scholarly journals Tutorial: Assessing metagenomics software with the CAMI benchmarking toolkit

2020 ◽  
Author(s):  
Fernando Meyer ◽  
Till-Robin Lesker ◽  
David Koslicki ◽  
Adrian Fritz ◽  
Alexey Gurevich ◽  
...  
Keyword(s):  
Best Practices ◽  
Quantitative Data ◽  
Critical Assessment ◽  
Data Sets ◽  
Software Performance ◽  
Performance Estimate ◽  
Microbiome Research ◽  
Metagenome Assembly ◽  
Community Of Researchers ◽  
Gut Metagenome

AbstractComputational methods are key in microbiome research, and obtaining a quantitative and unbiased performance estimate is important for method developers and applied researchers. For meaningful comparisons between methods, to identify best practices, common use cases, and to reduce overhead in benchmarking, it is necessary to have standardized data sets, procedures, and metrics for evaluation. In this tutorial, we describe emerging standards in computational metaomics benchmarking derived and agreed upon by a larger community of researchers. Specifically, we outline recent efforts by the Critical Assessment of Metagenome Interpretation (CAMI) initiative, which supplies method developers and applied researchers with exhaustive quantitative data about software performance in realistic scenarios and organizes community-driven benchmarking challenges. We explain the most relevant evaluation metrics to assess metagenome assembly, binning, and profiling results, and provide step-by-step instructions on how to generate them. The instructions use simulated mouse gut metagenome data released in preparation for the second round of CAMI challenges and showcase the use of a repository of tool results for CAMI data sets. This tutorial will serve as a reference to the community and facilitate informative and reproducible benchmarking in microbiome research.

scholarly journals Large-Scale Metagenome Assembly Reveals Novel Animal-Associated Microbial Genomes, Biosynthetic Gene Clusters, and Other Genetic Diversity

mSystems ◽  
2020 ◽  
Vol 5 (6) ◽  
Author(s):  
Nicholas D. Youngblut ◽  
Jacobo de la Cuesta-Zuluaga ◽  
Georg H. Reischer ◽  
Silke Dauser ◽  
Nathalie Schuster ◽  
...  
Keyword(s):  
Large Scale ◽  
Animal Species ◽  
Gene Clusters ◽  
Genomic Diversity ◽  
Data Sets ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Microbial Genomes ◽  
Metagenome Assembly ◽  
Gut Metagenome

ABSTRACT Large-scale metagenome assemblies of human microbiomes have produced a vast catalogue of previously unseen microbial genomes; however, comparatively few microbial genomes derive from other vertebrates. Here, we generated 5,596 metagenome-assembled genomes (MAGs) from the gut metagenomes of 180 predominantly wild animal species representing 5 classes, in addition to 14 existing animal gut metagenome data sets. The MAGs comprised 1,522 species-level genome bins (SGBs), most of which were novel at the species, genus, or family level, and the majority were enriched in host versus environment metagenomes. Many traits distinguished SGBs enriched in host or environmental biomes, including the number of antimicrobial resistance genes. We identified 1,986 diverse biosynthetic gene clusters; only 23 clustered with any MIBiG database references. Gene-based assembly revealed tremendous gene diversity, much of it host or environment specific. Our MAG and gene data sets greatly expand the microbial genome repertoire and provide a broad view of microbial adaptations to the vertebrate gut. IMPORTANCE Microbiome studies on a select few mammalian species (e.g., humans, mice, and cattle) have revealed a great deal of novel genomic diversity in the gut microbiome. However, little is known of the microbial diversity in the gut of other vertebrates. We studied the gut microbiomes of a large set of mostly wild animal species consisting of mammals, birds, reptiles, amphibians, and fish. Unfortunately, we found that existing reference databases commonly used for metagenomic analyses failed to capture the microbiome diversity among vertebrates. To increase database representation, we applied advanced metagenome assembly methods to our animal gut data and to many public gut metagenome data sets that had not been used to obtain microbial genomes. Our resulting genome and gene cluster collections comprised a great deal of novel taxonomic and genomic diversity, which we extensively characterized. Our findings substantially expand what is known of microbial genomic diversity in the vertebrate gut.

scholarly journals Inherent Bias of SARS-CoV-2 RNA Quantification for Wastewater Surveillance Due to Variable RT-qPCR Assay Parameters

2021 ◽  
Author(s):  
Aaron Bivins ◽  
Devrim Kaya ◽  
Kyle Bibby ◽  
Stuart Simpson ◽  
Stephen Bustin ◽  
...  
Keyword(s):  
Best Practices ◽  
Quantitative Data ◽  
Large Data ◽  
Large Data Sets ◽  
Data Sets ◽  
Quantitative Real Time Pcr ◽  
Quantitative Measurements ◽  
Rna Quantification ◽  
Reverse Transcription Quantitative Pcr ◽  
Detection And Quantification

The coronavirus disease 2019 (COVID-19) pandemic has led to wastewater surveillance becoming an important tool for monitoring the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within communities. As a result, molecular methods, in particular reverse transcription-quantitative PCR (RT-qPCR), have been employed to generate large data sets aimed at the detection and quantification of SARS-CoV-2 in wastewater. Although RT-qPCR is rapid and sensitive, there is no standard method that fits all use cases, there are no certified quantification standards and experiments are carried out using numerous different assays, reagents, instruments, and data analysis protocols. These variations can lead to the reporting of erroneous quantitative data resulting in potentially misleading interpretations and conclusions. We have reviewed the SARS-CoV-2 wastewater surveillance literature focusing on the variability of RT-qPCR data as revealed by inconsistent standard curves and associated parameters. We find that variation in these parameters and deviations from best practices as described in The Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines suggest a lack of reproducibility and reliability in quantitative measurements of SARS-CoV-2 RNA in wastewater.

Building holistic and agile collection development and assessment

2015 ◽  
Vol 16 (1) ◽  
pp. 62-85 ◽  
Author(s):  
Cheri Jeanette Duncan ◽  
Genya Morgan O'Gara
Keyword(s):  
Quantitative Data ◽  
Holistic Approach ◽  
Assessment Model ◽  
Data Sets ◽  
Collection Development ◽  
Content Type ◽  
Qualitative And Quantitative ◽  
Institutional Goals ◽  
Scholarly Output ◽  
Use Of Data

Purpose – The purpose of this paper is to examine the development of a flexible collections assessment rubric comprised of a suite of tools for more consistently and effectively evaluating and expressing a holistic value of library collections to a variety of constituents, from administrators to faculty and students, with particular emphasis to the use of data already being collected at libraries to “take the temperature” of how responsive collections are in supporting institutional goals. Design/methodology/approach – Using a literature review, internal and external conversations, several collections pilot projects, and a variety of other investigative mechanisms, this paper explores methods for creating a more flexible, holistic collection development and assessment model using both qualitative and quantitative data. Findings – The products of scholarship that academic libraries include in their collections are expanding exponentially and range from journals and monographs in all formats, to databases, data sets, digital text and images, streaming media, visualizations and animations. Content is also being shared in new ways and on a variety of platforms. Yet the framework for evaluating this new landscape of scholarly output is in its infancy. So, how do libraries develop and assess collections in a consistent, holistic, yet agile, manner? Libraries must employ a variety of mechanisms to ensure this goal, while remaining flexible in adapting to the shifting collections environment. Originality/value – In so much as the authors are aware, this is the first paper to examine an agile, holistic approach to collections using both qualitative and quantitative data.

scholarly journals PS2-54: Best Practices: Improving Quality and Reliability in Research Data Sets

2013 ◽  
Vol 11 (3) ◽  
pp. 157-157
Author(s):  
L. McFarland ◽  
J. Richter ◽  
C. Bredfeldt
Keyword(s):  
Best Practices ◽  
Research Data ◽  
Data Sets ◽  
Quality And Reliability

Software Performance Estimate using Fuzzy Based Backpropagation Learning

2016 ◽  
pp. 376-398
Author(s):  
Khaleel Ahmad ◽  
Gaurav Kumar ◽  
Abdul Wahid ◽  
Mudasir M. Kirmani
Keyword(s):  
Software Industry ◽  
Performance Measure ◽  
Performance Estimation ◽  
Accurate Estimation ◽  
Software Performance ◽  
Daily Lives ◽  
Software Application ◽  
Performance Estimate ◽  
Efficient Performance ◽  
Software Product

Accurate estimation of the software performance and its reliability is an important task in designing, developing and implementing software as per the desired requirements. With the increase in individuals relying on software application in their daily lives has resulted in increase in demand for good quality software with efficient performance. The professionals in the software industry are facing an uphill task of developing software with efficient performance measure and at the same time capable of evaluating software performance. In order to evaluate software performance it is necessary to have a method to estimate the software performance. The estimation of software performance plays an important role in predicting acceptability and longevity of a software product. Software performance estimation is essential in existing software-dominated environment where part of daily life is directly or indirectly dependent on software for fulfilling requirements. In this chapter discusses the reasons underlying the proposals and shows the pitfalls associated to these software attributes.

scholarly journals A stepwise method for annotating appraisal

2018 ◽  
Vol 25 (2) ◽  
pp. 229-258 ◽  
Author(s):  
Matteo Fuoli
Keyword(s):  
Statistical Analysis ◽  
Best Practices ◽  
Quantitative Data ◽  
Manual Annotation ◽  
Methodological Issues ◽  
Stepwise Method ◽  
Evaluative Language ◽  
Practical Tool ◽  
The Creation ◽  
Context Specific

Abstract Despite a growing awareness of methodological issues, the literature on appraisal has not so far provided adequate answers to some of the key challenges involved in reliably identifying and classifying evaluative language expressions. This article presents a stepwise method for the manual annotation of appraisal in text that is designed to optimize reliability, replicability and transparency. The procedure consists of seven steps, from the creation of a context-specific annotation manual to the statistical analysis of the quantitative data derived from the manually-performed annotations. By presenting this method, the article pursues the twofold purpose of (i) providing a practical tool that can facilitate more reliable, replicable and transparent analyses, and (ii) fostering a discussion of the best practices that should be observed when manually annotating appraisal.

scholarly journals Mainstreaming Microbes across Biomes

BioScience ◽  
2020 ◽  
Vol 70 (7) ◽  
pp. 589-596 ◽  
Author(s):  
Laurence J Clarke ◽  
Penelope J Jones ◽  
Hans Ammitzboll ◽  
Leon A Barmuta ◽  
Martin F Breed ◽  
...  
Keyword(s):  
Ecosystem Services ◽  
Microbial Communities ◽  
Public Awareness ◽  
Data Sets ◽  
The Public ◽  
Microbiome Research ◽  
Potential Applications ◽  
Potential Benefits ◽  
Global Data Sets ◽  
Global Data

Abstract Bacteria, fungi, and other microorganisms in the environment (i.e., environmental microbiomes) provide vital ecosystem services and affect human health. Despite their importance, public awareness of environmental microbiomes has lagged behind that of human microbiomes. A key problem has been a scarcity of research demonstrating the microbial connections across environmental biomes (e.g., marine, soil) and between environmental and human microbiomes. We show in the present article, through analyses of almost 10,000 microbiome papers and three global data sets, that there are significant taxonomic similarities in microbial communities across biomes, but very little cross-biome research exists. This disconnect may be hindering advances in microbiome knowledge and translation. In this article, we highlight current and potential applications of environmental microbiome research and the benefits of an interdisciplinary, cross-biome approach. Microbiome scientists need to engage with each other, government, industry, and the public to ensure that research and applications proceed ethically, maximizing the potential benefits to society.

scholarly journals A quantitative comparison of dispersed spore/pollen and plant megafossil assemblages from a Middle Jurassic plant bed from Yorkshire, UK

Paleobiology ◽  
2015 ◽  
Vol 41 (4) ◽  
pp. 640-660 ◽  
Author(s):  
Sam M. Slater ◽  
Charles H. Wellman
Keyword(s):  
Multivariate Analysis ◽  
Middle Jurassic ◽  
Quantitative Data ◽  
Reproductive Strategies ◽  
Quantitative Comparison ◽  
Principal Factor ◽  
Data Sets ◽  
Conflicting Evidence ◽  
Sampling Regime ◽  
Abundance And Diversity

AbstractDetailed quantitative data has previously been collected from plant megafossil assemblages from a Middle Jurassic (Aalenian) plant bed from Hasty Bank, North Yorkshire, UK. We conducted a similar analysis of palynological dispersed sporomorph (spore and pollen) assemblages collected from the same section using the same sampling regime: 67 sporomorph taxa were recorded from 50 samples taken at 10 cm intervals through the plant bed. Basic palynofacies analysis was also undertaken on each sample. Both dispersed sporomorph and plant megafossil assemblages display consistent changes in composition, diversity (richness), and abundance through time. However, the dispersed sporomorph and plant megafossil records provide conflicting evidence for the nature of parent vegetation. Specifically, conifers and ferns are underrepresented in plant megafossil assemblages, bryophytes and lycopsids are represented only in sporomorph assemblages, and sphenophytes, pteridosperms, Caytoniales, Cycadales, Ginkgoales and Bennettitales are comparatively underrepresented in sporomorph assemblages. Combined multivariate analysis (correspondence analysis and nonmetric multidimensional scaling) of sporomorph occurrence/abundance data demonstrates that temporal variation in sporomorph assemblages is the result of depositional change through the plant bed. The reproductive strategies of parent plants are considered to be a principal factor in shaping many of the major abundance and diversity irregularities between dispersed sporomorph and plant megafossil data sets that seemingly reflects different parent vegetation. Preferential occurrence/preservation of sporomorphs and equivalent parent plants is a consequence of a complex array of biological, ecological, geographical, taphonomic, and depositional factors that act inconsistently between and within fossil assemblages, which results in notable discrepancies between data sets.

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