Arnaud Caillo

Bio: Arnaud Caillo is an academic researcher. The author has contributed to research in topics: Repeatability & Multivariate statistics. The author has an hindex of 1, co-authored 1 publications receiving 3404 citations.

From core referencing to data re-use: two French national initiatives to reinforce paleodata stewardship (National Cyber Core Repository and LTER France Retro-Observatory)

Abstract: Managing paleoscience data is highly challenging to the multiplicity of actors in play, types of sampling, analysis, post-analysis treatments, statistics etc. However, a well-structured curating of data would permit innovative developments based on data and/or sample re-use, such as meta-analysis or the development of new proxies on previously studied cores. In this paper, we will present two recent initiatives that allowed us tackling this objective at a French national level: the “National Cyber Core Repository” (NCCR) and the “LTER-France retro-observatory” (ROZA).NCCR was developed under the umbrella of the French National Center fo Coring and Drilling (C2FN) thanks to the national excellence equipment project CLIMCOR. It aims at gathering on a unique website the locations and metadata of any scientific coring/drilling performed by French teams or using French facilities, whatever the type of archive it is (lake/marine sediment; ice etc.). It uses international standard, notably IGSN (for samples), ORCID (for persons) and DOI (for campaigns). NCC follows the INSPIRE ISO 19115 standard in order to catalogue the data. For continental sediment, NCCR may be fed directly on the field through a specifically developed mobile application.Based on NCCR, further initiatives may be led. In particular, under the umbrella of LTER-France (Long Term Ecological Research), we developed ROZA in order to facilitate the re-use of data and samples. Here the idea is to capitalise the knowledge on a given lake from which several sediment cores can be taken through time. In that aim we selected at least one lake from each of the 13 areas composing the network LTER-France. To enter the database, a set of mandatory data must be provided under a pre-determined format. In that case, the insertion of ROZA within the network LTER will favor to use of paleodata by non-paleodata scientists, in particular ecologists.

Enhancing the learning of evolutionary anthropology skills by combining student‐active teaching with actual and virtual immersion of Master's students in fieldwork, laboratory practice, and dissemination

Abstract: Abstract Higher education in evolutionary anthropology involves providing students with in‐depth knowledge of biological and cultural heritage sites and collections that are frequently inaccessible. Indeed, most sites, fossils, and archaeological remains can be visited or manipulated only rarely and solely by specialists with extensive experience. Owing to the development of 3D and medical imaging techniques, this fragile heritage is now more widely accessible, and in a dynamic way. However, exclusive adoption of virtual teaching and learning has a negative impact on student engagement and, naturally, on exchanges with instructors, and thus cannot be used without some reservations. In the ITAP (Immersion dans les Terrains de l’Anthropologie biologique et de la Préhistoire) project of the higher education STEP (Soutien à la Transformation et à l’Expérimentation Pédagogiques) transformation program at the University of Bordeaux, we combine student‐active teaching with Master's students fully immersed in ongoing fieldwork, laboratory study, and dissemination of research results in order to develop more individually shaped learning curricula and to foster both professional and new interdisciplinary skills. Here, we present examples of experiments conducted in the ITAP project using both authentic and virtual collections of archaeological, experimental, and reference materials that help to break down the barriers between research activities and higher education, as well as providing a more general appraisal of the appropriate use of virtual tools in higher education by combining them with real‐life situations.

Data quality control considerations in multivariate environmental monitoring: experience of the French coastal network SOMLIT

Abstract: Introduction While crucial to ensuring the production of accurate and high-quality data—and to avoid erroneous conclusions—data quality control (QC) in environmental monitoring datasets is still poorly documented. Methods With a focus on annual inter-laboratory comparison (ILC) exercises performed in the context of the French coastal monitoring SOMLIT network, we share here a pragmatic approach to QC, which allows the calculation of systematic and random errors, measurement uncertainty, and individual performance. After an overview of the different QC actions applied to fulfill requirements for quality and competence, we report equipment, accommodation, design of the ILC exercises, and statistical methodology specially adapted to small environmental networks (<20 laboratories) and multivariate datasets. Finally, the expanded uncertainty of measurement for 20 environmental variables routinely measured by SOMLIT from discrete sampling—including Essential Ocean Variables—is provided. Results, Discussion, Conclusion The examination of the temporal variations (2001–2021) in the repeatability, reproducibility, and trueness of the SOMLIT network over time confirms the essential role of ILC exercises as a tool for the continuous improvement of data quality in environmental monitoring datasets.

The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019.

Abstract: The GWAS Catalog delivers a high-quality curated collection of all published genome-wide association studies enabling investigations to identify causal variants, understand disease mechanisms, and establish targets for novel therapies. The scope of the Catalog has also expanded to targeted and exome arrays with 1000 new associations added for these technologies. As of September 2018, the Catalog contains 5687 GWAS comprising 71673 variant-trait associations from 3567 publications. New content includes 284 full P-value summary statistics datasets for genome-wide and new targeted array studies, representing 6 × 109 individual variant-trait statistics. In the last 12 months, the Catalog's user interface was accessed by ∼90000 unique users who viewed >1 million pages. We have improved data access with the release of a new RESTful API to support high-throughput programmatic access, an improved web interface and a new summary statistics database. Summary statistics provision is supported by a new format proposed as a community standard for summary statistics data representation. This format was derived from our experience in standardizing heterogeneous submissions, mapping formats and in harmonizing content. Availability: https://www.ebi.ac.uk/gwas/.

PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews.

Abstract: The methods and results of systematic reviews should be reported in sufficient detail to allow users to assess the trustworthiness and applicability of the review findings. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement was developed to facilitate transparent and complete reporting of systematic reviews and has been updated (to PRISMA 2020) to reflect recent advances in systematic review methodology and terminology. Here, we present the explanation and elaboration paper for PRISMA 2020, where we explain why reporting of each item is recommended, present bullet points that detail the reporting recommendations, and present examples from published reviews. We hope that changes to the content and structure of PRISMA 2020 will facilitate uptake of the guideline and lead to more transparent, complete, and accurate reporting of systematic reviews.

The Gene Ontology resource: enriching a GOld mine

Abstract: The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding the functions of genes and gene products. Here, we report the advances of the consortium over the past two years. The new GO-CAM annotation framework was notably improved, and we formalized the model with a computational schema to check and validate the rapidly increasing repository of 2838 GO-CAMs. In addition, we describe the impacts of several collaborations to refine GO and report a 10% increase in the number of GO annotations, a 25% increase in annotated gene products, and over 9,400 new scientific articles annotated. As the project matures, we continue our efforts to review older annotations in light of newer findings, and, to maintain consistency with other ontologies. As a result, 20 000 annotations derived from experimental data were reviewed, corresponding to 2.5% of experimental GO annotations. The website (http://geneontology.org) was redesigned for quick access to documentation, downloads and tools. To maintain an accurate resource and support traceability and reproducibility, we have made available a historical archive covering the past 15 years of GO data with a consistent format and file structure for both the ontology and annotations.

The ARRIVE guidelines 2.0: Updated guidelines for reporting animal research

Abstract: Reproducible science requires transparent reporting. The ARRIVE guidelines (Animal Research: Reporting of In Vivo Experiments) were originally developed in 2010 to improve the reporting of animal research. They consist of a checklist of information to include in publications describing in vivo experiments to enable others to scrutinise the work adequately, evaluate its methodological rigour, and reproduce the methods and results. Despite considerable levels of endorsement by funders and journals over the years, adherence to the guidelines has been inconsistent, and the anticipated improvements in the quality of reporting in animal research publications have not been achieved. Here, we introduce ARRIVE 2.0. The guidelines have been updated and information reorganised to facilitate their use in practice. We used a Delphi exercise to prioritise and divide the items of the guidelines into 2 sets, the “ARRIVE Essential 10,” which constitutes the minimum requirement, and the “Recommended Set,” which describes the research context. This division facilitates improved reporting of animal research by supporting a stepwise approach to implementation. This helps journal editors and reviewers verify that the most important items are being reported in manuscripts. We have also developed the accompanying Explanation and Elaboration document, which serves (1) to explain the rationale behind each item in the guidelines, (2) to clarify key concepts, and (3) to provide illustrative examples. We aim, through these changes, to help ensure that researchers, reviewers, and journal editors are better equipped to improve the rigour and transparency of the scientific process and thus reproducibility.

DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants

Abstract: The information about the genetic basis of human diseases lies at the heart of precision medicine and drug discovery. However, to realize its full potential to support these goals, several problems, such as fragmentation, heterogeneity, availability and different conceptualization of the data must be overcome. To provide the community with a resource free of these hurdles, we have developed DisGeNET (http://www.disgenet.org), one of the largest available collections of genes and variants involved in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype-phenotype relationships. The information is accessible through a web interface, a Cytoscape App, an RDF SPARQL endpoint, scripts in several programming languages and an R package. DisGeNET is a versatile platform that can be used for different research purposes including the investigation of the molecular underpinnings of specific human diseases and their comorbidities, the analysis of the properties of disease genes, the generation of hypothesis on drug therapeutic action and drug adverse effects, the validation of computationally predicted disease genes and the evaluation of text-mining methods performance.