Design and Laboratory Implementation of Web Application for Collaboratively Setting Reference Intervals

BACKGROUND: Although the same equipment and reagents can be employed for inspecting identical samples, the setting and verification methods for the corresponding reference intervals differ from each other, and such methods are not well established. To address the issues associated with establishing and validating reference intervals, a Web-based application is proposed for collaboratively setting reference intervals. METHODS: A Web application was designed for automatically providing the statistical results associated with a reference interval upon receiving the corresponding test results from participating institutions and incorporating the cumulative data. RESULTS: By employing the proposed Web-based application (www.referencerange.org), reference intervals can be collaboratively set based on objective and statistical analyses incorporating clinical chemistry results obtained from Korea Healthcare Association in the years 2016 and 2017. Cumulative data obtained from the existing input peer group associated with an inspection are updated in real time, and the current set reference interval is displayed in real time. CONCLUSIONS: In this study, a Web-based application is designed for collaboratively setting reference intervals whereby all Korean laboratories can easily participate, collectively set reference intervals, and apply the set reference intervals. Hence, the proposed application can aid in providing basic data associated with health information.

COEX-Seq: Convert a Variety of Measurements of Gene Expression in RNA-Seq

Next generation sequencing (NGS), a high-throughput DNA sequencing technology, is widely used for molecular biological studies. In NGS, RNA-sequencing (RNA-Seq), which is a short-read massively parallel sequencing, is a major quantitative transcriptome tool for different transcriptome studies. To utilize the RNA-Seq data, various quantification and analysis methods have been developed to solve specific research goals, including identification of differentially expressed genes and detection of novel transcripts. Because of the accumulation of RNA-Seq data in the public databases, there is a demand for integrative analysis. However, the available RNA-Seq data are stored in different formats such as read count, transcripts per million, and fragments per kilobase million. This hinders the integrative analysis of the RNA-Seq data. To solve this problem, we have developed a web-based application using Shiny, COEX-seq (Convert a Variety of Measurements of Gene Expression in RNA-Seq) that easily converts data in a variety of measurement formats of gene expression used in most bioinformatic tools for RNA-Seq. It provides a workflow that includes loading data set, selecting measurement formats of gene expression, and identifying gene names. COEX-seq is freely available for academic purposes and can be run on Windows, Mac OS, and Linux operating systems. Source code, sample data sets, and supplementary documentation are available as well.