Abstract
Background: Several techniques have been tailored to the quantification of microRNA expression, including hybridization arrays, quantitative PCR (qPCR), and high-throughput sequencing. Each of these has certain strengths and limitations depending both on the technology itself and the algorithm used to convert raw data into expression estimates. Reliable quantification of microRNA expression is challenging in part due to the relatively low abundance and short length of the miRNAs. While substantial research has been devoted to the development of methods to quantify mRNA expression, relatively little effort has been spent on microRNA expression. Results: In this work, we focus on the Life Technologies TaqMan OpenArray® system, a qPCR-based platform to measure microRNA expression. Several algorithms currently exist to estimate expression from the raw amplification data produced by qPCR-based technologies. To assess and compare the performance of these methods, we performed a set of dilution/mixture experiments to create a benchmark data set. We also developed a suite of statistical assessments that evaluate many different aspects of performance: accuracy, precision, titration response, number of complete features, limit of detection, and data quality. The benchmark data and software are freely available via two R/Bioconductor packages, miRcomp and miRcompData. Finally, we demonstrate use of our software by comparing two widely used algorithms and providing assessments for four other algorithms. Conclusions: Benchmark data sets and software are crucial tools for the assessment and comparison of competing algorithms. We believe that the miRcomp and miRcompData packages will facilitate the development of new methodology for microRNA expression estimation.
| Original language | English (US) |
|---|---|
| Article number | 138 |
| Journal | BMC Bioinformatics |
| Volume | 17 |
| Issue number | 1 |
| DOIs | |
| State | Published - Mar 22 2016 |
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Keywords
- Expression
- microRNA
- qPCR
ASJC Scopus subject areas
- Applied Mathematics
- Structural Biology
- Biochemistry
- Molecular Biology
- Computer Science Applications
Cite this
A benchmark for microRNA quantification algorithms using the OpenArray platform. / McCall, Matthew N.; Baras, Alexander; Crits-Christoph, Alexander; Ingersoll, Roxann; McAlexander, Melissa A.; Witwer, Kenneth Whitaker; Halushka, Marc K.
In: BMC Bioinformatics, Vol. 17, No. 1, 138, 22.03.2016.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A benchmark for microRNA quantification algorithms using the OpenArray platform
AU - McCall, Matthew N.
AU - Baras, Alexander
AU - Crits-Christoph, Alexander
AU - Ingersoll, Roxann
AU - McAlexander, Melissa A.
AU - Witwer, Kenneth Whitaker
AU - Halushka, Marc K
PY - 2016/3/22
Y1 - 2016/3/22
N2 - Background: Several techniques have been tailored to the quantification of microRNA expression, including hybridization arrays, quantitative PCR (qPCR), and high-throughput sequencing. Each of these has certain strengths and limitations depending both on the technology itself and the algorithm used to convert raw data into expression estimates. Reliable quantification of microRNA expression is challenging in part due to the relatively low abundance and short length of the miRNAs. While substantial research has been devoted to the development of methods to quantify mRNA expression, relatively little effort has been spent on microRNA expression. Results: In this work, we focus on the Life Technologies TaqMan OpenArray® system, a qPCR-based platform to measure microRNA expression. Several algorithms currently exist to estimate expression from the raw amplification data produced by qPCR-based technologies. To assess and compare the performance of these methods, we performed a set of dilution/mixture experiments to create a benchmark data set. We also developed a suite of statistical assessments that evaluate many different aspects of performance: accuracy, precision, titration response, number of complete features, limit of detection, and data quality. The benchmark data and software are freely available via two R/Bioconductor packages, miRcomp and miRcompData. Finally, we demonstrate use of our software by comparing two widely used algorithms and providing assessments for four other algorithms. Conclusions: Benchmark data sets and software are crucial tools for the assessment and comparison of competing algorithms. We believe that the miRcomp and miRcompData packages will facilitate the development of new methodology for microRNA expression estimation.
AB - Background: Several techniques have been tailored to the quantification of microRNA expression, including hybridization arrays, quantitative PCR (qPCR), and high-throughput sequencing. Each of these has certain strengths and limitations depending both on the technology itself and the algorithm used to convert raw data into expression estimates. Reliable quantification of microRNA expression is challenging in part due to the relatively low abundance and short length of the miRNAs. While substantial research has been devoted to the development of methods to quantify mRNA expression, relatively little effort has been spent on microRNA expression. Results: In this work, we focus on the Life Technologies TaqMan OpenArray® system, a qPCR-based platform to measure microRNA expression. Several algorithms currently exist to estimate expression from the raw amplification data produced by qPCR-based technologies. To assess and compare the performance of these methods, we performed a set of dilution/mixture experiments to create a benchmark data set. We also developed a suite of statistical assessments that evaluate many different aspects of performance: accuracy, precision, titration response, number of complete features, limit of detection, and data quality. The benchmark data and software are freely available via two R/Bioconductor packages, miRcomp and miRcompData. Finally, we demonstrate use of our software by comparing two widely used algorithms and providing assessments for four other algorithms. Conclusions: Benchmark data sets and software are crucial tools for the assessment and comparison of competing algorithms. We believe that the miRcomp and miRcompData packages will facilitate the development of new methodology for microRNA expression estimation.
KW - Expression
KW - microRNA
KW - qPCR
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UR - http://www.scopus.com/inward/citedby.url?scp=84962408490&partnerID=8YFLogxK
U2 - 10.1186/s12859-016-0987-8
DO - 10.1186/s12859-016-0987-8
M3 - Article
C2 - 27000067
AN - SCOPUS:84962408490
VL - 17
JO - BMC Bioinformatics
JF - BMC Bioinformatics
SN - 1471-2105
IS - 1
M1 - 138
ER -