miRcomp-Shiny: Interactive assessment of qPCR-based microRNA quantification and quality control algorithms

Implementation

We have developed a Shiny (http://shiny.rstudio.com/) interface to the miRcomp R package (version ≥ 1.3.3). Currently, six of the most widely-used algorithms to estimate miRNA expression and sample quality are included in the miRcomp-Shiny app. Each method provides both expression estimates and quality metrics. Assessments can be performed on individual algorithms, or two available algorithms can be compared. Researchers can also upload the results from their own method to be assessed. As new methods are developed and tested, we will continue to add these methods to miRcomp-Shiny. The development of a repository of qPCR-based miRNA expression estimation algorithms will be a valuable resource for researchers seeking to develop new methodology or comparison existing algorithms across a wide variety of assessment criteria.

Advantages of an interactive interface to the miRcomp package

The web application framework in R (Shiny) has enabled us to make several aspects of the miRcomp package more interactive than they were previously and facilitate comparisons that would have been difficult to make in R. Below we describe two common use cases that motivated the development of miRcomp-Shiny.

Methodology and quality threshold selection

When selecting methodology to analyze a data set, miRcomp-Shiny can be used to evaluate the performance of existing methods based on the benchmark data. The results of these evaluations can be used to guide the selection of an expression estimation algorithm and quality threshold based on the assessments most relevant to the user’s experiment. Additionally, one can examine the effect of changing quality thresholds on the performance of each method. The result of changes in the quality threshold are then displayed immediately for each assessment. This is particularly useful when selecting a quality threshold for one’s own data.

Comparison of novel algorithms with current methods

Another use case is comparison of a new method to an existing method. By providing current methods for comparison, researchers do not have to implement these algorithms themselves, which is often a substantial bottleneck in the development and assessment of novel algorithms. Additionally, we will continue to add new methods to miRcomp-Shiny. This will produce a richer set of available methods in a single location to guide comparisons. The success of this approach has been demonstrated by the affycomp webtool^7,8.

Operation

Installation. To access miRcomp-Shiny locally, the miRcomp R package and all required dependencies can be installed from Bioconductor with the following commands:

source("http://bioconductor.org/biocLite.R")

biocLite("miRcomp")

To access miRcomp-Shiny remotely, simply go to:

https://laurenkemperman.shinyapps.io/mircomp/

Input. The miRcomp-Shiny app takes one or two quantification methods as input. These methods can be selected from the drop-down menus on the left panel (Figure 1). Alternatively, the user can upload the results of their own method by selecting the custom option from the menu. If the custom option is selected, the user is prompted to upload a matrix of quality values (qc) and a matrix of expression estimates (ct). Once the method or methods have been selected, each assessment plot contains additional assessment-specific options below the plotting window (Figure 1).

Figure 1. The miRcomp-Shiny interface is organized into two panels: on the left the user selects one or more methods to compare and on the right the user selects an assessment tab.

The results of several methods are available or the user can upload the results of their own method (as shown above). After selecting one or more methods, the user can examine the 5 assessment tabs: limit of detection, accuracy, precision, quality assessment, and titration response. Each tab has its own options shown at the bottom of the pane.

Output. The miRcomp-Shiny app produces five plots to assess the performance of the method or methods selected: Limit of Detection, Accuracy, Precision, Quality Assessment, and Titration Response.