Dataset Information

Rcupcake: an R package for querying and analyzing biomedical data through the BD2K PIC-SURE RESTful API.

ABSTRACT: Motivation:In the era of big data and precision medicine, the number of databases containing clinical, environmental, self-reported and biochemical variables is increasing exponentially. Enabling the experts to focus on their research questions rather than on computational data management, access and analysis is one of the most significant challenges nowadays. Results:We present Rcupcake, an R package that contains a variety of functions for leveraging different databases through the BD2K PIC-SURE RESTful API and facilitating its query, analysis and interpretation. The package offers a variety of analysis and visualization tools, including the study of the phenotype co-occurrence and prevalence, according to multiple layers of data, such as phenome, exposome or genome. Availability and implementation:The package is implemented in R and is available under Mozilla v2 license from GitHub (https://github.com/hms-dbmi/Rcupcake). Two reproducible case studies are also available (https://github.com/hms-dbmi/Rcupcake-case-studies/blob/master/SSCcaseStudy_v01.ipynb, https://github.com/hms-dbmi/Rcupcake-case-studies/blob/master/NHANEScaseStudy_v01.ipynb). Contact:paul_avillach@hms.harvard.edu. Supplementary information:Supplementary data are available at Bioinformatics online.

SUBMITTER: Gutierrez-Sacristan A

PROVIDER: S-EPMC5905576 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Rcupcake: an R package for querying and analyzing biomedical data through the BD2K PIC-SURE RESTful API.

Gutiérrez-Sacristán Alba A Guedj Romain R Korodi Gabor G Stedman Jason J Furlong Laura I LI Patel Chirag J CJ Kohane Isaac S IS Avillach Paul P

Bioinformatics (Oxford, England) 20180401 8

<h4>Motivation</h4>In the era of big data and precision medicine, the number of databases containing clinical, environmental, self-reported and biochemical variables is increasing exponentially. Enabling the experts to focus on their research questions rather than on computational data management, access and analysis is one of the most significant challenges nowadays.<h4>Results</h4>We present Rcupcake, an R package that contains a variety of functions for leveraging different databases through ...[more]

PMID: 29267850

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Project description:BackgroundIn medical informatics, psychology, market research and many other fields, researchers often need to analyze and model ranking data. However, there is no statistical software that provides tools for the comprehensive analysis of ranking data. Here, we present pmr, an R package for analyzing and modeling ranking data with a bundle of tools. The pmr package enables descriptive statistics (mean rank, pairwise frequencies, and marginal matrix), Analytic Hierarchy Process models (with Saaty's and Koczkodaj's inconsistencies), probability models (Luce model, distance-based model, and rank-ordered logit model), and the visualization of ranking data with multidimensional preference analysis.ResultsExamples of the use of package pmr are given using a real ranking dataset from medical informatics, in which 566 Hong Kong physicians ranked the top five incentives (1: competitive pressures; 2: increased savings; 3: government regulation; 4: improved efficiency; 5: improved quality care; 6: patient demand; 7: financial incentives) to the computerization of clinical practice. The mean rank showed that item 4 is the most preferred item and item 3 is the least preferred item, and significance difference was found between physicians' preferences with respect to their monthly income. A multidimensional preference analysis identified two dimensions that explain 42% of the total variance. The first can be interpreted as the overall preference of the seven items (labeled as "internal/external"), and the second dimension can be interpreted as their overall variance of (labeled as "push/pull factors"). Various statistical models were fitted, and the best were found to be weighted distance-based models with Spearman's footrule distance.ConclusionsIn this paper, we presented the R package pmr, the first package for analyzing and modeling ranking data. The package provides insight to users through descriptive statistics of ranking data. Users can also visualize ranking data by applying a thought multidimensional preference analysis. Various probability models for ranking data are also included, allowing users to choose that which is most suitable to their specific situations.

Dataset Information

Rcupcake: an R package for querying and analyzing biomedical data through the BD2K PIC-SURE RESTful API.

Publications

Rcupcake: an R package for querying and analyzing biomedical data through the BD2K PIC-SURE RESTful API.

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