A benchmark for microRNA quantification algorithms using the OpenArray platform

BMC Bioinformatics

Volumn 17, Issue 1, 2016, Pages

  McCall, Matthew N ^a   Baras, Alexander S ^b   Crits Christoph, Alexander ^b   Ingersoll, Roxann ^b   McAlexander, Melissa A ^b   Witwer, Kenneth W ^b,c   Halushka, Marc K ^b  

^a UNIVERSITY OF ROCHESTER   (United States)

^b JOHNS HOPKINS UNIVERSITY   (United States)

^c JOHNS HOPKINS UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Expression; microRNA; qPCR

Indexed keywords

BENCHMARKING; DATA HANDLING; POLYMERASE CHAIN REACTION;

COMPETING ALGORITHMS; EXPRESSION; HIGH-THROUGHPUT SEQUENCING; LIMIT OF DETECTION; MICRORNA EXPRESSION; MICRORNAS; QPCR; STATISTICAL ASSESSMENT;

RNA;

MICRORNA;

ALGORITHM; BENCHMARKING; HUMAN; LIMIT OF DETECTION; METABOLISM; PROCEDURES; REAL TIME POLYMERASE CHAIN REACTION; SOFTWARE;

ALGORITHMS; BENCHMARKING; HUMANS; LIMIT OF DETECTION; MICRORNAS; REAL-TIME POLYMERASE CHAIN REACTION; SOFTWARE;

EID: 84962408490     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/s12859-016-0987-8     Document Type: Article

References (22)

1. Bartel DP. Micrornas: genomics, biogenesis, mechanism, and function. Cell. 2004; 116(2):281-97.
2. Haider BA, Baras AS, McCall MN, Hertel JA, Cornish TC, Halushka MK. A critical evaluation of microRNA biomarkers in non-neoplastic disease. PLoS One. 2014; 9(2):89565.
3. Mendell JT, Olson EN. MicroRNAs in stress signaling and human disease. Cell. 2012; 148(6):1172-87.
4. McCall MN, Kent OA, Yu J, Fox-Talbot K, Zaiman AL, Halushka MK. MicroRNA profiling of diverse endothelial cell types. BMC Med Genet. 2011; 4(1):78.
5. Londin E, Loher P, Telonis AG, Quann K, Clark P, Jing Y, Hatzimichael E, Kirino Y, Honda S, Lally M, et al. Analysis of 13 cell types reveals evidence for the expression of numerous novel primate-and tissue-specific microRNAs. Proc Natl Acad Sci. 2015; 112(10):1106-15.
6. Pritchard CC, Cheng HH, Tewari M. MicroRNA profiling: approaches and considerations. Nat Rev Genet. 2012; 13(5):358-69.
7. Mestdagh P, Hartmann N, Baeriswyl L, Andreasen D, Bernard N, Chen C, Cheo D, D'Andrade P, DeMayo M, Dennis L, et al. Evaluation of quantitative miRNA expression platforms in the microRNA quality control (miRQC) study. Nat Methods. 2014; 11(8):809-15.
8. Sah S, McCall MN, Eveleigh D, Wilson M, Irizarry RA. Performance evaluation of commercial miRNA expression array platforms. BMC Res Notes. 2010; 3(1):80.
9. Baras A, Mitchell C, Myers J, Gupta S, Weng L, Ashton J, Cornish T, Pandey A, Halushka M. miRge - a multiplexed method of processing small RNA-seq data to determine microRNA entropy. PLoS One. 2015; 10(11):0143066.
10. Applied BioSystems. Crt, a relative threshold method for qPCR data analysis on the QuantStudio 12K Flex system with OpenArray technology. 2014. Technical report, Life Technologies. https://tools.thermofisher.com/content/sfs/brochures/CO28730-Crt-Tech-note_FLR.pdf.
11. Ritz C, Spiess AN. qpcR: an R package for sigmoidal model selection in quantitative real-time polymerase chain reaction analysis. Bioinformatics. 2008; 24(13):1549-51.
12. Lievens A, Van Aelst S, Van den Bulcke M, Goetghebeur E. Enhanced analysis of real-time PCR data by using a variable efficiency model: FPK-PCR. Nucleic Acids Res. 2012; 40(2):10-10.
13. Rödiger S, Burdukiewicz M, Schierack P. chipPCR: an R package to pre-process raw data of amplification curves. Bioinformatics. 2015; 31(17):2900-2.
14. R Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2015. R Foundation for Statistical Computing. http://www.R-project.org.
15. Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, et al. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 2004; 5(10):80.
16. Bonnal RJP, Rossi RL, Carpi D, Ranzani V, Abrignani S, Pagani M. miRiadne: a web tool for consistent integration of miRNA nomenclature. Nucleic Acids Res. 2015; 43(W1):W487-92.
17. Rutledge R. Sigmoidal curve-fitting redefines quantitative real-time PCR with the prospective of developing automated high-throughput applications. Nucleic Acids Res. 2004; 32(22):178-8.
18. Spiess AN. QpcR: Modelling and Analysis of Real-time PCR data. 2014. R package version 1.4-0. http://CRAN.R-project.org/package=qpcR.
19. Spiess AN, Feig C, Ritz C. Highly accurate sigmoidal fitting of real-time PCR data by introducing a parameter for asymmetry. BMC Bioinforma. 2008; 9(1):221.
20. Pabinger S, Rödiger S, Kriegner A, Vierlinger K, Weinhäusel A. A survey of tools for the analysis of quantitative PCR (qPCR) data. Biomolecular Detect Quantification. 2014; 1(1):23-33.
21. Irizarry RA, Cope LM, Wu Z. Feature-level exploration of a published Affymetrix GeneChip control dataset. Genome Biol. 2006; 7(8):404.
22. McCall MN, Irizarry RA. Consolidated strategy for the analysis of microarray spike-in data. Nucleic Acids Res. 2008; 36(17):108-8.