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Updated: Aug 19, 2026

A Complete Pipeline for Isolating and Sequencing MicroRNAs, and Analyzing Them Using Open Source Tools
Published on: August 21, 2019
MiRQuery: a user-friendly web app for the interactive analysis and visualization of microRNA sequencing data
Julianne C Yang1, Jake Sauter2, Gregory C Adam1
1Quantitative Biosciences, Merck & Co., Inc., 770 Sumneytown Pike, West Point, PA, 19846, USA.
Background:
MicroRNAs (miRNAs) are a class of small noncoding RNAs that inhibit the translation of target messenger RNAs (mRNAs). Given that a single miRNA can regulate the translation of many mRNAs, miRNAs have emerged as critical regulators of physiological processes. MiRNAs have been linked to the development and progression of cancers, neurodegenerative and other diseases, most recently using high-throughput miRNA "miRNome" sequencing. As miRNome sequencing represents a newer 'omics application, limited guidance is available for how to analyze this data. Existing interfaces that enable non-computational users to interpret and perform comprehensive secondary analysis on their own miRNome data are limited in functionality and/or interactivity. Therefore, we developed MiRQuery to address this need.
Results:
MiRQuery is an RShiny application which features common visualization methods for high-throughput sequencing data, such as multidimensional scaling, stacked column charts, heatmaps, and boxplots to compare expression across groups for a user-specified miRNA of interest. MiRQuery further provides support for differential miRNA and gene expression analysis. Unique to miRNome sequencing data analysis, users may retrieve predicted gene targets of differentially expressed miRNA and follow up with pathway overrepresentation analysis of the gene targets. Finally, if users upload paired bulk mRNA sequencing data, they may identify differentially expressed genes and negatively correlated miRNA-gene pairs.
Conclusions:
By providing access to sophisticated bioinformatics tools through a user-friendly interface, MiRQuery empowers both scientists new to bioinformatics and bioinformaticians new to the field to extract insights rapidly and reproducibly from their sequencing data. MiRQuery can be accessed through PositConnect at https://julianneyang-mirquery.share.connect.posit.cloud/ , and alternatively is available by user local installation via instructions on the Github project homepage.
