, assess media selectivity and detect rare environmental bacterial species
<p>Processed raw data reads</p>
Raw data for: Identifying archived insect bulk samples using DNA metabarcoding: A case study using the long-term Rothamsted Insect Survey
<p>These are the raw files from the Illumina MiSeq for the 12 libraries sequenced.</p>
eDNAglobe: investigating global organism distribution via environmental DNA metabarcoding data
<p>Data generated for eDNAglobe, and codes used to generate the data</p>
Tara Pacific metabarcoding sequencing (16S, 18S, ITS2) reference & replication tables version 1
<p>The tables in this dataset associate metabarcoding sequencing files generated by Genoscope (i.e. fastq.gz files with informative filename structures; with sequencing file pairs associated to unique 'readset' identifiers; housed on their FTP server at www.genoscope.cns.fr/sadc/tarapacific/METABARCODING; with the 'METAB' sequence strategy identifier as part of the sequencing file name) with their associated 'sample-id_source' identifier; as detailed in the 'TARA-PACIFIC_samples-provenance' file part of the 'Tara Pacific samples provenance and environmental context' Zenodo publication (DOI: 10.5281/zenodo.4068292) part of the 'tarapacific' Zenodo community). The main purpose of these tables is to act as a reference to identify samples (i.e., with a single 'sample-id_source') for which sequencing replication exists, per primer set (i.e., more than one set of fastq.gz sequencing files were generated, pre primer set). In the case of replication, these tables classify the replication into three classes color coded as green (same DNA extraction, same PCR, same sequencing run, different sequencing lane), yellow (same DNA extraction, same PCR, different sequencing run) and red (different DNA extraction and/or different PCR). It should be noted that in the vast majority of cases a 'sample-id_source' associates to only one readset per primer set. For a full description of the dataset, please see the included README.</p>
R code and datasets for ITS2 DNA metabarcoding stigma sequence data
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R script ITS2 DNA metabarcoding stigma data and stats analysis
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Pollen metabarcoding 2020 Data per bee species and plot
<p>Pollen identified through metabarcoding from neeting bees 2020</p>
Priority list of plant collection from metabarcoding 2020 and visitation records
<p>Priority list for plant collection, priorities based on number of reeds in metabarcoding and number of bees encountered in visitation records. </p>
ITS2 stigma metabarcoding sequence processing
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Single cell rDNA 16S V4V5 and 18S V9 metabarcoding tables (dada2) from the Tara Oceans expedition (2009-2013)
<p>Single cell rDNA 16S V4V5 and 18S V9 metabarcoding tables (dada2) from the Tara Oceans expedition (2009-2013). The code to generate the ASV tables is here: https://gitlab.com/tara-and-friends-euk-metab/tara-single-cell-metab</p>
Re-evaluating the genetic variation of the COI gene of Insecta: Implications for DNA barcoding, metabarcoding and species delimitation studies
<p>To analyze the genetic variation of the <i>cytochrome c oxidase subunit I</i> (<i>COI</i>) gene of Insecta, the <i>COI</i> data of Insecta was downloaded from GenBank and the intraspecific Kimura-2 -parameter (K2P) distance of 40,782 species was calculated (each species with three or more sequences). Our result indicated that the maximum intraspecific genetic distance of 8,928 (21.89%) species was over 3%. Using a threshold of 3% in the clustering analysis, 7,123 (17.47%) species can be divided into two or more clusters. We also analyzed 3,189 genera with over three species (25,283 species) and found that the optimal thresholds for these genera ranged from 0.1%-15.7% (average value: 0.03531, median value: 0.02900). In clustering analysis, if the threshold values were set to 0.01, 0.02, 0.022, and 0.03, the numbers of clusters were 39,860, 31,024, 29,954, and 26,527, respectively. In metabarcoding studies, a threshold of 0.03 was recommended to estimate the species diversity of insects in a certain environment. However, using the empirical thresholds mentioned above for operational taxonomic unit (OTU) picking, the average match ratios of the 3,189 genera were 0.5137, 0.6338, 0.6440, and 0.6587. By contrast, if the possible thresholds from the distance matrix, the minimum interspecific genetic distance of congeneric species, and the optimal thresholds were used in clustering analysis, the average match ratios of them were 0.6626 0.7530, and 0.7549. Herein, we recommended the utilizations of the minimum interspecific genetic distance (when it was greater than or equal to 2%) and the optimal thresholds for OTU picking in DNA barcoding and species delimitation studies based on the <i>COI</i> gene of insects.</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.
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DANDI Archive for NWB datasets
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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.