Molecular Detection Mapping and Analysis Platform.

MDMAPR

The MDMAPR 2.0 is an open-source and extensible Shiny web application that is able to merge raw qPCR fluorescence data and metadata together to facilitate the spatial visualization of species presence/absence detections. The application also has the ability to visualize qPCR fluorescence curves and standard curves to evaluate data quality. MDMAPR 2.0 aims to centralize varied qPCR data, which includes data from pathogen and environmental qPCR species detection studies, gene expression studies, and quantification studies used in identifying pathogen-associated health threats.

The MDMAPR 2.0 shiny application has the option to be connected to a custom developed MySQL database in order to populate the applications interface with data. Data can also be uploaded directly on the application for analysis.

To learn how to set up a MDMAPR 2.0 MySQL database to run with the MDMAPR 2.0 Shiny application please refer to the wiki.

The MDMAPR 2.0 was developed by Alka Benawra at the University of Guelph.

Installation

You can install the released version of MDMAPR from CRAN with:

install.packages("MDMAPR")

Example on how to run MDMAPR without database connection:

library(MDMAPR)

#Set dbInstance to no
dbInstance("No")

#Launch app to run application
launchApp()

Example on how to run MDMAPR with database connection

library(MDMAPR)

#Set dbInstance to yes
dbInstance("Yes")

#Enter database connection details in dbVariables (Note: the entries for each variable are examples. Please ensure the variables you enter in the dbVariables function reflect your database instance.)
dbVariables(user = "root", password = "Test23!", dbname = 'MDMap_2.0', host = "127.0.0.1")

#Launch app to run application
launchApp()

Example on how to format raw qPCR fluoresence file data from MIC, StepOnePlus or Biomeme two3/Franklin machines into a table that includes rows for each well location on qPCR plate and the associated fluorescence data for each reaction cycle.

The table is written to the local machine directory as a CSV file. The formatted data can be copied and pasted into the results_Table or standardCurveResults_Table, which are used in the MDMAPR 2.0 MySQL database.

library(MDMAPR)

#Use formatRawFluorescenceFile function to format raw MIC qPCR fluorescence file.
formatRawFluorescenceFile(rawFluorescenceFile = "MIC_raw_fluorescence_data.csv",
                          platform = "MIC", 
                          rawFluorescenceFile = "MIC_formatted_fluorescence_data.csv")

Example on how to add systemCalculatedThresholdValue and systemCalculatedCqValue to the results_Table and standardCurveResults_Table files.

The results_Table and standardCurveResults_Table files must have the formatted fluorescence data already input in the file in order for the addThresholdCq function to work. Users can also use the addThresholdCq function to add the userProvidedCqValue's to the file by setting the calculateUserProvidedCq parameter to "Yes". The userProvidedThresholdValue's must be provided in the results_Table and standardCurveResults_Table in order for the addThresholdCq function to calculate the userProvidedCqValue's.

library(MDMAPR)

#Use addThresholdCq() to add systemCalculatedThresholdValue, systemCalculatedCqValue, and userProvidedCqValue to results_Table files.
addThresholdCq(file = "results_Table.csv", 
               calculateUserProvidedCq = "Yes")

#Use addThresholdCq() to add systemCalculatedThresholdValue and systemCalculatedCqValue to standardCurveResults_Table files. The userProvidedCqValue is not added. 
addThresholdCq(file "standardCurveResults_Table.csv", 
               calculateUserProvidedCq = "No")

Mapping Dashboard

The Mapping Dashboard is used to perform geospatial analysis on qPCR run samples. On this page, an interactive map displays location markers for qPCR run sample collection locations and allows for filtering of markers by Cq intensity, date, location, taxon details, machine type, project, and assay. Hovering above a certain marker will display a pop-up menu that shows information about the specific marker. As well, the page contains a data table which shows detailed information about the markers on the map. The data table will update based on the used filters. A copy of the data table can be downloaded as a CSV by pressing the ‘Download Mapped Markers Metadata’ button.

Data Overview Page

The Data Overview page is used to analyze individual tube/well samples and facilitates the quality control inspection of data. The page has four tabs, which include the ‘Presence/Absence Samples’, ‘Amplification Plot’, ‘Standard Curve Data Overview’, and ‘Standard Curve Plot’. The ‘Presence/Absence Samples’ tab displays a table which indicates if a target sequence was detected in a tube/well based on its Cq Value. The ‘Amplification Plot’ shows the amplification curve associated with a specific well sample from the ‘Presence/Absence Samples’ tab. The ‘Standard Curve Data Overview’ tab displays a table with information related to the standard curve used for the samples in the ‘Presence/Absence Samples’ tab. Lastly, the ‘Standard Curve Plot’ tab shows the plotted standard curve.

Data Submission page

The Data Submission page is used to format raw qPCR fluorescence data and associated metadata into a format that is acceptable to be added to the MDMAPR 2.0 database for storage. On this page, a raw qPCR experimental fluorescence file, a raw standard curve fluorescence file, and the filled in MDMAPR 2.0 metadata file are required. The Data Submission tool will parse the data into 13 CSV files. A preview of the tables is viewable on the page. A zipped file of the CSVs can be downloaded by pressing the ‘Download Data Submission Files’ button. NOTE: Before you can upload the generated CSV data files into their respective tables in the MDMAPR 2.0 database, the ID columns (projectID, geographicRegionID, siteID, stationID, replicateID, extractID, assayID, runID, pcrChemistryID, resultID, standardCurveID, and SCresultID) must be manually changed from alphabetical characters to unique numeric IDs.