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11 results for “Qiime2”
Qiime2 classifiers (rbcl, Mollusc 18s) for testing the validity of using eDNA for carbon origin analysis from sediment cores
<p>Qiime2 formatted classifiers that were created for a Natural England funded project by researchers at the James Hutton Institute. The pilot project aims to test the validity of using eDNA for carbon origin analysis from sediment cores. These classifiers for the rbcl and 18 Mollusc genes were made using RESCRIPt and Qiime2. </p> <p>The scripts used to created these classifiers are available at the James Hutton ICS GitHub <a href="https://github.com/HuttonICS/blue-carbon-db">blue-carbon-db</a> . The files are as follows:</p> <p><a href="../api/records/10046481/draft/files/mollusc-espineira-classifier.qza/content" target="_blank" rel="noopener noreferrer">mollusc-espineira-classifier.qza</a> is a classifer built from ncbi 18s Mollusc sequences, trained on the primer set from Espiñeira et al (2009).</p> <div>rbcl-vasselon-zimmerman-F3-R1-classifier.qza is a classifer built from ncbi rbcl sequences, trained on the F3 and R1 primer set fromVasselon et al (2017).</div> <p> </p> <p> </p> <p><strong>Important: </strong>If you use these classifiers please be aware of the process used to create them and be sure to review the methods. These databases were created by downloading data from the NCBI in October 2023, sequence data available at the NCBI changes over time. To create the most up to date database a fresh download and re-evaluations of the databases would be preferable. All method and scripts can be found at <a href="https://github.com/HuttonICS/blue-carbon-db">blue-carbon-db </a></p> <p>If you use these database please reference this repository along with RESCRIPt and Qiime2 </p> <p> </p> <p>Espiñeira, M., González-Lavín, N., Vieites, J. M. and Santaclara, F. J. 2009 Development of a method for the genetic identification of commercial bivalve species based on mitochondrial 18S rRNA sequences. J Agric Food Chem, 28, 495-502 https://doi.org/10.1021/jf802787d</p> <p> </p> <p>Vasselon, V., Rimet, F., Tapolczai, K. and Bouchez, A. 2017. Assessing ecological status with diatoms DNA metabarcoding: Scaling-up on a WFD monitoring network (Mayotte island, France). Ecological Indicators, 82, 1-12 <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.ecolind.2017.06.024" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.ecolind.2017.06.024</a></p>
PRJNA860062 Assigned Taxonomy and QIIME2 Pipeline
<p><strong>PRJNA860062 Assigned Taxonomy:</strong></p> <p>This upload comprises two datasets with the assigned taxonomy for sequence variants of BioProject PRNJA860062.</p> <ul> <li>PRJNA860062_ASVCounts_NCBItaxonomy.txt</li> <li>PRJNA860062_ASVCounts_SILVAtaxonomy.txt</li> </ul> <p>BioProject PRNJN860062 compares bacterial profiles of zebrafish larvae microbiota resulting from two different microbial colonization methods. The full description and sequence data for this project can be obtained from the Sequence Read Archive (<a href="https://www.ncbi.nlm.nih.gov/bioproject">https://www.ncbi.nlm.nih.gov/bioproject</a>). </p> <p>The dataset with the SILVA taxonomy can directly be obtained using the QIIME2 script included in this upload ('PRJNA860062_QIIME2Script.txt'). As previously noted by Lesack and Birol (2018), SILVA species annotations include nomenclature errors (<a href="https://doi.org/10.1101/441576">DOI: 10.1101/441576</a>). Therefore, the dataset with the NCBI taxonomy comprises a manually corrected taxonomy for BioProject PRNJA860062, based on the family to phylum level nomenclature of the NCBI taxonomy browser (<a href="https://www.ncbi.nlm.nih.gov/taxonomy">https://www.ncbi.nlm.nih.gov/taxonomy</a>).</p> <p>Both files are tab-delimited text files, include the domain to species level taxonomy in the first 7 columns, and include the number of assigned sequence variants (ASVs) per taxon in the final 6 colums, corresponding to BioSample SAMN29820940, SAMN29820941, SAMN29820942, SAMN29820943, SAMN29820944, and SAMN29820945.</p> <p> </p> <p><strong>QIIME 2 Pipeline:</strong></p> <p>The QIIME2 script that was used to obtain the assigned SILVA taxonomy BioProject PRNJA860062 is uploaded as:</p> <ul> <li>PRJNA860062_QIIME2Script.txt</li> </ul> <p>Input files that are required to run this script, including a manifest text file, sample metadata, and the reference sequences and taxonomy from the SILVA 138 small subunit (16S/18S) rRNA database Ref NR 99, are uploaded in the zipped file:</p> <ul> <li>PRJNA860062_InputFiles.zip</li> </ul> <p>FASTQ sequence data for BioSample SAMN29820940, SAMN29820941, SAMN29820942, SAMN29820943, SAMN29820944, and SAMN29820945, can be obtained from the Sequence Read Archive under BioProject PRNJA860062 (<a href="https://www.ncbi.nlm.nih.gov/bioproject">https://www.ncbi.nlm.nih.gov/bioproject</a>).</p> <p>All output files are uploaded in the zipped file:</p> <ul> <li>PRJNA860062_OutputFiles.zip</li> </ul> <p>Data provenance, including the versions of python (3.6.7) and python packages, can be acquired by dragging QIIME2 Visualizations (.qzv output files) into the QIIME2 viewing interface (<a href="http://view.qiime2.org">http://view.qiime2.org</a>).</p>
Introduction to Metabarcoding using QIIME2 - Echidna Dataset
<p>This is the data and associated metadata file for the Melbourne Bioinformatics workshop (https://mdhs.unimelb.edu.au/melbournebioinformatics/teaching-and-training), Introduction to Metabarcoding using QIIME2 - Mammal Dataset. There are 38 samples in this dataset from the short-beaked echidna <a href="https://en.wikipedia.org/wiki/Short-beaked_echidna"><i>Tachyglossus aculeatus. </i></a></p><ol><li>5 samples from each individual (3x male and 3x female).</li><li>8 control samples (DNA extraction blanks (n=5) and PCR blanks (n=3))</li></ol>
The demo data set for the meta16S-Seq workflow using Qiime2
<p>The demo data used in the introduction of meta16S-Seq workflow using Qiime2. The original manuscript of the workflow introduction is written by Yuh Shiwa. The workflow is translated in Common Workflow Language by Tazro Ohta.</p>
Práctica Metagenómica: Tutorial de microbiomas usando QIIME2 / Practical Metagenomics: Microbiome tutorial with QIIME 2
<p>Data for the e-learning tutorial Práctica Metagenómica: Tutorial de microbiomas usando QIIME2 </p> <p>Datos para el tutorial e-learning <a href="https://f1000research.com/documents/10-798">Practical Metagenomics: Microbiome tutorial with QIIME 2</a></p> <p> </p>
Metabarcoding data package for QIIME2 workshop
<p>Raw data files and intermediate results of the feature tabulation and taxonomic classification of amplicon sequences using QIIME2. This data package is used during the Metabarcoding analyses using QIIME2 workshop, which is part of the 2021 Amsterdam Science Park Study Group summer school. The complete workflow is detailed in this tutorial: https://ejongepier.github.io/metabarcoding-qiime2-workshop/genintro.html.</p>
Qiime2 classifiers
<p>These files are companion classifiers for QIIME2 snakemake pipeline.</p> <p> </p> <p>If you use these data files please cite:</p> <ul> <li> <p>Michael S Robeson II, Devon R O’Rourke, Benjamin D Kaehler, Michal Ziemski, Matthew R Dillon, Jeffrey T Foster, Nicholas A Bokulich. RESCRIPt: Reproducible sequence taxonomy reference database management for the masses. bioRxiv 2020.10.05.326504; doi: <a href="https://doi.org/10.1101/2020.10.05.326504">https://doi.org/10.1101/2020.10.05.326504</a></p> </li> <li> <p>Bokulich, N.A., Kaehler, B.D., Rideout, J.R. et al. Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome 6, 90 (2018). <a href="https://doi.org/10.1186/s40168-018-0470-z">https://doi.org/10.1186/s40168-018-0470-z</a></p> </li> <li> <p>See the <a href="https://www.arb-silva.de/">SILVA website</a> and the latest <a href="https://www.nature.com/articles/ismej2011139">Greengenes publication</a> for the latest citation information for these reference databases.</p> </li> <li> <p>We will update this information later.</p> </li> </ul>
QIIME2 2.0.5 feauture-classifier tutorial data
<p>Data for the QIIME2 2.0.5 feature-classifier tutorial.</p> <p>Some data reproduced from here: http://qiime.org/home_static/dataFiles.html</p>
qiime2
Open the record for dataset details and reuse information.
An Open-Source QIIME2 and R Pipeline for Multi-Amplicon 16S rRNA Profiling: Validation and Application in Pediatric Microbiome Studies
GEO Series GSE300047. unidentified. 119 samples. Type: Other.
QIIME2 Workflow
<p>QIIME2 1.0 Workflow for FCAV Project.</p>
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