Relevant bibliographies by topics / QIIME 2

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'QIIME 2'

Author: Grafiati
Published: 8 June 2021
Last updated: 29 July 2025

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Journal articles on the topic "QIIME 2"

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Keefe, Christopher R., Matthew R. Dillon, Elizabeth Gehret, et al. "Facilitating bioinformatics reproducibility with QIIME 2 provenance Replay." PLOS Computational Biology 19, no. 11 (2023): e1011676. http://dx.doi.org/10.1371/journal.pcbi.1011676.

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Study reproducibility is essential to corroborate, build on, and learn from the results of scientific research but is notoriously challenging in bioinformatics, which often involves large data sets and complex analytic workflows involving many different tools. Additionally, many biologists are not trained in how to effectively record their bioinformatics analysis steps to ensure reproducibility, so critical information is often missing. Software tools used in bioinformatics can automate provenance tracking of the results they generate, removing most barriers to bioinformatics reproducibility.
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Bolyen, Evan, Jai Ram Rideout, Matthew R. Dillon, et al. "Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2." Nature Biotechnology 37, no. 8 (2019): 852–57. http://dx.doi.org/10.1038/s41587-019-0209-9.

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3

Raspet, Isaiah, Elizabeth Gehret, Chloe Herman, et al. "Facilitating bootstrapped and rarefaction-based microbiome diversity analysis with q2-boots." F1000Research 14 (January 15, 2025): 87. https://doi.org/10.12688/f1000research.156295.1.

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Background We present q2-boots, a QIIME 2 plugin that facilitates bootstrapped and rarefaction-based microbiome diversity analysis. This plugin provides eight new actions that allow users to apply any of thirty different alpha diversity metrics and twenty-two beta diversity metrics to bootstrapped or rarefied feature tables, using a single QIIME 2 Pipeline command, or more granular QIIME 2 Action commands. Results Given a feature table, an even sampling depth, and the number of iterations to perform (n), the command qiime boots core-metrics will resample the feature table n times and compute a
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Bolyen, Evan, Jai Ram Rideout, Matthew R. Dillon, et al. "Author Correction: Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2." Nature Biotechnology 37, no. 9 (2019): 1091. http://dx.doi.org/10.1038/s41587-019-0252-6.

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Bolyen, Evan, Matthew R. Dillon, Nicholas A. Bokulich, et al. "Reproducibly sampling SARS-CoV-2 genomes across time, geography, and viral diversity." F1000Research 9 (June 29, 2020): 657. http://dx.doi.org/10.12688/f1000research.24751.1.

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The COVID-19 pandemic has led to a rapid accumulation of SARS-CoV-2 genomes, enabling genomic epidemiology on local and global scales. Collections of genomes from resources such as GISAID must be subsampled to enable computationally feasible phylogenetic and other analyses. We present genome-sampler, a software package that supports sampling collections of viral genomes across multiple axes including time of genome isolation, location of genome isolation, and viral diversity. The software is modular in design so that these or future sampling approaches can be applied independently and combined
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Bolyen, Evan, Matthew R. Dillon, Nicholas A. Bokulich, et al. "Reproducibly sampling SARS-CoV-2 genomes across time, geography, and viral diversity." F1000Research 9 (October 28, 2020): 657. http://dx.doi.org/10.12688/f1000research.24751.2.

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The COVID-19 pandemic has led to a rapid accumulation of SARS-CoV-2 genomes, enabling genomic epidemiology on local and global scales. Collections of genomes from resources such as GISAID must be subsampled to enable computationally feasible phylogenetic and other analyses. We present genome-sampler, a software package that supports sampling collections of viral genomes across multiple axes including time of genome isolation, location of genome isolation, and viral diversity. The software is modular in design so that these or future sampling approaches can be applied independently and combined
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7

Shah, Manasi S., Todd Z. DeSantis, Thomas Weinmaier, et al. "Leveraging sequence-based faecal microbial community survey data to identify a composite biomarker for colorectal cancer." Gut 67, no. 5 (2017): 882–91. http://dx.doi.org/10.1136/gutjnl-2016-313189.

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ObjectiveColorectal cancer (CRC) is the second leading cause of cancer-associated mortality in the USA. The faecal microbiome may provide non-invasive biomarkers of CRC and indicate transition in the adenoma–carcinoma sequence. Re-analysing raw sequence and metadata from several studies uniformly, we sought to identify a composite and generalisable microbial marker for CRC.DesignRaw 16S rRNA gene sequence data sets from nine studies were processed with two pipelines, (1) QIIME closed reference (QIIME-CR) or (2) a strain-specific method herein termed SS-UP (Strain Select, UPARSE bioinformatics
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8

Zhao, Jingcheng, Yunhui Qi, Peng Liu, et al. "Prebiotic Effects of a Cranberry Beverage in a Randomized, Placebo-Controlled, Crossover Clinical Trial." Current Developments in Nutrition 5, Supplement_2 (2021): 1190. http://dx.doi.org/10.1093/cdn/nzab054_045.

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Abstract Objectives The objective was to evaluate the prebiotic effects of a milled whole cranberry beverage on modulating the gut microbiota in young adults. Methods Adults (n = 17; ages 18–42 y; BMI 30.5 ± 3.1 kg/m2) were enrolled in a 60-d, two-period, randomized, placebo-controlled, crossover clinical study. Throughout the study, participants were fed a standardized 10-d cycle menu on site. During each 20-d treatment period, participants consumed twice daily a whole cranberry or placebo beverage (240 mL per serving). Treatment periods were separated by an 11-wk washout period and preceded
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Heidrich, Vitor, Petr Karlovsky, and Lukas Beule. "‘SRS’ R Package and ‘q2-srs’ QIIME 2 Plugin: Normalization of Microbiome Data Using Scaling with Ranked Subsampling (SRS)." Applied Sciences 11, no. 23 (2021): 11473. http://dx.doi.org/10.3390/app112311473.

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Several ecological data types, especially microbiome count data, are commonly sample-wise normalized before analysis to correct for sampling bias and other technical artifacts. Recently, we developed an algorithm for the normalization of ecological count data called ‘scaling with ranked subsampling (SRS)’, which surpasses the widely adopted ‘rarefying’ (random subsampling without replacement) in reproducibility and in safeguarding the original community structure. Here, we describe an implementation of the SRS algorithm in the ‘SRS’ R package and the ‘q2-srs’ QIIME 2 plugin. We also provide ac
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10

Rivers, Adam R., Kyle C. Weber, Terrence G. Gardner, Shuang Liu, and Shalamar D. Armstrong. "ITSxpress: Software to rapidly trim internally transcribed spacer sequences with quality scores for marker gene analysis." F1000Research 7 (September 6, 2018): 1418. http://dx.doi.org/10.12688/f1000research.15704.1.

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The internally transcribed spacer (ITS) region between the small subunit ribosomal RNA gene and large subunit ribosomal RNA gene is a widely used phylogenetic marker for fungi and other taxa. The eukaryotic ITS contains the conserved 5.8S rRNA and is divided into the ITS1 and ITS2 hypervariable regions. These regions are variable in length and are amplified using primers complementary to the conserved regions of their flanking genes. Previous work has shown that removing the conserved regions results in more accurate taxonomic classification. An existing software program, ITSx, is capable of t
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Dissertations / Theses on the topic "QIIME 2"

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Filomena, João Pedro Fernandes Lourenço da. "Adaptation of genoqual pipeline to new upstream applications and to run independently from galaxy portal." Master's thesis, 2021. http://hdl.handle.net/10400.26/36701.

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O presente estágio foi realizado no Instituto Gulbenkian de Ciência (IGC) no âmbito do mestrado em engenharia biológica e química. O estagiário esteve envolvido com termos e ferramentas usadas em bioinformática, metagenómica e NGS. A principal tarefa do estagiário focou-se na atualização de uma pipeline de análises genómicas feito pelo IGC designado por “GenoQual”. O principal objetivo do estágio do discente focou-se na atualização de uma pipeline de análises genómicas feito pelo IGC, há vários anos, designado por “GenoQual”. Desde a última atualização do GenoQual, tem havido uma
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Books on the topic "QIIME 2"

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Bioinformatic and Statistical Analysis of Microbiome Data: From Raw Sequences to Advanced Modeling with QIIME 2 and R. Springer International Publishing AG, 2024.

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2

Sun, Jun, and Yinglin Xia. Bioinformatic and Statistical Analysis of Microbiome Data: From Raw Sequences to Advanced Modeling with QIIME 2 and R. Springer International Publishing AG, 2023.

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Book chapters on the topic "QIIME 2"

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Xia, Yinglin, and Jun Sun. "Introduction to QIIME 2." In Bioinformatic and Statistical Analysis of Microbiome Data. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-21391-5_1.

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Xia, Yinglin, and Jun Sun. "Basic Data Processing in QIIME 2." In Bioinformatic and Statistical Analysis of Microbiome Data. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-21391-5_3.

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Conference papers on the topic "QIIME 2"

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Varela-Villegas, Emmanuel, Daniel López-Juárez, and Rebeca Campos-Sánchez. "Characterization of QIIME 2 with Intel Technology on-premises and in Microsoft Azure Cloud." In 2023 IEEE 5th International Conference on BioInspired Processing (BIP). IEEE, 2023. http://dx.doi.org/10.1109/bip60195.2023.10379373.

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Lima, Isadora Soares de, Tiago Palladino Delforno, and Iolanda Cristina Silveira Duarte. "ANÁLISE IN SILICO PARA DEFINIÇÃO DE COMMON CORE MICROBIANO ASSOCIADO À DEGRADAÇÃO DE SURFACTANTE ANIÔNICO ALQUILBENZENO LINEAR SULFONADO (LAS)." In II Congresso Brasileiro de Biologia Molecular On-line. Revista Multidisciplinar em Saúde, 2021. http://dx.doi.org/10.51161/rems/2314.

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Introdução: O alquilbenzeno linear sulfonado é o surfactante aniônico de maior interesse econômico, correspondendo a 84% do mercado no Brasil, e 45% no mundo. Sua rota de biodegradação envolve reações de adição de fumarato, β-oxidação, clivagem do anel aromático e dessulfonação. Tratando-se de um processo complexo, o uso de consórcios microbianos possibilita usufruir de diferentes metabolismos para a degradação do LAS. Contudo, nota-se uma escassez na literatura acerca dos microrganismos que desempenham papel fundamental na degradação do surfactante em reatores biológicos. Portanto, o presente
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