Proficiency testing of virus diagnostics based on bioinformatics analysis of simulated in silico high-throughput sequencing data sets

Quality management and independent assessment of high-throughput sequencing-based virus diagnostics have not yet been established as a mandatory approach for ensuring comparable results. The sensitivity and specificity of viral high-throughput sequence data analysis are highly affected by bioinformatics processing using publicly available and custom tools and databases and thus differ widely between individuals and institutions. Here we present the results of the COMPARE [Collaborative Management Platform for Detection and Analyses of (Re-) emerging and Foodborne Outbreaks in Europe] in silico virus proficiency test. An artificial, simulated in silico data set of Illumina HiSeq sequences was provided to 13 different European institutes for bioinformatics analysis to identify viral pathogens in high-throughput sequence data. Comparison of the participants’ analyses shows that the use of different tools, programs, and databases for bioinformatics analyses can impact the correct identification of viral sequences from a simple data set. The identification of slightly mutated and highly divergent virus genomes has been shown to be most challenging. Furthermore, the interpretation of the results, together with a fictitious case report, by the participants showed that in addition to the bioinformatics analysis, the virological evaluation of the results can be important in clinical settings. External quality assessment and proficiency testing should become an important part of validating high-throughput sequencing-based virus diagnostics and could improve the harmonization, comparability, and reproducibility of results. There is a need for the establishment of international proficiency testing, like that established for conventional laboratory tests such as PCR, for bioinformatics pipelines and the interpretation of such results

A previously undescribed highly prevalent phage identified in a Danish Enteric Virome Catalog

Gut viruses are important, yet often neglected, players in the complex human gut microbial ecosystem. Recently, the number of human gut virome studies has been increasing; however, we are still only scratching the surface of the immense viral diversity. In this study, 254 virus-enriched fecal metagenomes from 204 Danish subjects were used to generate the anish nteric irme atalog (DEVoC) containing 12,986 nonredundant viral scaffolds, of which the majority was previously undescribed, encoding 190,029 viral genes. The DEVoC was used to compare 91 healthy DEVoC gut viromes from children, adolescents, and adults that were used to create the DEVoC. Gut viromes of healthy Danish subjects were dominated by phages. While most phage genomes (PGs) only occurred in a single subject, indicating large virome individuality, 39 PGs were present in more than 10 healthy subjects. Among these 39 PGs, the prevalences of three PGs were associated with age. To further study the prevalence of these 39 prevalent PGs, 1,880 gut virome data sets of 27 studies from across the world were screened, revealing several age-, geography-, and disease-related prevalence patterns. Two PGs also showed a remarkably high prevalence worldwide - a crAss-like phage (20.6% prevalence), belonging to the tentative subfamily, and a previously undescribed circular temperate phage infecting Bacteroides dorei (14.4% prevalence), called LoVEphage because it encodes ots f iral lements. Due to the LoVEphage's high prevalence and novelty, public data sets in which the LoVEphage was detected were assembled, resulting in an additional 18 circular LoVEphage-like genomes (67.9 to 72.4 kb)

Repurposing NGO data for better research outcomes: A scoping review of the use and secondary analysis of NGO data in health policy and systems research

Background Non-government organisations (NGOs) collect and generate vast amounts of potentially rich data, most of which are not used for research purposes. Secondary analysis of NGO data (their use and analysis in a study for which they were not originally collected) presents an important but largely unrealised opportunity to provide new research insights in critical areas including the evaluation of health policy and programmes. Methods A scoping review of the published literature was performed to identify the extent to which secondary analysis of NGO data has been used in health policy and systems research (HPSR). A tiered analytic approach provided a comprehensive overview and descriptive analyses of the studies which: 1) used data produced or collected by or about NGOs; 2) performed secondary analysis of the NGO data (beyond use of an NGO report as a supporting reference); 3) used NGO-collected clinical data. Results Of the 156 studies which performed secondary analysis of NGO-produced or collected data, 64% (n=100) used NGO-produced reports (e.g. to critique NGO activities and as a contextual reference) and 8% (n=13) analysed NGO-collected clinical data.. Of the studies, 55% investigated service delivery research topics, with 48% undertaken in developing countries and 17% in both developing and developed. NGO-collected clinical data enabled HPSR within marginalised groups (e.g. migrants, people in conflict-affected areas), with some limitations such as inconsistencies and missing data. Conclusion We found evidence that NGO-collected and produced data are most commonly perceived as a source of supporting evidence for HPSR and not as primary source data. However, these data can facilitate research in under-researched marginalised groups and in contexts that are hard to reach by academics, such as conflict-affected areas. NGO–academic collaboration could help address issues of NGO data quality to facilitate their more widespread use in research. Their use could enable relevant and timely research in the areas of health policy, programme evaluation and advocacy to improve health and reduce health inequalities, especially in marginalised groups and developing countries

Proficiency Testing of Virus Diagnostics Based on Bioinformatics Analysis of Simulated In Silico High-Throughput Sequencing Data Sets

Quality management and independent assessment of high-throughput sequencing-based virus diagnostics have not yet been established as a mandatory approach for ensuring comparable results. The sensitivity and specificity of viral high-throughput sequence data analysis are highly affected by bioinformatics processing using publicly available and custom tools and databases and thus differ widely between individuals and institutions. Here we present the results of the COMPARE [Collaborative Management Platform for Detection and Analyses of (Re-) emerging and Foodborne Outbreaks in Europe] in silico virus proficiency test. An artificial, simulated in silico data set of Illumina HiSeq sequences was provided to 13 different European institutes for bioinformatics analysis to identify viral pathogens in high-throughput sequence data. Comparison of the participants’ analyses shows that the use of different tools, programs, and databases for bioinformatics analyses can impact the correct identification of viral sequences from a simple data set. The identification of slightly mutated and highly divergent virus genomes has been shown to be most challenging. Furthermore, the interpretation of the results, together with a fictitious case report, by the participants showed that in addition to the bioinformatics analysis, the virological evaluation of the results can be important in clinical settings. External quality assessment and proficiency testing should become an important part of validating high-throughput sequencing-based virus diagnostics and could improve the harmonization, comparability, and reproducibility of results. There is a need for the establishment of international proficiency testing, like that established for conventional laboratory tests such as PCR, for bioinformatics pipelines and the interpretation of such results

Adolescent suicidal ideation: a comparison of incarcerated and school-based samples

and risk-taking behavior. RESULTS: Suicidal ideations during the past year were reported by 21.5% of detained males, compared to 6.7% in the general population. In females, 58.1% of detained individuals reported suicidal thoughts during the past year, compared to 14.4% of the general population. In girls and boys from the general population, both internalizing and externalizing problems were higher in suicidal ideators than in non-suicidal youth, while in the detention group mainly internalizing problems were higher in suicidal ideators. When comparing detention suicidal ideators with those from the general population, male suicidal ideators scored higher on delinquency, while detained female suicidal ideators also scored higher on posttraumatic stress, but lower on prosocial beliefs. LIMITATIONS: Information used in this study was solely based on self-report measures only and limited to Flemish adolescents. CONCLUSION: Since suicidal ideation is a frequent problem in detained youth, adequate recognition and treatment seems clinically relevant. While both internalizing and externalizing psychopathology may be an indicator of suicidal ideation in the general population, internalizing problems may be the main clinical predictor in detained yout

NCBI’s virus discovery codeathon: building “FIVE” —the Federated Index of Viral Experiments API index

Viruses represent important test cases for data federation due to their genome size and the rapid increase in sequence data in publicly available databases. However, some consequences of previously decentralized (unfederated) data are lack of consensus or comparisons between feature annotations. Unifying or displaying alternative annotations should be a priority both for communities with robust entry representation and for nascent communities with burgeoning data sources. To this end, during this three-day continuation of the Virus Hunting Toolkit codeathon series (VHT-2), a new integrated and federated viral index was elaborated. This Federated Index of Viral Experiments (FIVE) integrates pre-existing and novel functional and taxonomy annotations and virus–host pairings. Variability in the context of viral genomic diversity is often overlooked in virus databases. As a proof-of-concept, FIVE was the first attempt to include viral genome variation for HIV, the most well-studied human pathogen, through viral genome diversity graphs. As per the publication of this manuscript, FIVE is the first implementation of a virus-specific federated index of such scope. FIVE is coded in BigQuery for optimal access of large quantities of data and is publicly accessible. Many projects of database or index federation fail to provide easier alternatives to access or query information. To this end, a Python API query system was developed to enhance the accessibility of FIVE