seqQscorer: automated quality control of next-generation sequencing data using machine learning

Controlling quality of next-generation sequencing (NGS) data files is a necessary but complex task. To address this problem, we statistically characterize common NGS quality features and develop a novel quality control procedure involving tree-based and deep learning classification algorithms. Predictive models, validated on internal and external functional genomics datasets, are to some extent generalizable to data from unseen species. The derived statistical guidelines and predictive models represent a valuable resource for users of NGS data to better understand quality issues and perform automatic quality control. Our guidelines and software are available at https://github.com/salbrec/seqQscorer.

Statisticians as Back-office Policy-makers: Counting Asylum-Seekers and Refugees in Europe

Street-level bureaucracy literature ascertains that policies get made not only in the offices of legislatures or politicians but through the discretion bureaucrats employ in their day-to-day interactions with citizens in government agencies. The discretion bureaucrats use to grant access to public benefits or impose sanctions adds up to what the public ultimately experience as the government and its policies. This perspective, however, overlooks policy-making that gets done in the back offices of government, where there might not be direct interaction with citizens. Furthermore, it treats discretion as inherently anthropogenic and ignores that it is exercised in relation to sociotechnical arrangements of which bureaucrats are a part. In this paper, based on extensive ethnography at national statistical institutes and international statistical meetings across Europe, I make two arguments. The first is that, statisticians emerge as back-office policy-makers as they are compelled to take multiple methodological decisions when operationalizing abstract statistical guidelines and definitions, thus effectively making rather than merely implementing policies. This is the “discretion” they employ, even when they may not interact with citizens. The second argument is that the exercise of discretion is sociotechnical, that is, it happens in relation to the constraints and affordances of technologies and the decisions of other bureaucrats in their institutions and others.

Automated quality control of next generation sequencing data using machine learning

Controlling quality of next generation sequencing (NGS) data files is a necessary but complex task. To address this problem, we statistically characterized common NGS quality features and developed a novel quality control procedure involving tree-based and deep learning classification algorithms. Predictive models, validated on internal data and external disease diagnostic datasets, are to some extent generalizable to data from unseen species. The derived statistical guidelines and predictive models represent a valuable resource for users of NGS data to better understand quality issues and perform automatic quality control. Our guidelines and software are available at the following URL: https://github.com/salbrec/seqQscorer.

The benefits of collaboration: the Nordic Arthroplasty Register Association

The Nordic Arthroplasty Register Association (NARA) was established in 2007 by arthroplasty register representatives from Sweden, Norway and Denmark with the overall aim to improve the quality of research and thereby enhance the possibility for quality improvement with arthroplasty surgery. Finland joined the NARA collaboration in 2010. NARA minimal hip, knee and shoulder datasets were created with variables that all countries can deliver. They are dynamic datasets, currently with 25 variables for hip arthroplasty, 20 for knee arthroplasty and 20 for shoulder arthroplasty. NARA has published statistical guidelines for the analysis of arthroplasty register data. The association is continuously working on the improvement of statistical methods and the application of new ones. There are 31 published peer-reviewed papers based on the NARA databases and 20 ongoing projects in different phases. Several NARA publications have significantly affected clinical practice. For example, metal-on-metal total hip arthroplasty and resurfacing arthroplasty have been abandoned due to increased revision risk based on i.a. NARA reports. Further, the use of uncemented total hip arthroplasty in elderly patients has decreased significantly, especially in Finland, based on the NARA data. The NARA collaboration has been successful because the countries were able to agree on a common dataset and variable definitions. The collaboration was also successful because the group was able to initiate a number of research projects and provide answers to clinically relevant questions. A number of specific goals, set up in 2007, have been achieved and new one has emerged in the process. Cite this article: EFORT Open Rev 2019;4 DOI: 10.1302/2058-5241.4.180058

Evaluating the Effectiveness of Complex, Multi-component, Dynamic, Community-Based Injury Prevention Interventions: A Statistical Framework

Dynamic violence and injury prevention interventions located within community settings raise evaluation challenges by virtue of their complex structure, focus, and aims. They try to address many risk factors simultaneously, are often overlapped in their implementation, and their implementation may be phased over time. This article proposes a statistical and analytic framework for evaluating the effectiveness of multilevel, multisystem, multi-component, community-driven, dynamic interventions. The proposed framework builds on meta regression methodology and recently proposed approaches for pooling results from multi-component intervention studies. The methodology is applied to the evaluation of the effectiveness of South African community-centered injury prevention and safety promotion interventions. The proposed framework allows for complex interventions to be disaggregated into their constituent parts in order to extract their specific effects. The potential utility of the framework is successfully illustrated using contact crime data from select police stations in Johannesburg. The proposed framework and statistical guidelines proved to be useful to study the effectiveness of complex, dynamic, community-based interventions as a whole and of their components. The framework may help researchers and policy makers to adopt and study a specific methodology for evaluating the effectiveness of complex intervention programs.