Dataset Information

A Practical Guide to Visualization and Statistical Analysis of R. solanacearum Infection Data Using R.

ABSTRACT: This paper describes and summarizes approaches for visualization and statistical analysis using data from Ralstonia solanacearum infection experiments based on methods and concepts that are broadly applicable. Members of the R. solanacearum species complex cause bacterial wilt disease. Bacterial wilt is a lethal plant disease and has been studied for over 100 years. During this time various methods to quantify disease and different ways to analyze the generated data have been employed. Here, I aim to provide a general background on three distinct and commonly used measures of disease: the area under the disease progression curve, longitudinal recordings of disease severity and host survival. I will discuss how one can proceed with visualization, statistical analysis, and interpretation using different datasets while revisiting the general concepts of statistical analysis. Datasets and R code to perform all analyses discussed here are included in the supplement.

SUBMITTER: Schandry N

PROVIDER: S-EPMC5401893 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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A Practical Guide to Visualization and Statistical Analysis of R. solanacearum Infection Data Using R.

Schandry Niklas N

Frontiers in plant science 20170424

This paper describes and summarizes approaches for visualization and statistical analysis using data from Ralstonia solanacearum infection experiments based on methods and concepts that are broadly applicable. Members of the R. solanacearum species complex cause bacterial wilt disease. Bacterial wilt is a lethal plant disease and has been studied for over 100 years. During this time various methods to quantify disease and different ways to analyze the generated data have been emplo ...[more]

PMID: 28484483

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Project description:BACKGROUND:Shifts in data sharing policy have increased researchers' access to individual participant data (IPD) from clinical studies. Simultaneously the number of IPD meta-analyses (IPDMAs) is increasing. However, rates of data retrieval have not improved. Our goal was to describe the challenges of retrieving IPD for an IPDMA and provide practical guidance on obtaining and managing datasets based on a review of the literature and practical examples and observations. METHODS:We systematically searched MEDLINE, Embase, and the Cochrane Library, until January 2019, to identify publications focused on strategies to obtain IPD. In addition, we searched pharmaceutical websites and contacted industry organizations for supplemental information pertaining to recent advances in industry policy and practice. Finally, we documented setbacks and solutions encountered while completing a comprehensive IPDMA and drew on previous experiences related to seeking and using IPD. RESULTS:Our scoping review identified 16 articles directly relevant for the conduct of IPDMAs. We present short descriptions of these articles alongside overviews of IPD sharing policies and procedures of pharmaceutical companies which display certification of Principles for Responsible Clinical Trial Data Sharing via Pharmaceutical Research and Manufacturers of America or European Federation of Pharmaceutical Industries and Associations websites. Advances in data sharing policy and practice affected the way in which data is requested, obtained, stored and analyzed. For our IPDMA it took 6.5?years to collect and analyze relevant IPD and navigate additional administrative barriers. Delays in obtaining data were largely due to challenges in communication with study sponsors, frequent changes in data sharing policies of study sponsors, and the requirement for a diverse skillset related to research, administrative, statistical and legal issues. CONCLUSIONS:Knowledge of current data sharing practices and platforms as well as anticipation of necessary tasks and potential obstacles may reduce time and resources required for obtaining and managing data for an IPDMA. Sufficient project funding and timeline flexibility are pre-requisites for successful collection and analysis of IPD. IPDMA researchers must acknowledge the additional and unexpected responsibility they are placing on corresponding study authors or data sharing administrators and should offer assistance in readying data for sharing.

Dataset Information

A Practical Guide to Visualization and Statistical Analysis of R. solanacearum Infection Data Using R.

Publications

A Practical Guide to Visualization and Statistical Analysis of <i>R. solanacearum</i> Infection Data Using R.

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