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ShareScore release 0.9.0
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47 results for “metabarcoding analysis”
Network analysis with either Illumina or MinION reveals that detecting vertebrate species requires metabarcoding of iDNA from a diverse fly community
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Data from: Comparing the effectiveness of metagenomics and metabarcoding for diet analysis of a leaf-feeding monkey (Pygathrix nemaeus)
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Ecological specialization and niche overlap of subterranean rodents inferred from DNA metabarcoding diet analysis
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Data from: Evaluation of plant contamination in metabarcoding diet analysis of a herbivore
Fecal DNA metabarcoding is currently used in various fields of ecology to determine animal diets. Contamination of non-food DNA from complex field environments is a considerable challenge to the reliability of this method but has rarely been quantified. We evaluated plant DNA contamination by sequencing the chloroplast trnL P6 loop region from food-controlled geese feces. The average percentage of contaminant sequences per sample was 1.86%. According to the results of generalized linear models, the probability of contamination was highest in samples placed in wet soil. The proportion of contaminant sequences was lowest at the earliest sampling point and was slightly higher in samples placed in open conditions. Exclusion of rare OTUs (operational taxonomic units) was effective for obtaining reliable dietary data from the obtained sequences, and a 1% cutoff reduced the percentage of contaminated samples to less than 30%. However, appropriate interpretation of the barcoding results considering inevitable contamination is an important issue to address. We suggest the following procedures for fecal sampling and sequence data treatment to increase the reliability of DNA metabarcoding diet analyses: (i) Collect samples as soon as possible after deposition, (ii) avoid samples from deposits on wet soil, and (iii) exclude rare OTUs from diet composition estimations.
Figure 1 from: Anslan S, Nilsson RH, Wurzbacher C, Baldrian P, Tedersoo L, Bahram M (2018) Great differences in performance and outcome of high-throughput sequencing data analysis platforms for fungal metabarcoding. MycoKeys 39: 29-40. https://doi.org/10.3897/mycokeys.39.28109
Figure 1 - Outline of workflow in different analysis pipelines.
Data from: Evaluation of plant contamination in metabarcoding diet analysis of a herbivore
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R script ITS2 DNA metabarcoding stigma data and stats analysis
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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.