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DATA RESOURCES AND ANALYSES FAIR Header Reference genome: A TRUSTworthy standard.

ABSTRACT: The lack of interoperable data standards among reference genome data-sharing platforms inhibits cross-platform analysis while increasing the risk of data provenance loss. Here, we describe the FAIR-bioHeaders Reference genome (FHR), a metadata standard guided by the principles of Findability, Accessibility, Interoperability, and Reuse (FAIR) in addition to the principles of Transparency, Responsibility, User focus, Sustainability, and Technology (TRUST). The objective of FHR is to provide an extensive set of data serialisation methods and minimum data field requirements while still maintaining extensibility, flexibility, and expressivity in an increasingly decentralised genomic data ecosystem. The effort needed to implement FHR is low; FHR's design philosophy ensures easy implementation while retaining the benefits gained from recording both machine and human-readable provenance.

SUBMITTER: Wright A

PROVIDER: S-EPMC10705436 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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DATA RESOURCES AND ANALYSES FAIR Header Reference genome: A TRUSTworthy standard.

Wright Adam A Wilkinson Mark D MD Mungall Chris C Cain Scott S Richards Stephen S Sternberg Paul P Provin Ellen E Jacobs Jonathan L JL Geib Scott S Raciti Daniela D Yook Karen K Stein Lincoln L Molik David C DC

bioRxiv : the preprint server for biology 20231220

The lack of interoperable data standards among reference genome data-sharing platforms inhibits cross-platform analysis while increasing the risk of data provenance loss. Here, we describe the FAIR-bioHeaders Reference genome (FHR), a metadata standard guided by the principles of Findability, Accessibility, Interoperability, and Reuse (FAIR) in addition to the principles of Transparency, Responsibility, User focus, Sustainability, and Technology (TRUST). The objective of FHR is to provide an ext ...[more]

PMID: 38076838

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Project description:Motivation:Comparisons of microbiome communities across populations are often based on pairwise distance measures (beta-diversity). Standard analyses (principal coordinate plots, permutation tests, kernel methods) require access to primary data if another investigator wants to add or compare independent data. We propose using standard reference measurements to simplify microbiome beta-diversity analyses, to make them more transparent, and to facilitate independent validation and comparisons across studies. Results:Using stool and nasal reference sets from the Human Microbiome Project (HMP), we computed mean distances (actually Bray-Curtis or Pearson correlation dissimilarities) to each reference set for each new sample. Thus, each new sample has two mean distances that can be plotted and analyzed with classical statistical methods. To test the approach, we studied independent (not reference) HMP subjects. Simple Hotelling tests demonstrated statistically significant differences in mean distances to reference sets between all pairs of body sites (stool, skin, nasal, saliva and vagina) at the phylum, class, order, family and genus levels. Using the distance to a single reference set was usually sufficient, but using both reference sets always worked well. The use of reference sets simplifies standard analyses of beta-diversity and facilitates the independent validation and combining of such data because others can compute distances to the same reference sets. Moreover, standard statistical methods for survival analysis, logistic regression and other procedures can be applied to vectors of mean distances to reference sets, thereby greatly expanding the potential uses of beta-diversity information. More work is needed to identify the best reference sets for particular applications. Availability and implementation:https://github.com/NCI-biostats/microbiome-fixed-reference. Supplementary information:Supplementary data are available at Bioinformatics online.

Project description:BackgroundTo reduce ergonomic risk factors in terms of awkward and constrained postures and high velocities, it is important to perform adequate risk assessments. Technical methods provide objective measures of physical workload. These methods have so far mainly been used by researchers. However, if written instructions how to apply the sensors and how to adopt the reference posture are provided, together with triaxial accelerometers, it may be possible for employees to record their own physical workload. The exposure in terms of e.g. upper arm elevations could then easily be assessed for all workers in a workplace. The main aims of this study were: 1) to compare analyses for self-recording of upper arm elevation during work using a simplified reference posture versus using a standard reference posture, and 2) to compare the two reference postures.MethodsTwenty-eight cleaners attached an accelerometer to their dominant upper arm and adopted a simplified reference according to a written instruction. They were thereafter instructed by a researcher to adopt a standard reference. Upper arm elevations were recorded for 2 or 3 days. Each recording was analysed twice; relative to the simplified reference posture and relative to the standard reference posture. The group means of the differences in recorded upper arm elevations between simplified and standard reference analyses were assessed using Wilcoxon signed ranks test. Furthermore, we calculated the group mean of the differences between the simplified reference posture and the standard reference posture.ResultsFor arm elevation during work (50th percentile), the group mean of the differences between the two analyses was 0.2° (range -7 - 10°). The group mean of the differences between the two references was 9° (range 1 - 21°). The subjects were able to follow the instructions in the protocol and performed self-recording of upper arm elevation and velocity.ConclusionsThe small difference between the two analyses indicates that recordings performed by employees themselves are comparable, on a group level, with those performed by researchers. Self-recordings in combination with action levels would provide employers with a method for risk assessment as a solid basis for prevention of work-related musculoskeletal disorders.

Dataset Information

DATA RESOURCES AND ANALYSES FAIR Header Reference genome: A TRUSTworthy standard.

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DATA RESOURCES AND ANALYSES FAIR Header Reference genome: A TRUSTworthy standard.

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