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DNA Microarrays

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

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Updated: Mar 23, 2026

Probe-based Real-time PCR Approaches for Quantitative Measurement of microRNAs

Probe-based Real-time PCR Approaches for Quantitative Measurement of microRNAs

Published on: April 14, 2015

A benchmark for microRNA quantification algorithms using the OpenArray platform.

Matthew N McCall¹, Alexander S Baras², Alexander Crits-Christoph³

¹Department of Biostatistics and Computational Biology, University of Rochester, 265 Crittenden Blvd, Rochester, 14642, NY, USA. mccallm@gmail.com.

BMC Bioinformatics

|March 23, 2016

Summary

This summary is machine-generated.

Accurate microRNA expression quantification is challenging. This study introduces benchmark data and R/Bioconductor packages (miRcomp and miRcompData) for evaluating quantitative PCR (qPCR) algorithms, improving microRNA analysis.

Keywords:

Expression microRNA qPCR

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Area of Science:

Biotechnology
Bioinformatics
Molecular Biology

Background:

Quantifying microRNA expression faces challenges due to low abundance and short length.
Existing methods like hybridization arrays, quantitative PCR (qPCR), and sequencing have limitations.
Limited research has focused on microRNA expression quantification compared to mRNA.

Purpose of the Study:

To develop and validate a benchmark dataset and statistical assessments for evaluating microRNA expression quantification algorithms.
To compare the performance of different algorithms for the Life Technologies TaqMan OpenArray qPCR system.
To provide freely available resources (miRcomp and miRcompData packages) for the microRNA research community.

Main Methods:

Utilized a qPCR-based platform (Life Technologies TaqMan OpenArray) for microRNA expression measurement.
Designed dilution/mixture experiments to create a comprehensive benchmark dataset.
Developed statistical assessments evaluating accuracy, precision, limit of detection, and data quality.

Main Results:

Established a benchmark dataset and a suite of statistical assessments for qPCR-based microRNA expression analysis.
Developed R/Bioconductor packages, miRcomp and miRcompData, containing the benchmark data and assessment tools.
Demonstrated the utility of the software by comparing two common algorithms and assessing four others.

Conclusions:

Benchmark datasets and software are essential for rigorous evaluation and comparison of quantification algorithms.
The miRcomp and miRcompData packages will aid in the development of improved microRNA expression estimation methodologies.
These resources aim to advance the accuracy and reliability of microRNA expression profiling.