QIIME 2: Reproducible, interactive, scalable, and extensible microbiome data science

We present QIIME 2, an open-source microbiome data science platform accessible to users spanning the microbiome research ecosystem, from scientists and engineers to clinicians and policy makers. QIIME 2 provides new features that will drive the next generation of microbiome research. These include interactive spatial and temporal analysis and visualization tools, support for metabolomics and shotgun metagenomics analysis, and automated data provenance tracking to ensure reproducible, transparent microbiome data science.

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QIIME 2: Reproducible, interactive, scalable, and extensible microbiome data science

10.7287/peerj.preprints.27295 ◽

2018 ◽

Cited By ~ 23

Author(s):

Evan Bolyen ◽

Jai Ram Rideout ◽

Matthew R Dillon ◽

Nicholas A Bokulich ◽

Christian Abnet ◽

...

Keyword(s):

Data Science ◽

Temporal Analysis ◽

Data Provenance ◽

Policy Makers ◽

Shotgun Metagenomics ◽

Spatial And Temporal Analysis ◽

Microbiome Research ◽

Scientists And Engineers ◽

Visualization Tools ◽

Microbiome Data

We present QIIME 2, an open-source microbiome data science platform accessible to users spanning the microbiome research ecosystem, from scientists and engineers to clinicians and policy makers. QIIME 2 provides new features that will drive the next generation of microbiome research. These include interactive spatial and temporal analysis and visualization tools, support for metabolomics and shotgun metagenomics analysis, and automated data provenance tracking to ensure reproducible, transparent microbiome data science.

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SKIOME Project: a curated collection of skin microbiome datasets enriched with study-related metadata

10.1101/2021.08.17.456635 ◽

2021 ◽

Author(s):

Giulia Agostinetto ◽

Davide Bozzi ◽

Danilo Porro ◽

Maurizio Casiraghi ◽

Massimo Labra ◽

...

Keyword(s):

Data Science ◽

Data Retrieval ◽

Amplicon Sequencing ◽

Full Potential ◽

Skin Microbiome ◽

Data Accessibility ◽

16S Rrna Amplicon Sequencing ◽

Comprehensive Collection ◽

Microbiome Research ◽

Microbiome Data

Large amounts of data from microbiome-related studies have been (and are currently being) deposited on international public databases. These datasets represent a valuable resource for the microbiome research community and could serve future researchers interested in integrating multiple datasets into powerful meta-analyses. However, this huge amount of data lacks harmonization and is far from being completely exploited in its full potential to build a foundation that places microbiome research at the nexus of many subdisciplines within and beyond biology. Thus, urges the need for data accessibility and reusability, according to FAIR (Findable, Accessible, Interoperable, and Reusable) principles, as supported by National Microbiome Data Collaborative and FAIR Microbiome. To tackle the challenge of accelerating discovery and advances in skin microbiome research, we collected, integrated and organized existing microbiome data resources from human skin 16S rRNA amplicon sequencing experiments. We generated a comprehensive collection of datasets, enriched in metadata, and organized this information into data frames ready to be integrated into microbiome research projects and advanced post-processing analysis, such as data science applications (e.g. machine learning). Furthermore, we have created a data retrieval and curation framework built on three different stages to maximize the retrieval of datasets and metadata associated with them. Lastly, we highlighted some caveats regarding metadata retrieval and suggested ways to improve future metadata submissions. Overall, our work resulted in a curated skin microbiome datasets collection accompanied by a state-of-the-art analysis of the last 10 years of the skin microbiome field.

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Uncovering host-microbiome interactions in global systems with collaborative programming: a novel approach integrating social and data sciences

F1000Research ◽

10.12688/f1000research.26459.1 ◽

2020 ◽

Vol 9 ◽

pp. 1478

Author(s):

Jenna Oberstaller ◽

Swamy Rakesh Adapa ◽

Guy W. Dayhoff II ◽

Justin Gibbons ◽

Thomas E. Keller ◽

...

Keyword(s):

Data Science ◽

South Florida ◽

Technological Advancement ◽

Real World Data ◽

Domain Experts ◽

Novel Approach ◽

Microbiome Research ◽

Data Output ◽

Microbiome Data ◽

Global Systems

Microbiome data are undergoing exponential growth powered by rapid technological advancement. As the scope and depth of microbiome research increases, cross-disciplinary research is urgently needed for interpreting and harnessing the unprecedented data output. However, conventional research settings pose challenges to much-needed interdisciplinary research efforts due to barriers in scientific terminologies, methodology and research-culture. To breach these barriers, our University of South Florida OneHealth Codeathon was designed to be an interactive, hands-on event that solves real-world data problems. The format brought together students, postdocs, faculty, researchers, and clinicians in a uniquely cross-disciplinary, team-focused setting. Teams were formed to encourage equitable distribution of diverse domain-experts and proficient programmers, with beginners to experts on each team. To unify the intellectual framework, we set the focus on the topics of microbiome interactions at different scales from clinical to environmental sciences, leveraging local expertise in the fields of genetics, genomics, clinical data, and social and geospatial sciences. As a result, teams developed working methods and pipelines to face major challenges in current microbiome research, including data integration, experimental power calculations, geospatial mapping, and machine-learning classifiers. This broad, transdisciplinary and efficient workflow will be an example for future workshops to deliver useful data-science products.

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A primer and discussion on DNA-based microbiome data and related bioinformatics analyses

10.31219/osf.io/3dybg ◽

2021 ◽

Author(s):

Gavin Douglas ◽

Morgan G. I. Langille

Keyword(s):

Marker Gene ◽

Research Area ◽

Sequencing Data ◽

Data Types ◽

Bioinformatics Analyses ◽

Shotgun Metagenomics ◽

The Past ◽

Microbiome Research ◽

The Many ◽

Microbiome Data

The past decade has seen an eruption of interest in profiling microbiomes through DNA sequencing. The resulting investigations have revealed myriad insights and attracted an influx of researchers to the research area. Many newcomers are in need of primers on the fundamentals of microbiome sequencing data types and the methods used to analyze them. Accordingly, here we aim to provide a detailed, but accessible, introduction to these topics. We first present the background on marker-gene and shotgun metagenomics sequencing and then discuss unique characteristics of microbiome data in general. We highlight several important caveats resulting from these characteristics that should be appreciated when analyzing these data. We then introduce the many-faceted concept of microbial functions and several controversies in this area. One controversy in particular is regarding whether metagenome prediction methods (i.e. based on marker gene sequences) are sufficiently accurate to ensure reliable biological inferences. We next highlight several underappreciated developments regarding the integration of taxonomic and functional data types. This is a highly pertinent topic because although these data types are inherently connected, they are often analyzed independently and primarily only linked anecdotally in the literature. We close by providing our perspective on this topic in addition to the issue of reproducibility in microbiome research, which are both crucial data analysis challenges facing microbiome researchers.

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O tym, co minęło, lecz nie zostało zapomniane: Badania archeologiczne na terenie byłego obozu zagłady w Treblince

Zagłada Żydów. Studia i Materiały ◽

10.32927/zzsim.628 ◽

2012 ◽

pp. 83-118

Author(s):

Caroline Sturdy Colls

Keyword(s):

Temporal Analysis ◽

Archaeological Survey ◽

Mass Graves ◽

Non Invasive ◽

Physical Evidence ◽

Spatial And Temporal Analysis ◽

The Holocaust ◽

Public Consciousness ◽

Level Of Knowledge ◽

Answering Questions

Public impression of the Holocaust is unquestionably centred on knowledge about, and the image of, Auschwitz-Birkenau – the gas chambers, the crematoria, the systematic and industrialized killing of victims. Conversely, knowledge of the former extermination camp at Treblinka, which stands in stark contrast in terms of the visible evidence that survives pertaining to it, is less embedded in general public consciousness. As this paper argues, the contrasting level of knowledge about Auschwitz- Birkenau and Treblinka is centred upon the belief that physical evidence of the camps only survives when it is visible and above-ground. The perception of Treblinka as having been “destroyed” by the Nazis, and the belief that the bodies of all of the victims were cremated without trace, has resulted in a lack of investigation aimed at answering questions about the extent and nature of the camp, and the locations of mass graves and cremation pits. This paper discusses the evidence that demonstrates that traces of the camp do survive. It outlines how archival research and non-invasive archaeological survey has been used to re-evaluate the physical evidence pertaining to Treblinka in a way that respects Jewish Halacha Law. As well as facilitating spatial and temporal analysis of the former extermination camp, this survey has also revealed information about the cultural memory.

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DRAINAGE BASIN AS A COMPLEX SOCIO-NATURAL HIERARCHICAL SYSTEM

THE LIFE OF THE EARTH ◽

10.29003/m1483.0514-7468.2020_42_3/293-303 ◽

2020 ◽

Vol 42 (3) ◽

pp. 293-303

Author(s):

VALERIY BONDAREV

Keyword(s):

Drainage Basin ◽

Temporal Analysis ◽

Large River ◽

Hierarchical Level ◽

Effective Management ◽

Drainage Basins ◽

Time Intervals ◽

Natural Systems ◽

Spatial And Temporal Analysis ◽

Entire Complex

The theoretical and methodological basis of the systems hierarchical spatial and temporal analysis of a drainage basin, which addresses the problems of effective management in socio-natural systems of different ranks, is considered. It is proposed to distinguish 9 orders of forms that are relevant to the analysis of drainage basins, where the first level is represented by individual aggregates and particles, and the last - by basins of large and the largest rivers. As part of the allocation of geological, historical and modern time intervals, the specificity of the implementation of processes in basins of different scales from changing states, through functioning to evolution is demonstrated. The interrelation of conditions and factors that determine the processes occurring within the drainage basins is revealed. It is shown that a specific combination of conditions and factors that determine processes in the drainage basin is associated with the hierarchy of the objects under consideration, i.e. the choice of a spatial-temporal hierarchical level is crucial for the organization of study within drainage basins. At one hierarchical level, some phenomenon can be considered as a factor, and at another - as a condition. For example, tectonic processes can be considered as an active factor in the evolution of large river basins in the geological perspective, but for small drainage basin, this is already a conservative background condition. It is shown that at the historical time the anthropogenic factor often comes to the fore, with the appearance of which in the functioning of the drainage basin, there is a need to take into account the entire complex of socio-environmental problems that can affect the sustainable state of various territories, especially in the field of water and land use. Hierarchical levels of managing subjects are identified, which are primarily responsible for effective management at the appropriate hierarchical level of the organization of the socio-natural system within the catchment area, starting from an individual to humankind as a whole.

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