Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project

Viewing systematic reviews and meta-analysis in social research through different lenses

Systematic reviews and meta-analyses are used to combine results across studies to determine an overall effect. Meta-analysis is especially useful for combining evidence to inform social policy, but meta-analyses of applied social science research may encounter practical issues arising from the nature of the research domain. The current paper identifies potential resolutions to four issues that may be encountered in systematic reviews and meta-analyses in social research. The four issues are: scoping and targeting research questions appropriate for meta-analysis; selecting eligibility criteria where primary studies vary in research design and choice of outcome measures; dealing with inconsistent reporting in primary studies; and identifying sources of heterogeneity with multiple confounded moderators. The paper presents an overview of each issue with a review of potential resolutions, identified from similar issues encountered in meta-analysis in medical and biological sciences. The discussion aims to share and improve methodology in systematic reviews and meta-analysis by promoting cross-disciplinary communication, that is, to encourage 'viewing through different lenses'.

Data Interpretation in the Digital Age

The consultation of internet databases and the related use of computer software to retrieve, visualise and model data have become key components of many areas of scientific research. This paper focuses on the relation of these developments to understanding the biology of organisms, and examines the conditions under which the evidential value of data posted online is assessed and interpreted by the researchers who access them, in ways that underpin and guide the use of those data to foster discovery. I consider the types of knowledge required to interpret data as evidence for claims about organisms, and in particular the relevance of knowledge acquired through physical interaction with actual organisms to assessing the evidential value of data found online. I conclude that familiarity with research in vivo is crucial to assessing the quality and significance of data visualised in silico; and that studying how biological data are disseminated, visualised, assessed and interpreted in the digital age provides a strong rationale for viewing scientific understanding as a social and distributed, rather than individual and localised, achievement.

The quality of methods reporting in parasitology experiments

There is a growing concern both inside and outside the scientific community over the lack of reproducibility of experiments. The depth and detail of reported methods are critical to the reproducibility of findings, but also for making it possible to compare and integrate data from different studies. In this study, we evaluated in detail the methods reporting in a comprehensive set of trypanosomiasis experiments that should enable valid reproduction, integration and comparison of research findings. We evaluated a subset of other parasitic (Leishmania, Toxoplasma, Plasmodium, Trichuris and Schistosoma) and non-parasitic (Mycobacterium) experimental infections in order to compare the quality of method reporting more generally. A systematic review using PubMed (2000-2012) of all publications describing gene expression in cells and animals infected with Trypanosoma spp was undertaken based on PRISMA guidelines; 23 papers were identified and included. We defined a checklist of essential parameters that should be reported and have scored the number of those parameters that are reported for each publication. Bibliometric parameters (impact factor, citations and h-index) were used to look for association between Journal and Author status and the quality of method reporting. Trichuriasis experiments achieved the highest scores and included the only paper to score 100% in all criteria. The mean of scores achieved by Trypanosoma articles through the checklist was 65.5% (range 32-90%). Bibliometric parameters were not correlated with the quality of method reporting (Spearman's rank correlation coefficient <-0.5; p>0.05). Our results indicate that the quality of methods reporting in experimental parasitology is a cause for concern and it has not improved over time, despite there being evidence that most of the assessed parameters do influence the results. We propose that our set of parameters be used as guidelines to improve the quality of the reporting of experimental infection models as a pre-requisite for integrating and comparing sets of data.

Minimum information about a spinal cord injury experiment: a proposed reporting standard for spinal cord injury experiments

The lack of reproducibility in many areas of experimental science has a number of causes, including a lack of transparency and precision in the description of experimental approaches. This has far-reaching consequences, including wasted resources and slowing of progress. Additionally, the large number of laboratories around the world publishing articles on a given topic make it difficult, if not impossible, for individual researchers to read all of the relevant literature. Consequently, centralized databases are needed to facilitate the generation of new hypotheses for testing. One strategy to improve transparency in experimental description, and to allow the development of frameworks for computer-readable knowledge repositories, is the adoption of uniform reporting standards, such as common data elements (data elements used in multiple clinical studies) and minimum information standards. This article describes a minimum information standard for spinal cord injury (SCI) experiments, its major elements, and the approaches used to develop it. Transparent reporting standards for experiments using animal models of human SCI aim to reduce inherent bias and increase experimental value.

Standardized metadata for human pathogen/vector genomic sequences

High throughput sequencing has accelerated the determination of genome sequences for thousands of human infectious disease pathogens and dozens of their vectors. The scale and scope of these data are enabling genotype-phenotype association studies to identify genetic determinants of pathogen virulence and drug/insecticide resistance, and phylogenetic studies to track the origin and spread of disease outbreaks. To maximize the utility of genomic sequences for these purposes, it is essential that metadata about the pathogen/vector isolate characteristics be collected and made available in organized, clear, and consistent formats. Here we report the development of the GSCID/BRC Project and Sample Application Standard, developed by representatives of the Genome Sequencing Centers for Infectious Diseases (GSCIDs), the Bioinformatics Resource Centers (BRCs) for Infectious Diseases, and the U.S. National Institute of Allergy and Infectious Diseases (NIAID), part of the National Institutes of Health (NIH), informed by interactions with numerous collaborating scientists. It includes mapping to terms from other data standards initiatives, including the Genomic Standards Consortium's minimal information (MIxS) and NCBI's BioSample/BioProjects checklists and the Ontology for Biomedical Investigations (OBI). The standard includes data fields about characteristics of the organism or environmental source of the specimen, spatial-temporal information about the specimen isolation event, phenotypic characteristics of the pathogen/vector isolated, and project leadership and support. By modeling metadata fields into an ontology-based semantic framework and reusing existing ontologies and minimum information checklists, the application standard can be extended to support additional project-specific data fields and integrated with other data represented with comparable standards. The use of this metadata standard by all ongoing and future GSCID sequencing projects will provide a consistent representation of these data in the BRC resources and other repositories that leverage these data, allowing investigators to identify relevant genomic sequences and perform comparative genomics analyses that are both statistically meaningful and biologically relevant.

Semantic Web repositories for genomics data using the eXframe platform

BACKGROUND

With the advent of inexpensive assay technologies, there has been an unprecedented growth in genomics data as well as the number of databases in which it is stored. In these databases, sample annotation using ontologies and controlled vocabularies is becoming more common. However, the annotation is rarely available as Linked Data, in a machine-readable format, or for standardized queries using SPARQL. This makes large-scale reuse, or integration with other knowledge bases very difficult.

METHODS

To address this challenge, we have developed the second generation of our eXframe platform, a reusable framework for creating online repositories of genomics experiments. This second generation model now publishes Semantic Web data. To accomplish this, we created an experiment model that covers provenance, citations, external links, assays, biomaterials used in the experiment, and the data collected during the process. The elements of our model are mapped to classes and properties from various established biomedical ontologies. Resource Description Framework (RDF) data is automatically produced using these mappings and indexed in an RDF store with a built-in Sparql Protocol and RDF Query Language (SPARQL) endpoint.

CONCLUSIONS

Using the open-source eXframe software, institutions and laboratories can create Semantic Web repositories of their experiments, integrate it with heterogeneous resources and make it interoperable with the vast Semantic Web of biomedical knowledge.

Metadata Standard and Data Exchange Specifications to Describe, Model, and Integrate Complex and Diverse High-Throughput Screening Data from the Library of Integrated Network-based Cellular Signatures (LINCS)

The National Institutes of Health Library of Integrated Network-based Cellular Signatures (LINCS) program is generating extensive multidimensional data sets, including biochemical, genome-wide transcriptional, and phenotypic cellular response signatures to a variety of small-molecule and genetic perturbations with the goal of creating a sustainable, widely applicable, and readily accessible systems biology knowledge resource. Integration and analysis of diverse LINCS data sets depend on the availability of sufficient metadata to describe the assays and screening results and on their syntactic, structural, and semantic consistency. Here we report metadata specifications for the most important molecular and cellular components and recommend them for adoption beyond the LINCS project. We focus on the minimum required information to model LINCS assays and results based on a number of use cases, and we recommend controlled terminologies and ontologies to annotate assays with syntactic consistency and semantic integrity. We also report specifications for a simple annotation format (SAF) to describe assays and screening results based on our metadata specifications with explicit controlled vocabularies. SAF specifically serves to programmatically access and exchange LINCS data as a prerequisite for a distributed information management infrastructure. We applied the metadata specifications to annotate large numbers of LINCS cell lines, proteins, and small molecules. The resources generated and presented here are freely available.

Optimizing methodologies for PCR-based DNA methylation analysis

Comprehensive analysis of DNA methylation patterns is critical for understanding the molecular basis of many human diseases. While hundreds of PCR-based DNA methylation studies are published every year, the selection and implementation of appropriate methods for these studies can be challenging for molecular genetics researchers not yet familiar with methylation analysis. Here we review the most commonly used PCR-based DNA methylation analysis techniques: bisulfite sequencing PCR (BSP), methylation specific PCR (MSP), MethyLight, and methylation-sensitive high resolution melting (MS-HRM). We provide critical analysis of the strengths and weaknesses of each approach as well as a series of guidelines to assist in selecting and implementing an appropriate method.

A digital repository with an extensible data model for biobanking and genomic analysis management

Motivation

Molecular biology laboratories require extensive metadata to improve data collection and analysis. The heterogeneity of the collected metadata grows as research is evolving in to international multi-disciplinary collaborations and increasing data sharing among institutions. Single standardization is not feasible and it becomes crucial to develop digital repositories with flexible and extensible data models, as in the case of modern integrated biobanks management.

Results

We developed a novel data model in JSON format to describe heterogeneous data in a generic biomedical science scenario. The model is built on two hierarchical entities: processes and events, roughly corresponding to research studies and analysis steps within a single study. A number of sequential events can be grouped in a process building up a hierarchical structure to track patient and sample history. Each event can produce new data. Data is described by a set of user-defined metadata, and may have one or more associated files. We integrated the model in a web based digital repository with a data grid storage to manage large data sets located in geographically distinct areas. We built a graphical interface that allows authorized users to define new data types dynamically, according to their requirements. Operators compose queries on metadata fields using a flexible search interface and run them on the database and on the grid. We applied the digital repository to the integrated management of samples, patients and medical history in the BIT-Gaslini biobank. The platform currently manages 1800 samples of over 900 patients. Microarray data from 150 analyses are stored on the grid storage and replicated on two physical resources for preservation. The system is equipped with data integration capabilities with other biobanks for worldwide information sharing.

Conclusions

Our data model enables users to continuously define flexible, ad hoc, and loosely structured metadata, for information sharing in specific research projects and purposes. This approach can improve sensitively interdisciplinary research collaboration and allows to track patients' clinical records, sample management information, and genomic data. The web interface allows the operators to easily manage, query, and annotate the files, without dealing with the technicalities of the data grid.

The eGenVar data management system--cataloguing and sharing sensitive data and metadata for the life sciences

Systematic data management and controlled data sharing aim at increasing reproducibility, reducing redundancy in work, and providing a way to efficiently locate complementing or contradicting information. One method of achieving this is collecting data in a central repository or in a location that is part of a federated system and providing interfaces to the data. However, certain data, such as data from biobanks or clinical studies, may, for legal and privacy reasons, often not be stored in public repositories. Instead, we describe a metadata cataloguing system and a software suite for reporting the presence of data from the life sciences domain. The system stores three types of metadata: file information, file provenance and data lineage, and content descriptions. Our software suite includes both graphical and command line interfaces that allow users to report and tag files with these different metadata types. Importantly, the files remain in their original locations with their existing access-control mechanisms in place, while our system provides descriptions of their contents and relationships. Our system and software suite thereby provide a common framework for cataloguing and sharing both public and private data.

Database URL:http://bigr.medisin.ntnu.no/data/eGenVar/

Screening for host proteins with pro- and antiviral activity using high-throughput RNAi

RNA interference (RNAi) describes the mechanism of posttranscriptional gene silencing by small (typically 18-24 nucleotides) RNA molecules and includes small-interfering RNAs (siRNAs) and microRNAs (miRNAs). As siRNAs and miRNAs are simple to use experimentally, they are easily adaptable to high-throughput methodologies and provide an ideal tool for genome-wide gene depletion studies. Over recent years RNAi has been used extensively to investigate the complex interactions between pathogen and host, and the identification of novel cellular factors and pathways influencing viral disease pathogenesis exemplifies the power of this technique. Here, the use of RNAi to investigate the functional role of cellular proteins in herpesvirus (Herpes Simplex Virus Type I; HSV-1) replication and how to identify novel antiviral and proviral host proteins is described.

MIRAGE: the minimum information required for a glycomics experiment

The MIRAGE (minimum information required for a glycomics experiment) initiative was founded in Seattle, WA, in November 2011 in order to develop guidelines for reporting the qualitative and quantitative results obtained by diverse types of glycomics analyses, including the conditions and techniques that were applied to prepare the glycans for analysis and generate the primary data along with the tools and parameters that were used to process and annotate this data. These guidelines must address a broad range of issues, as glycomics data are inherently complex and are generated using diverse methods, including mass spectrometry (MS), chromatography, glycan array-binding assays, nuclear magnetic resonance (NMR) and other rapidly developing technologies. The acceptance of these guidelines by scientists conducting research on biological systems in which glycans have a significant role will facilitate the evaluation and reproduction of glycomics experiments and data that is reported in scientific journals and uploaded to glycomics databases. As a first step, MIRAGE guidelines for glycan analysis by MS have been recently published (Kolarich D, Rapp E, Struwe WB, Haslam SM, Zaia J., et al. 2013. The minimum information required for a glycomics experiment (MIRAGE) project – Improving the standards for reporting mass spectrometry-based glycoanalytic data. Mol. Cell Proteomics. 12:991–995), allowing them to be implemented and evaluated in the context of real-world glycobiology research. In this paper, we set out the historical context, organization structure and overarching objectives of the MIRAGE initiative.

A sea of standards for omics data: sink or swim?

In the era of Big Data, omic-scale technologies, and increasing calls for data sharing, it is generally agreed that the use of community-developed, open data standards is critical. Far less agreed upon is exactly which data standards should be used, the criteria by which one should choose a standard, or even what constitutes a data standard. It is impossible simply to choose a domain and have it naturally follow which data standards should be used in all cases. The 'right' standards to use is often dependent on the use case scenarios for a given project. Potential downstream applications for the data, however, may not always be apparent at the time the data are generated. Similarly, technology evolves, adding further complexity. Would-be standards adopters must strike a balance between planning for the future and minimizing the burden of compliance. Better tools and resources are required to help guide this balancing act.

Minimum information about a biofilm experiment (MIABiE): standards for reporting experiments and data on sessile microbial communities living at interfaces

The minimum information about a biofilm experiment (MIABiE) initiative has arisen from the need to find an adequate and scientifically sound way to control the quality of the documentation accompanying the public deposition of biofilm-related data, particularly those obtained using high-throughput devices and techniques. Thereby, the MIABiE consortium has initiated the identification and organization of a set of modules containing the minimum information that needs to be reported to guarantee the interpretability and independent verification of experimental results and their integration with knowledge coming from other fields. MIABiE does not intend to propose specific standards on how biofilms experiments should be performed, because it is acknowledged that specific research questions require specific conditions which may deviate from any standardization. Instead, MIABiE presents guidelines about the data to be recorded and published in order for the procedure and results to be easily and unequivocally interpreted and reproduced. Overall, MIABiE opens up the discussion about a number of particular areas of interest and attempts to achieve a broad consensus about which biofilm data and metadata should be reported in scientific journals in a systematic, rigorous and understandable manner.

QTREDS: a Ruby on Rails-based platform for omics laboratories

Background

In recent years, the experimental aspects of the laboratory activities have been growing in complexity in terms of amount and diversity of data produced, equipment used, of computer-based workflows needed to process and analyze the raw data generated. To enhance the level of quality control over the laboratory activities and efficiently handle the large amounts of data produced, a Laboratory Management Information System (LIMS) is highly-recommended. A LIMS is a complex software platform that helps researchers to have a complete knowledge of the laboratory activities at each step encouraging them to adopt good laboratory practices.

Results

We have designed and implemented Quality and TRacEability Data System - QTREDS, a software platform born to address the specific needs of the CRS4 Sequencing and Genotyping Platform (CSGP). The system written in the Ruby programming language and developed using the Rails framework is based on four main functional blocks: a sample handler, a workflow generator, an inventory management system and a user management system. The wizard-based sample handler allows to manage one or multiple samples at a time, tracking the path of each sample and providing a full chain of custody. The workflow generator encapsulates a user-friendly JavaScript-based visual tool that allows users to design customized workflows even for those without a technical background. With the inventory management system, reagents, laboratory glassware and consumables can be easily added through their barcodes and minimum stock levels can be controlled to avoid shortages of essential laboratory supplies. QTREDS provides a system for privileges management and authorizations to create different user roles, each with a well-defined access profile.

Conclusions

Tracking and monitoring all the phases of the laboratory activities can help to identify and troubleshoot problems more quickly, reducing the risk of process failures and their related costs. QTREDS was designed to address the specific needs of the CSGP laboratory, where it has been successfully used for over a year, but thanks to its flexibility it can be easily adapted to other "omics" laboratories. The software is freely available for academic users from http://qtreds.crs4.it.

Controlled vocabularies and ontologies in proteomics: overview, principles and practice

This paper focuses on the use of controlled vocabularies (CVs) and ontologies especially in the area of proteomics, primarily related to the work of the Proteomics Standards Initiative (PSI). It describes the relevant proteomics standard formats and the ontologies used within them. Software and tools for working with these ontology files are also discussed. The article also examines the "mapping files" used to ensure correct controlled vocabulary terms that are placed within PSI standards and the fulfillment of the MIAPE (Minimum Information about a Proteomics Experiment) requirements. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.

The Minimal Information about a Proteomics Experiment (MIAPE) from the Proteomics Standards Initiative

During the last 10 years, the Proteomics Standards Initiative from the Human Proteome Organization (HUPO-PSI) has worked on defining standards for proteomics data representation as well as guidelines that state the minimum information that should be included when reporting a proteomics experiment (MIAPE). Such minimum information must describe the complete experiment, including both experimental protocols and data processing methods, allowing a critical evaluation of the whole process and the potential recreation of the work. In this chapter we describe the standardization work performed by the HUPO-PSI, and then we concentrate on the MIAPE guidelines, highlighting its importance when publishing proteomics experiments particularly in specialized proteomics journals. Finally, we describe existing bioinformatics resources that generate MIAPE compliant reports or that check proteomics data files for MIAPE compliance.

Toward more transparent and reproducible omics studies through a common metadata checklist and data publications

Biological processes are fundamentally driven by complex interactions between biomolecules. Integrated high-throughput omics studies enable multifaceted views of cells, organisms, or their communities. With the advent of new post-genomics technologies, omics studies are becoming increasingly prevalent; yet the full impact of these studies can only be realized through data harmonization, sharing, meta-analysis, and integrated research. These essential steps require consistent generation, capture, and distribution of metadata. To ensure transparency, facilitate data harmonization, and maximize reproducibility and usability of life sciences studies, we propose a simple common omics metadata checklist. The proposed checklist is built on the rich ontologies and standards already in use by the life sciences community. The checklist will serve as a common denominator to guide experimental design, capture important parameters, and be used as a standard format for stand-alone data publications. The omics metadata checklist and data publications will create efficient linkages between omics data and knowledge-based life sciences innovation and, importantly, allow for appropriate attribution to data generators and infrastructure science builders in the post-genomics era. We ask that the life sciences community test the proposed omics metadata checklist and data publications and provide feedback for their use and improvement.

linkedISA: semantic representation of ISA-Tab experimental metadata

BACKGROUND

Reporting and sharing experimental metadata- such as the experimental design, characteristics of the samples, and procedures applied, along with the analysis results, in a standardised manner ensures that datasets are comprehensible and, in principle, reproducible, comparable and reusable. Furthermore, sharing datasets in formats designed for consumption by humans and machines will also maximize their use. The Investigation/Study/Assay (ISA) open source metadata tracking framework facilitates standards-compliant collection, curation, visualization, storage and sharing of datasets, leveraging on other platforms to enable analysis and publication. The ISA software suite includes several components used in increasingly diverse set of life science and biomedical domains; it is underpinned by a general-purpose format, ISA-Tab, and conversions exist into formats required by public repositories. While ISA-Tab works well mainly as a human readable format, we have also implemented a linked data approach to semantically define the ISA-Tab syntax.

RESULTS

We present a semantic web representation of the ISA-Tab syntax that complements ISA-Tab's syntactic interoperability with semantic interoperability. We introduce the linkedISA conversion tool from ISA-Tab to the Resource Description Framework (RDF), supporting mappings from the ISA syntax to multiple community-defined, open ontologies and capitalising on user-provided ontology annotations in the experimental metadata. We describe insights of the implementation and how annotations can be expanded driven by the metadata. We applied the conversion tool as part of Bio-GraphIIn, a web-based application supporting integration of the semantically-rich experimental descriptions. Designed in a user-friendly manner, the Bio-GraphIIn interface hides most of the complexities to the users, exposing a familiar tabular view of the experimental description to allow seamless interaction with the RDF representation, and visualising descriptors to drive the query over the semantic representation of the experimental design. In addition, we defined queries over the linkedISA RDF representation and demonstrated its use over the linkedISA conversion of datasets from Nature' Scientific Data online publication.

CONCLUSIONS

Our linked data approach has allowed us to: 1) make the ISA-Tab semantics explicit and machine-processable, 2) exploit the existing ontology-based annotations in the ISA-Tab experimental descriptions, 3) augment the ISA-Tab syntax with new descriptive elements, 4) visualise and query elements related to the experimental design. Reasoning over ISA-Tab metadata and associated data will facilitate data integration and knowledge discovery.

Guidelines for the design, analysis and interpretation of 'omics' data: focus on human endometrium

BACKGROUND

'Omics' high-throughput analyses, including genomics, epigenomics, transcriptomics, proteomics and metabolomics, are widely applied in human endometrial studies. Analysis of endometrial transcriptome patterns in physiological and pathophysiological conditions has been to date the most commonly applied 'omics' technique in human endometrium. As the technologies improve, proteomics holds the next big promise for this field. The 'omics' technologies have undoubtedly advanced our knowledge of human endometrium in relation to fertility and different diseases. Nevertheless, the challenges arising from the vast amount of data generated and the broad variation of 'omics' profiling according to different environments and stimuli make it difficult to assess the validity, reproducibility and interpretation of such 'omics' data. With the expansion of 'omics' analyses in the study of the endometrium, there is a growing need to develop guidelines for the design of studies, and the analysis and interpretation of 'omics' data.

METHODS

Systematic review of the literature in PubMed, and references from relevant articles were investigated up to March 2013.

RESULTS

The current review aims to provide guidelines for future 'omics' studies on human endometrium, together with a summary of the status and trends, promise and shortcomings in the high-throughput technologies. In addition, the approaches presented here can be adapted to other areas of high-throughput 'omics' studies.

CONCLUSION

A highly rigorous approach to future studies, based on the guidelines provided here, is a prerequisite for obtaining data on biological systems which can be shared among researchers worldwide and will ultimately be of clinical benefit.

Integrating data to acquire new knowledge: Three modes of integration in plant science

This paper discusses what it means and what it takes to integrate data in order to acquire new knowledge about biological entities and processes. Maureen O'Malley and Orkun Soyer have pointed to the scientific work involved in data integration as important and distinct from the work required by other forms of integration, such as methodological and explanatory integration, which have been more successful in captivating the attention of philosophers of science. Here I explore what data integration involves in more detail and with a focus on the role of data-sharing tools, like online databases, in facilitating this process; and I point to the philosophical implications of focusing on data as a unit of analysis. I then analyse three cases of data integration in the field of plant science, each of which highlights a different mode of integration: (1) inter-level integration, which involves data documenting different features of the same species, aims to acquire an interdisciplinary understanding of organisms as complex wholes and is exemplified by research on Arabidopsis thaliana; (2) cross-species integration, which involves data acquired on different species, aims to understand plant biology in all its different manifestations and is exemplified by research on Miscanthus giganteus; and (3) translational integration, which involves data acquired from sources within as well as outside academia, aims at the provision of interventions to improve human health (e.g. by sustaining the environment in which humans thrive) and is exemplified by research on Phytophtora ramorum. Recognising the differences between these efforts sheds light on the dynamics and diverse outcomes of data dissemination and integrative research; and the relations between the social and institutional roles of science, the development of data-sharing infrastructures and the production of scientific knowledge.

Comparative study of candidate housekeeping genes for quantification of target gene messenger RNA expression by real-time PCR in patients with inflammatory bowel disease

BACKGROUND

Mucosal expression of immunological mediators is modified in inflammatory bowel disease (IBD). Quantification of target gene messenger RNA (mRNA) transcripts depends on the normalization to a housekeeping or reference gene. Stability of housekeeping gene expression is critical for the accurate measurement of transcripts of the target gene. No studies have addressed the optimization of reference gene performance for mRNA studies in healthy intestinal mucosa and during mucosal inflammation.

METHODS

RNA was extracted from endoscopically obtained intestinal biopsies from healthy control subjects and patients with active IBD or non-IBD inflammatory diseases. Comparative analysis of 10 candidate housekeeping genes for quantitative real-time PCR was carried out according to predefined criteria, including use of the Web-based RefFinder platform.

RESULTS

We demonstrate that intestinal inflammation may significantly affect the stability of mucosal expression of housekeeping genes. Commonly used controls, such as glyceraldehyde-3-phosphate dehydrogenase, β-actin, or β2-microglobulin displayed high variability within the control group and/or between the healthy and inflamed mucosae. In contrast, we have identified novel genes with optimal stability, which may be used as appropriate housekeeping controls. The ribosomal proteins encoding genes (RPLPO and RPS9) were the most stable because their expression was not affected by interindividual differences, the presence of inflammation, or intestinal location. Normalization ofthe mRNA expression of mucosal tumor necrosis factor-α was highly dependent on the specific reference gene and varied significantly when normalized to genes with high or low stability.

CONCLUSIONS

Validation for optimal performance of the housekeeping gene is required for target mRNA quantification in healthy intestine and IBD-associated lesions. Suboptimal reference gene expression may explain conflicting results from published studies on IBD gene expression.

Toward More Transparent and Reproducible Omics Studies Through a Common Metadata Checklist and Data Publications

Biological processes are fundamentally driven by complex interactions between biomolecules. Integrated high-throughput omics studies enable multifaceted views of cells, organisms, or their communities. With the advent of new post-genomics technologies, omics studies are becoming increasingly prevalent; yet the full impact of these studies can only be realized through data harmonization, sharing, meta-analysis, and integrated research. These essential steps require consistent generation, capture, and distribution of metadata. To ensure transparency, facilitate data harmonization, and maximize reproducibility and usability of life sciences studies, we propose a simple common omics metadata checklist. The proposed checklist is built on the rich ontologies and standards already in use by the life sciences community. The checklist will serve as a common denominator to guide experimental design, capture important parameters, and be used as a standard format for stand-alone data publications. The omics metadata checklist and data publications will create efficient linkages between omics data and knowledge-based life sciences innovation and, importantly, allow for appropriate attribution to data generators and infrastructure science builders in the post-genomics era. We ask that the life sciences community test the proposed omics metadata checklist and data publications and provide feedback for their use and improvement.

New types of experimental data shape the use of enzyme kinetics for dynamic network modeling

Since the publication of Leonor Michaelis and Maude Menten's paper on the reaction kinetics of the enzyme invertase in 1913, molecular biology has evolved tremendously. New measurement techniques allow in vivo characterization of the whole genome, proteome or transcriptome of cells, whereas the classical enzyme essay only allows determination of the two Michaelis-Menten parameters V and K(m). Nevertheless, Michaelis-Menten kinetics are still commonly used, not only in the in vitro context of enzyme characterization but also as a rate law for enzymatic reactions in larger biochemical reaction networks. In this review, we give an overview of the historical development of kinetic rate laws originating from Michaelis-Menten kinetics over the past 100 years. Furthermore, we briefly summarize the experimental techniques used for the characterization of enzymes, and discuss web resources that systematically store kinetic parameters and related information. Finally, describe the novel opportunities that arise from using these data in dynamic mathematical modeling. In this framework, traditional in vitro approaches may be combined with modern genome-scale measurements to foster thorough understanding of the underlying complex mechanisms.

Challenges for an enzymatic reaction kinetics database

The scientific literature contains a tremendous amount of kinetic data describing the dynamic behaviour of biochemical reactions over time. These data are needed for computational modelling to create models of biochemical reaction networks and to obtain a better understanding of the processes in living cells. To extract the knowledge from the literature, biocurators are required to understand a paper and interpret the data. For modellers, as well as experimentalists, this process is very time consuming because the information is distributed across the publication and, in most cases, is insufficiently structured and often described without standard terminology. In recent years, biological databases for different data types have been developed. The advantages of these databases lie in their unified structure, searchability and the potential for augmented analysis by software, which supports the modelling process. We have developed the SABIO-RK database for biochemical reaction kinetics. In the present review, we describe the challenges for database developers and curators, beginning with an analysis of relevant publications up to the export of database information in a standardized format. The aim of the present review is to draw the experimentalist's attention to the problem (from a data integration point of view) of incompletely and imprecisely written publications. We describe how to lower the barrier to curators and improve this situation. At the same time, we are aware that curating experimental data takes time. There is a community concerned with making the task of publishing data with the proper structure and annotation to ontologies much easier. In this respect, we highlight some useful initiatives and tools.

Mobilizing and evaluating anticancer T cells: pitfalls and solutions

Immunotherapy is a promising means to fight cancer, prompting a steady increase in clinical trials and correlative laboratory studies in this field. As antitumor T cells play central roles in immunity against malignant diseases, most immunotherapeutic protocols aim to induce and/or strengthen their function. Various treatment strategies have elicited encouraging clinical responses; however, major challenges have been uncovered that should be addressed in order to fully exploit the potential of immunotherapy. Here, we outline pitfalls for the mobilization of antitumor T cells and offer solutions to improve their therapeutic efficacy. We provide a critical perspective on the main methodologies used to characterize T-cell responses to cancer therapies, with a focus on discrepancies between T-cell attributes measured in vitro and protective responses in vivo. This review altogether provides recommendations to optimize the design of future clinical trials and highlights important considerations for the proficient analysis of clinical specimens available for research.

Function of dynamic models in systems biology: linking structure to behaviour

BACKGROUND

Dynamic models in Systems Biology are used in computational simulation experiments for addressing biological questions. The complexity of the modelled biological systems and the growing number and size of the models calls for computer support for modelling and simulation in Systems Biology. This computer support has to be based on formal representations of relevant knowledge fragments.

RESULTS

In this paper we describe different functional aspects of dynamic models. This description is conceptually embedded in our "meaning facets" framework which systematises the interpretation of dynamic models in structural, functional and behavioural facets. Here we focus on how function links the structure and the behaviour of a model. Models play a specific role (teleological function) in the scientific process of finding explanations for dynamic phenomena. In order to fulfil this role a model has to be used in simulation experiments (pragmatical function). A simulation experiment always refers to a specific situation and a state of the model and the modelled system (conditional function). We claim that the function of dynamic models refers to both the simulation experiment executed by software (intrinsic function) and the biological experiment which produces the phenomena under investigation (extrinsic function). We use the presented conceptual framework for the function of dynamic models to review formal accounts for functional aspects of models in Systems Biology, such as checklists, ontologies, and formal languages. Furthermore, we identify missing formal accounts for some of the functional aspects. In order to fill one of these gaps we propose an ontology for the teleological function of models.

CONCLUSION

We have thoroughly analysed the role and use of models in Systems Biology. The resulting conceptual framework for the function of models is an important first step towards a comprehensive formal representation of the functional knowledge involved in the modelling and simulation process. Any progress in this area will in turn improve computer-supported modelling and simulation in Systems Biology.

Automated processing of zebrafish imaging data: a survey

Due to the relative transparency of its embryos and larvae, the zebrafish is an ideal model organism for bioimaging approaches in vertebrates. Novel microscope technologies allow the imaging of developmental processes in unprecedented detail, and they enable the use of complex image-based read-outs for high-throughput/high-content screening. Such applications can easily generate Terabytes of image data, the handling and analysis of which becomes a major bottleneck in extracting the targeted information. Here, we describe the current state of the art in computational image analysis in the zebrafish system. We discuss the challenges encountered when handling high-content image data, especially with regard to data quality, annotation, and storage. We survey methods for preprocessing image data for further analysis, and describe selected examples of automated image analysis, including the tracking of cells during embryogenesis, heartbeat detection, identification of dead embryos, recognition of tissues and anatomical landmarks, and quantification of behavioral patterns of adult fish. We review recent examples for applications using such methods, such as the comprehensive analysis of cell lineages during early development, the generation of a three-dimensional brain atlas of zebrafish larvae, and high-throughput drug screens based on movement patterns. Finally, we identify future challenges for the zebrafish image analysis community, notably those concerning the compatibility of algorithms and data formats for the assembly of modular analysis pipelines.

Deriving bio-equivalents from in vitro bioassays: assessment of existing uncertainties and strategies to improve accuracy and reporting

Bio-equivalents (e.g., 17β-estradiol or dioxin equivalents) are commonly employed to quantify the in vitro effects of complex human or environmental samples. However, there is no generally accepted data analysis strategy for estimating and reporting bio-equivalents. Therefore, the aims of the present study are to 1) identify common mathematical models for the derivation of bio-equivalents from the literature, 2) assess the ability of those models to correctly predict bio-equivalents, and 3) propose measures to reduce uncertainty in their calculation and reporting. We compiled a database of 234 publications that report bio-equivalents. From the database, we extracted 3 data analysis strategies commonly used to estimate bio-equivalents. These models are based on linear or nonlinear interpolation, and the comparison of effect concentrations (ECX ). To assess their accuracy, we employed simulated data sets in different scenarios. The results indicate that all models lead to a considerable misestimation of bio-equivalents if certain mathematical assumptions (e.g., goodness of fit, parallelism of dose-response curves) are violated. However, nonlinear interpolation is most suitable to predict bio-equivalents from single-point estimates. Regardless of the model, subsequent linear extrapolation of bio-equivalents generates additional inaccuracy if the prerequisite of parallel dose-response curves is not met. When all these factors are taken into consideration, it becomes clear that data analysis introduces considerable uncertainty in the derived bio-equivalents. To improve accuracy and transparency of bio-equivalents, we propose a novel data analysis strategy and a checklist for reporting Minimum Information about Bio-equivalent ESTimates (MIBEST).

LabTrove: a lightweight, web based, laboratory "blog" as a route towards a marked up record of work in a bioscience research laboratory

BACKGROUND

The electronic laboratory notebook (ELN) has the potential to replace the paper notebook with a marked-up digital record that can be searched and shared. However, it is a challenge to achieve these benefits without losing the usability and flexibility of traditional paper notebooks. We investigate a blog-based platform that addresses the issues associated with the development of a flexible system for recording scientific research.

METHODOLOGY/PRINCIPAL FINDINGS

We chose a blog-based approach with the journal characteristics of traditional notebooks in mind, recognizing the potential for linking together procedures, materials, samples, observations, data, and analysis reports. We implemented the LabTrove blog system as a server process written in PHP, using a MySQL database to persist posts and other research objects. We incorporated a metadata framework that is both extensible and flexible while promoting consistency and structure where appropriate. Our experience thus far is that LabTrove is capable of providing a successful electronic laboratory recording system.

CONCLUSIONS/SIGNIFICANCE

LabTrove implements a one-item one-post system, which enables us to uniquely identify each element of the research record, such as data, samples, and protocols. This unique association between a post and a research element affords advantages for monitoring the use of materials and samples and for inspecting research processes. The combination of the one-item one-post system, consistent metadata, and full-text search provides us with a much more effective record than a paper notebook. The LabTrove approach provides a route towards reconciling the tensions and challenges that lie ahead in working towards the long-term goals for ELNs. LabTrove, an electronic laboratory notebook (ELN) system from the Smart Research Framework, based on a blog-type framework with full access control, facilitates the scientific experimental recording requirements for reproducibility, reuse, repurposing, and redeployment.

Open data in public health surveillance systems: a case study using the French Sentinelles network

INTRODUCTION

Public Health Surveillance (PHS) produces an increasing number of health indicators. Exposing these data is at the core of interoperability; however no standard has yet been adopted for such information on the internet.

METHOD

Here, we compared two approaches to expose data from the French Sentinelles network, an information system focusing on communicable diseases surveillance in the general population. We implemented SDMX-HD (Statistical Data and Metadata Exchange-Health Domain), a standard supported by government agencies to exchange statistical data and OpenData (OData), a general purpose protocol proposed by Microsoft Corp. The same data were described using SDMX-HD (available at http://sdmx.sentiweb.fr) and using OData (http://odata.sentiweb.fr).

DISCUSSION

These two use cases proved the feasibility of opening public health data on the internet, and highlighted difficulties: SDMX, a full-featured solution, encouraged harmonization and reusability, sustainability, but required complex developments and tools; OData was much simpler to implement but required a "from scratch" description and did not encourage reusability. From an end-user perspective, integration in every-day tools is not achieved yet. These two approaches are a first step to interoperability in PHS.

EDAM: an ontology of bioinformatics operations, types of data and identifiers, topics and formats

MOTIVATION

Advancing the search, publication and integration of bioinformatics tools and resources demands consistent machine-understandable descriptions. A comprehensive ontology allowing such descriptions is therefore required.

RESULTS

EDAM is an ontology of bioinformatics operations (tool or workflow functions), types of data and identifiers, application domains and data formats. EDAM supports semantic annotation of diverse entities such as Web services, databases, programmatic libraries, standalone tools, interactive applications, data schemas, datasets and publications within bioinformatics. EDAM applies to organizing and finding suitable tools and data and to automating their integration into complex applications or workflows. It includes over 2200 defined concepts and has successfully been used for annotations and implementations.

AVAILABILITY

The latest stable version of EDAM is available in OWL format from http://edamontology.org/EDAM.owl and in OBO format from http://edamontology.org/EDAM.obo. It can be viewed online at the NCBO BioPortal and the EBI Ontology Lookup Service. For documentation and license please refer to http://edamontology.org. This article describes version 1.2 available at http://edamontology.org/EDAM_1.2.owl.

CONTACT

jison@ebi.ac.uk.

Quality control, analysis and secure sharing of Luminex® immunoassay data using the open source LabKey Server platform

BACKGROUND

Immunoassays that employ multiplexed bead arrays produce high information content per sample. Such assays are now frequently used to evaluate humoral responses in clinical trials. Integrated software is needed for the analysis, quality control, and secure sharing of the high volume of data produced by such multiplexed assays. Software that facilitates data exchange and provides flexibility to perform customized analyses (including multiple curve fits and visualizations of assay performance over time) could increase scientists' capacity to use these immunoassays to evaluate human clinical trials.

RESULTS

The HIV Vaccine Trials Network and the Statistical Center for HIV/AIDS Research and Prevention collaborated with LabKey Software to enhance the open source LabKey Server platform to facilitate workflows for multiplexed bead assays. This system now supports the management, analysis, quality control, and secure sharing of data from multiplexed immunoassays that leverage Luminex xMAP® technology. These assays may be custom or kit-based. Newly added features enable labs to: (i) import run data from spreadsheets output by Bio-Plex Manager™ software; (ii) customize data processing, curve fits, and algorithms through scripts written in common languages, such as R; (iii) select script-defined calculation options through a graphical user interface; (iv) collect custom metadata for each titration, analyte, run and batch of runs; (v) calculate dose-response curves for titrations; (vi) interpolate unknown concentrations from curves for titrated standards; (vii) flag run data for exclusion from analysis; (viii) track quality control metrics across runs using Levey-Jennings plots; and (ix) automatically flag outliers based on expected values. Existing system features allow researchers to analyze, integrate, visualize, export and securely share their data, as well as to construct custom user interfaces and workflows.

CONCLUSIONS

Unlike other tools tailored for Luminex immunoassays, LabKey Server allows labs to customize their Luminex analyses using scripting while still presenting users with a single, graphical interface for processing and analyzing data. The LabKey Server system also stands out among Luminex tools for enabling smooth, secure transfer of data, quality control information, and analyses between collaborators. LabKey Server and its Luminex features are freely available as open source software at http://www.labkey.com under the Apache 2.0 license.

Towards the collaborative curation of the registry underlying Identifiers.org

The MIRIAM Registry (http://www.ebi.ac.uk/miriam/) records information about collections of data in the life sciences, as well as where it can be obtained. This information is used, in combination with the resolving infrastructure of Identifiers.org (http://identifiers.org/), to generate globally unique identifiers, in the form of Uniform Resource Identifier. These identifiers are now widely used to provide perennial cross-references and annotations. The growing demand for these identifiers results in a significant increase in curational efforts to maintain the underlying registry. This requires the design and implementation of an economically viable and sustainable solution able to cope with such expansion. We briefly describe the Registry, the current curation duties entailed, and our plans to extend and distribute this workload through collaborative and community efforts.

The minimum information required for a glycomics experiment (MIRAGE) project: improving the standards for reporting mass-spectrometry-based glycoanalytic data

The MIRAGE guidelines are being developed in response to a critical need in the glycobiology community to clarify glycoanalytic results so that they are more readily evaluated (in terms of their scope and depth) and to facilitate the reproduction of important results in the laboratory. The molecular and biological complexity of the glycosylation process makes thorough reporting of the results of a glycomics experiment a highly challenging endeavor. The resulting data specify the identity and quantity of complex structures, the precise molecular features of which are sometimes inferred using prior knowledge, such as familiarity with a particular biosynthetic mechanism. Specifying the exact methods and assumptions that were used to assign and quantify reported structures allows the interested scientist to appreciate the scope and depth of the analysis. Mass spectrometry (MS) is the most widely used tool for glycomics experiments. The interpretation and reproducibility of MS-based glycomics data depend on comprehensive meta-data describing the instrumentation, instrument setup, and data acquisition protocols. The MIRAGE guidelines for MS-based glycomics have been designed to facilitate the collection and sharing of this critical information in order to assist the glycoanalyst in generating data sets with maximum information content and biological relevance.

The ToxBank Data Warehouse: Supporting the Replacement of In Vivo Repeated Dose Systemic Toxicity Testing

The aim of the SEURAT-1 (Safety Evaluation Ultimately Replacing Animal Testing-1) research cluster, comprised of seven EU FP7 Health projects co-financed by Cosmetics Europe, is to generate a proof-of-concept to show how the latest technologies, systems toxicology and toxicogenomics can be combined to deliver a test replacement for repeated dose systemic toxicity testing on animals. The SEURAT-1 strategy is to adopt a mode-of-action framework to describe repeated dose toxicity, combining in vitro and in silico methods to derive predictions of in vivo toxicity responses. ToxBank is the cross-cluster infrastructure project whose activities include the development of a data warehouse to provide a web-accessible shared repository of research data and protocols, a physical compounds repository, reference or "gold compounds" for use across the cluster (available via wiki.toxbank.net), and a reference resource for biomaterials. Core technologies used in the data warehouse include the ISA-Tab universal data exchange format, REpresentational State Transfer (REST) web services, the W3C Resource Description Framework (RDF) and the OpenTox standards. We describe the design of the data warehouse based on cluster requirements, the implementation based on open standards, and finally the underlying concepts and initial results of a data analysis utilizing public data related to the gold compounds.

Ancillary study management systems: a review of needs

BACKGROUND

The valuable clinical data, specimens, and assay results collected during a primary clinical trial or observational study can enable researchers to answer additional, pressing questions with relatively small investments in new measurements. However, management of such follow-on, "ancillary" studies is complex. It requires coordinating across institutions, sites, repositories, and approval boards, as well as distributing, integrating, and analyzing diverse data types. General-purpose software systems that simplify the management of ancillary studies have not yet been explored in the research literature.

METHODS

We have identified requirements for ancillary study management primarily as part of our ongoing work with a number of large research consortia. These organizations include the Center for HIV/AIDS Vaccine Immunology (CHAVI), the Immune Tolerance Network (ITN), the HIV Vaccine Trials Network (HVTN), the U.S. Military HIV Research Program (MHRP), and the Network for Pancreatic Organ Donors with Diabetes (nPOD). We also consulted with researchers at a range of other disease research organizations regarding their workflows and data management strategies. Lastly, to enhance breadth, we reviewed process documents for ancillary study management from other organizations.

RESULTS

By exploring characteristics of ancillary studies, we identify differentiating requirements and scenarios for ancillary study management systems (ASMSs). Distinguishing characteristics of ancillary studies may include the collection of additional measurements (particularly new analyses of existing specimens); the initiation of studies by investigators unaffiliated with the original study; cross-protocol data pooling and analysis; pre-existing participant consent; and pre-existing data context and provenance. For an ASMS to address these characteristics, it would need to address both operational requirements (e.g., allocating existing specimens) and data management requirements (e.g., securely distributing and integrating primary and ancillary data).

CONCLUSIONS

The scenarios and requirements we describe can help guide the development of systems that make conducting ancillary studies easier, less expensive, and less error-prone. Given the relatively consistent characteristics and challenges of ancillary study management, general-purpose ASMSs are likely to be useful to a wide range of organizations. Using the requirements identified in this paper, we are currently developing an open-source, general-purpose ASMS based on LabKey Server (http://www.labkey.org) in collaboration with CHAVI, the ITN and nPOD.

Controlled annotations for systems biology

The aim of this chapter is to provide sufficient information to enable a reader, new to the subject of Systems Biology, to create and use effectively controlled annotations, using resolvable Identifiers.org Uniform Resource Identifiers (URIs). The text details the underlying requirements that have led to the development of such an identification scheme and infrastructure, the principles that underpin its syntax and the benefits derived through its use. It also places into context the relationship with other standardization efforts, how it differs from other pre-existing identification schemes, recent improvements to the system, as well as those that are planned in the future. Throughout, the reader is provided with explicit examples of use and directed to supplementary information where necessary.

Real-time quantitative PCR, pathogen detection and MIQE

Nucleic acids are the ultimate biomarker and real-time PCR (qPCR) is firmly established as the method of choice for nucleic acid detection. Together, they allow the accurate, sensitive and specific identification of pathogens, and the use of qPCR has become routine in diagnostic laboratories. The reliability of qPCR-based assays relies on a combination of optimal sample selection, assay design and validation as well as appropriate data analysis and the "Minimal Information for the Publication of real-time PCR" (MIQE) guidelines aim to improve both the reliability of assay design as well as the transparency of reporting, essential conditions if qPCR is to remain the benchmark technology for molecular diagnosis.

Threats to validity in the design and conduct of preclinical efficacy studies: a systematic review of guidelines for in vivo animal experiments

BACKGROUND

The vast majority of medical interventions introduced into clinical development prove unsafe or ineffective. One prominent explanation for the dismal success rate is flawed preclinical research. We conducted a systematic review of preclinical research guidelines and organized recommendations according to the type of validity threat (internal, construct, or external) or programmatic research activity they primarily address.

METHODS AND FINDINGS

We searched MEDLINE, Google Scholar, Google, and the EQUATOR Network website for all preclinical guideline documents published up to April 9, 2013 that addressed the design and conduct of in vivo animal experiments aimed at supporting clinical translation. To be eligible, documents had to provide guidance on the design or execution of preclinical animal experiments and represent the aggregated consensus of four or more investigators. Data from included guidelines were independently extracted by two individuals for discrete recommendations on the design and implementation of preclinical efficacy studies. These recommendations were then organized according to the type of validity threat they addressed. A total of 2,029 citations were identified through our search strategy. From these, we identified 26 guidelines that met our eligibility criteria--most of which were directed at neurological or cerebrovascular drug development. Together, these guidelines offered 55 different recommendations. Some of the most common recommendations included performance of a power calculation to determine sample size, randomized treatment allocation, and characterization of disease phenotype in the animal model prior to experimentation.

CONCLUSIONS

By identifying the most recurrent recommendations among preclinical guidelines, we provide a starting point for developing preclinical guidelines in other disease domains. We also provide a basis for the study and evaluation of preclinical research practice. Please see later in the article for the Editors' Summary.