A survey of tools for the analysis of quantitative PCR (qPCR) data

Biomolecular Detection and Quantification

Volumn 1, Issue 1, 2014, Pages 23-33

  Pabinger, Stephan ^a   Rödiger, Stefan ^b   Kriegner, Albert ^a   Vierlinger, Klemens ^a   Weinhäusel, Andreas ^a  

^a AIT AUSTRIAN INSTITUTE OF TECHNOLOGY   (Austria)

^b BRANDENBURG UNIVERSITY OF TECHNOLOGY   (Germany)

Author keywords

Data analysis; MIQE; qPCR; RDML; Software; Tools

Indexed keywords

MESSENGER RNA; MICRORNA;

ARTICLE; CALIBRATION; CLINICAL ASSESSMENT TOOL; COMPUTER PROGRAM; COPY NUMBER VARIATION; DNA METHYLATION; GENE TARGETING; GENOTYPE; HIGH RESOLUTION MELTING ANALYSIS; POLYMERASE CHAIN REACTION; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; PROTEIN EXPRESSION; REAL TIME POLYMERASE CHAIN REACTION; SENSITIVITY AND SPECIFICITY; SINGLE NUCLEOTIDE POLYMORPHISM; STATISTICAL MODEL;

EID: 84921951808     PISSN: None     EISSN: 22147535     Source Type: Journal    
DOI: 10.1016/j.bdq.2014.08.002     Document Type: Review

References (126)

1. Higuchi R, Dollinger G, Walsh PS, Griffith R. Simultaneous amplification and detection of specific DNA sequences. Biotechnology (NY) 1992;10(4):413-7.
2. Kubista M, Andrade JM, Bengtsson M, Forootan A, Jonák J, Lind K, et al. The real-time polymerase chain reaction. Mol Aspects Med 2006;27(2-3):95-125.
3. RödigerS, LiebschC, Schmidt C, LehmannW, Resch-GengerU,SchedlerU,etal. Nucleic acid detection based on the use of microbeads: a review. Microchim Acta 2014.
4. Khodakov DA, Ellis AV. Recent developments in nucleic acid identification using solid-phase enzymatic assays. Microchim Acta 2014:1-14. Available from: URL: http://link.springer.com/article/10.1007/s00604-014-1167-z [cited 08.04.14].
5. Bustin SA, Benes V, GarsonJA, Hellemans J, Huggett J, Kubista M, et al. The MIQE guidelines: minimum information for publication of quantitative realtime PCR experiments. Clin Chem 2009;55(4):611-22.
6. LefeverS, Hellemans J, PattynF, Przybylski DR, Taylor C, Geurts R, et al. RDML: structured language and reporting guidelines for real-time quantitative PCR data. Nucleic Acids Res 2009;37(7):2065-9.
7. Bustin S, Bergkvist A, Nolan T. In silico tools for qPCR assay design and data analysis. Methods Mol Biol 2011;760:283-306.
8. Ince DC, HattonL, Graham-CummingJ. The case for open computer programs. Nature 2012;482(7386):485-8 [cited 03.04.14].
9. Morin A, Urban J, Adams PD, Foster I, Sali A, Baker D, et al. Shining light into black boxes. Science 2012;336(6078):159-60. Available from: URL: http://www.sciencemag.org/content/336/6078/159 [cited 08.04.14].
10. Nolan T, Hands RE, Bustin SA. Quantification of mRNA using real-time RT-PCR. Nat Protoc 2006;1(3):1559-82.
11. Wittwer CT, Herrmann MG, Moss AA, Rasmussen RP. Continuous fluorescence monitoring of rapid cycle DNA amplification. Biotechniques 1997;22(1):130-1,134-8.
12. GudnasonH, DufvaM, Bang DD, Wolff A. Comparison of multiple DNA dyes for real-time PCR: effects of dye concentration and sequence composition on DNA amplification and melting temperature. Nucleic Acids Res 2007;35(19):e127.
13. Ruijter JM, Lorenz P, Tuomi JM, Hecker M, van den Hoff MJB. Fluorescentincrease kinetics of different fluorescent reporters used for qPCR depend on monitoring chemistry, targeted sequence, type of DNA input and PCR efficiency. Microchim Acta 2014:1-8. Available from: URL: http://link. springer.com/article/10.1007/s00604-013-1155-8 [cited 08.04.14].
14. Wittwer CT, Herrmann MG, Gundry CN, Elenitoba-Johnson KS. Real-time multiplex PCR assays. Methods 2001;25(4):430-42.
15. Ruijter JM, Pfaffl MW, ZhaoS, Spiess AN, Boggy G, Blom J, et al. Evaluation of qPCR curve analysis methods for reliable biomarker discovery: bias, resolution, precision, and implications. Methods 2013;59(1):32-46.
16. Wong ML, Medrano JF. Real-time PCR for mRNA quantitation. Biotechniques 2005;39(1):75-85.
17. HeidCA, Stevens J, Livak KJ, Williams PM. Real time quantitative PCR. Genome Res 1996;6(10):986-94.
18. Vogelstein B, Kinzler KW. Digital PCR. Proc Natl Acad Sci U S A 1999;96(16):9236-41.
19. Baker M. Digital PCR hits its stride. Nat Methods 2012;9(6):541-4.
20. Kalinina O, Lebedeva I, Brown J, Silver J. Nanoliter scale PCR with TaqMan detection. Nucleic Acids Res 1997;25(10):1999-2004.
21. White RA, Blainey PC, Fan HC, Quake SR, Digital PCR. provides sensitive and absolute calibration for high throughput sequencing. BMC Genomics 2009;10:116.
22. Bustin SA, Nolan T. Pitfalls of quantitative real-time reverse-transcription polymerase chain reaction. J Biomol Tech 2004;15(3):155-66.
23. Huggett JF, Foy CA, Benes V, Emslie K, GarsonJA, Haynes R, et al. The digital MIQE guidelines: minimum information for publication of quantitative digital PCR experiments. Clin Chem 2013;59(6):892-902.
24. Marx V. PCR:paths to sensitivity. Nat Methods 2014;11(3):241-5.
25. Hindson CM, Chevillet JR, Briggs HA, Gallichotte EN, Ruf IK, Hindson BJ, et al. Absolute quantification by droplet digital PCR versus analog real-time PCR. Nat Methods 2013;10(10):1003-5.
26. Hellemans J, MortierG, de Paepe A, Speleman F, VandesompeleJ. qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data. Genome Biol 2007;8(2):R19.
27. Cikos S, Bukovská A, Koppel J. Relative quantification of mRNA: comparison of methods currently used for real-time PCR data analysis. BMC Mol Biol 2007;8:113.
28. Kozera B, Rapacz M. Reference genes in real-time PCR. J Appl Genet 2013;54(4):391-406.
29. D'haene B, MestdaghP, Hellemans J, VandesompeleJ. miRNA expression profiling: from reference genes to global mean normalization. Methods Mol Biol 2012;822:261-72.
30. Mestdagh P, van Vlierberghe P, de WeerA, Muth D, Westermann F, Speleman F, et al. A novel and universal method for microRNA RT-qPCR data normalization. Genome Biol 2009;10(6):R64.
31. Nordgård O, Kvaløy JT, Farmen RK, Heikkilä R. Error propagation in relative real-time reverse transcription polymerase chain reaction quantification models: the balance between accuracy and precision. Anal Biochem 2006;356(2):182-93.
32. Logan J, Edwards K, Saunders NA. Real-time PCR: current technology and applications. Horizon Scientific Press; 2009.
33. RödigerS, Schierack P, Böhm A, NitschkeJ, BergerI, FrömmelU, et al. A highly versatile microscope imaging technology platform for the multiplex realtime detection of biomolecules and autoimmune antibodies. Adv Biochem Eng Biotechnol 2013;133:35-74.
34. Rödiger S, Burdukiewicz M. chipPCR: toolkit of helper functions to preprocess amplification data; 2013. Available from: URL: http://cran.r-project. org/web/packages/chipPCR/index.html [accessed 08.04.14].
35. BoyerTC, Hanson T, Singer RS. Estimation of low quantity genes: a hierarchical model for analyzing censored quantitative real-time PCR data. PLOS ONE 2013;8(5):e64900.
36. McCall MN, McMurray HR, Land H, AlmudevarA. On non-detects in qPCRdata. Bioinformatics 2014.
37. Sørby LA, Andersen SN, Bukholm IR, Jacobsen MB. Evaluation of suitable reference genes for normalization of real-time reverse transcription PCR analysis in colon cancer. J Exp Clin Cancer Res 2010;29:144.
38. Udvardi MK, Czechowski T, Scheible W. Eleven golden rules of quantitative RT-PCR. Plant Cell 2008;20(7):1736-7.
39. Bustin SA. Why the need forqPCR publication guidelines? The case for MIQE. Methods 2010;50(4):217-26.
40. Rieu I, Powers SJ. Real-time quantitative RT-PCR: design, calculations, and statistics. Plant Cell 2009;21(4):1031-3.
41. SchmittgenTD, Lee EJ, Jiang J. High-throughput real-time PCR. Methods Mol Biol 2008;429:89-98.
42. Spitzer M, WildenhainJ, RappsilberJ, Tyers M. BoxPlotR: a web tool for generation of box plots. Nat Methods 2014;11(2):121-2.
43. Krzywinski M, Altman N. Points of significance: visualizing samples with box plots. Nat Methods 2014;11(2):119-20.
44. Maurin M. Real-time PCR as a diagnostic tool for bacterial diseases. Expert Rev Mol Diagn 2012;12(7):731-54.
45. VanGuilder HD, Vrana KE, Freeman WM. Twenty-five years of quantitative PCR for gene expression analysis. Biotechniques 2008;44(5):619-26.
46. Devonshire AS, Sanders R, Wilkes TM, Taylor MS, Foy CA, Huggett JF. Application of next generation qPCR and sequencing platforms to mRNA biomarker analysis. Methods 2013;59(1):89-100.
47. Riedmaier I, Pfaffl MW. Transcriptional biomarkers-high throughput screening, quantitative verification, and bioinformatical validation methods. Methods 2013;59(1):3-9.
48. StåhlbergA, ZoricN, AmanP, Kubista M. Quantitative real-time PCR for cancer detection: the lymphoma case. Expert Rev Mol Diagn 2005;5(2):221-30.
49. Liu Y, Gibson J, Wheeler J, Kwee LC, Santiago-Turla CM, Akafo SK, et al. GALC deletions increase the risk of primary open-angle glaucoma: the role of Mendelian variants in complex disease. PLoS ONE 2011;6(11):e27134.
50. Kim VN, Nam J. Genomics of microRNA. Trends Genet 2006;22(3):165-73.
51. ChenX, Ba Y, Ma L, Cai X, Yin Y, Wang K, et al. Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases. Cell Res 2008;18(10):997-1006.
52. SchmittgenTD, Lee EJ, Jiang J, Sarkar A, Yang L, Elton TS, et al. Real-time PCR quantification of precursor and mature microRNA. Methods 2008;44(1):31-8.
53. YoshizawaJM, Wong DT. Salivary microRNAs and oral cancer detection. Methods Mol Biol 2013;936:313-24.
54. LeuenbergerN, SchumacherYO, PradervandS, SanderT, Saugy M, Pottgiesser T. Circulating microRNAs as biomarkers for detection of autologous blood transfusion. PLOS ONE 2013;8(6):e66309.
55. Siegismund CS, Rohde M, Kühl U, Lassner D. Multiparametric diagnostics of cardiomyopathies by microRNA signatures. Microchim Acta 2014:1-7. Available from: URL: http://link.springer.com/article/10.1007/ s00604-014-1249-y [cited 08.04.14].
56. Almal SH, Padh H. Implications of gene copy-number variation in health and diseases. J Hum Genet 2012;57(1):6-13.
57. Ma L, Chung WK. Quantitative analysis of copy number variants based on real-time LightCycler PCR. Curr Protoc Hum Genet 2014;80(7):21.1-8.
58. WeaverS, Dube S, Mir A, QinJ, Sun G, Ramakrishnan R, et al. Taking qPCRto a higher level: analysis of CNV reveals the power of high throughput qPCRto enhance quantitative resolution. Methods 2010;50(4):271-6.
59. Yuan JS, Burris J, Stewart NR, Mentewab A, Stewart CN. Statistical tools for transgene copy number estimation based on real-time PCR. BMC Bioinformatics 2007;8(Suppl. 7):S6.
60. D'haene B, VandesompeleJ, Hellemans J. Accurate and objective copy number profiling using real-time quantitative PCR. Methods 2010;50(4):262-70.
61. Gibson NJ. The use of real-time PCR methods in DNA sequence variation analysis. Clin Chim Acta 2006;363(1-2):32-47.
62. Wiita AP, Schrijver I. Clinical application of high throughput molecular screening techniques for pharmacogenomics. Pharmgenom Pers Med 2011;4:109-21.
63. Boggy GJ, Woolf PJ. A mechanistic model of PCR for accurate quantification of quantitative PCR data. PLoS ONE 2010;5(8):e12355.
64. Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, et al. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol 2004;5(10):R80.
65. Valero-Mora PM, Ledesma R. Graphical user interfaces for R. J Stat Softw 2012;49(1):1-8. Available from: URL: http://www.jstatsoft.org/v49/i01
66. Rödiger S, Friedrichsmeier T, Kapat P, Michalke M. RKWard: a comprehensive graphical user interface and integrated development environment for statistical analysis with R. J Stat Softw 2012;49(9):1-34. Available from: URL: http://www.jstatsoft.org/v49/i09
67. Pfaffl MW. A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res 2001;29(9):e45.
68. RStudio Inc. shiny: web application framework for R; 2014. Available from: URL: http://cran.rproject.org/web/packages/shiny/index.html [cited 08.04.14].
69. Rödiger S, Böhm A, Nitschke J, Schierack P, Lehmann W, Schimke I, et al. Analysis of data from experimental qPCR systems with RKWard. qPCR & NGS 2013 Poster Presentations; 2013. Available from: URL: http://www.genequantification. de/qpcr-ngs-2013/posters/P088-qPCR-NGS-2013.pdf [cited 08.04.14].
70. Roediger S, Bohm A, Schimke I. Surface melting curve analysis with R. R J 2013;5(2):37-53. Available from: URL: http://journal.r-project.org/ archive/2013-2/roediger-bohmschimke.pdf
71. Rutledge RG, Stewart D. A kinetic-based sigmoidal model for the polymerase chain reaction and its application to high-capacity absolute quantitative realtime PCR. BMC Biotechnol 2008;8:47.
72. Karlen Y, McNair A, PerseguersS, MazzaC, Mermod N. Statistical significance of quantitative PCR. BMC Bioinformatics 2007;8:131.
73. PerkinsJR, Dawes JM,McMahon SB, Bennett DLH, OrengoC, Kohl M. ReadqPCR and NormqPCR: R packages for the reading, quality checking and normalisation of RT-qPCR quantification cycle (Cq) data. BMC Genomics 2012;13:296.
74. Bustin SA, Benes V, Garson J, Hellemans J, Huggett J, Kubista M, et al. The need for transparency and good practices intheqPCR literature. Nat Methods 2013;10(11):1063-7.
75. Peng RD. Reproducible research in computational science. Science 2011;334(6060):1226-7.
76. CAmpER. Available from: URL: http://camper.cebitec.uni-bielefeld.de/ [cited 2014].
77. Blom J, Rückert C, Kalinowski J, Goesmann A. CAmpER-a software for the calculation of amplification efficiencies for real-time PCR-experiments; 2007. Available from: URL: http://camper.cebitec.uni-bielefeld.de/ [cited 03.03.14].
78. CopyCaller. Available from: URL: http://www.appliedbiosystems.com/absite/ us/en/home/support/software/real-timepcr/copycaller.html [cited 2014].
79. Applied Biosystems. CopyCaller® Software v2.0. Available from: URL: http://www.appliedbiosystems.com/absite/us/en/home/support/software/ real-timepcr/copycaller.html [cited 02.03.14].
80. Cy0 Method. Available from: URL: http://www.cy0method.org/ [cited 2014].
81. Guescini M, Sisti D, Rocchi MBL, Stocchi L, Stocchi V. A new real-time PCR method to overcome significant quantitative inaccuracy due to slight amplification inhibition. BMC Bioinformatics 2008;9:326.
82. Guescini M, Sisti D, Rocchi MBL, Panebianco R, Tibollo P, Stocchi V, et al. Accurate and precise DNA quantification in the presence of different amplification efficiencies using an improved Cy0 method. PLOS ONE 2013;8(7):e68481.
83. DART-PCR. Available from: URL: http://www.genequantification.de/ download.html#dart [cited 2014].
84. PeirsonSN, Butler JN, Foster RG. Experimental validation of novel and conventional approaches to quantitative real-time PCR data analysis. Nucleic Acids Res 2003;31(14):e73.
85. ddCt. Available from: URL: http://www.bioconductor.org/packages/release/ bioc/html/ddCt.html [cited 2014].
86. Zhang JD, Ruschhaupt M, Biczok R. ddCt method for qRT-PCR data analysis; 2013.
87. Deconvolution. Available from: URL: http://www.biomedcentral.com/1471- 2199/11/30 [cited 2014].
88. HirakawaY, MedhRD, MetzenbergS. Quantitative polymerase chain reaction analysis by deconvolution of internal standard. BMC Mol Biol 2010;11:30.
89. dPCR. Available from: URL: http://cran.r-project.org/web/packages/dpcR/ [cited 2014].
90. BurdukiewiczM, Roediger S.dpcR: digital PCR analysis; 2013. Available from: URL: http://cran.r-project.org/web/packages/dpcR/ [cited 05.03.14].
91. EasyqpcR. Available from: URL: http://www.bioconductor.org/packages/ release/bioc/html/EasyqpcR.html [cited 2014].
92. Le Pape S. EasyqpcR for low-throughput real-time quantitative PCR data analysis. Available from: URL: http://www.bioconductor.org/packages/ release/bioc/html/EasyqpcR.html [cited 03.03.14].
93. FPK-PCR. Available from: URL: http://www.gene-quantification.de/lievenset- alefficiency-nar-2011.pdf [cited 2014].
94. 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):e10.
95. HTqPCR. Available from: URL: http://www.bioconductor.org/packages/ release/bioc/html/HTqPCR.html [cited 2014].
96. Dvinge H, Bertone P. HTqPCR: high-throughput analysis and visualization of quantitative real-time PCR data in R. Bioinformatics 2009;25(24):3325-6.
97. LinRegPCR. Available from: URL: http://linregpcr.nl [cited 2014].
98. Ramakers C, Ruijter JM, Deprez RH, Moorman AF. Assumption-free analysis of quantitative real-time polymerase chain reaction (PCR) data. Neurosci Lett 2003;339(1):62-6.
99. LRE Analysis. Available from: URL: http://www.mathworks.com/ matlabcentral/fileexchange/35174-lre-analysis-of-real-time-pcrdata [cited 2014].
100. Leigh D. LRE analysis of real time PCR data. Available from: URL: http://www.mathworks.com/matlabcentral/fileexchange/35174-lreanalysis- of-real-time-pcrdata [cited 03.03.14].
101. LRE Analyzer. Available from: URL: https://sites.google.com/site/lreqpcr [cited 2014].
102. Rutledge RG. A Java program for LRE-based real-time qPCRthat enables largescale absolute quantification. PLoS ONE 2011;6(3):e17636.
103. MAKERGAUL. Available from: URL: http://www.sciencedirect.com/science/ article/pii/S0009912013004918#gr3 [cited 2014].
104. Bultmann CA, Weiskirchen R. MAKERGAUL: an innovative MAK2-based model and software for real-time PCR quantification. Clin Biochem 2014;47(1-2):117-22.
105. NormqPCR. Available from: URL: http://www.bioconductor.org/packages/ release/bioc/html/NormqPCR.html [cited 2014].
106. PCR-Miner. Available from: URL: http://www.miner.ewindup.info/ [cited 2014].
107. Zhao S, Fernald RD. Comprehensive algorithm for quantitative real-time polymerase chain reaction. J Comput Biol 2005;12(8):1047-64.
108. pyQPCR. Available from: URL: http://pyqpcr.sourceforge.net/ [cited 2014].
109. Thomas G, Magali H. pyQPCR; 2014. Available from: URL: http://pyqpcr. sourceforge.net/ [cited 03.03.14].
110. qBase. Available from: URL: http://www.gene-quantification.de/hellemansqbase- 2007.pdf [cited 2014].
111. qCalculator. Available from: URL: http://www.genequantification.de/ download.html#qcalculator [cited 2014].
112. Gilsbach R, Kouta M, Bönisch H, Brüss M. Comparison of in vitro and in vivo reference genes for internal standardization of real-time PCR data. Biotechniques 2006;40(2):173-7.
113. QPCR. Available from: URL: http://www.icbi.at/qpcr [cited 2014].
114. PabingerS,ThallingerGG, SnajderR, Eichhorn H, RaderR, TrajanoskiZ. QPCR: application for real-time PCR data management and analysis. BMC Bioinformatics 2009;10:268.
115. qpcR library. Available from: URL: http://www.dr-spiess.de/qpcR.html [cited 2014].
116. Ritz C, Spiess A. qpcR: an R package for sigmoidal model selection in quantitative real-time polymerase chain reaction analysis. Bioinformatics 2008;24(13):1549-51.
117. qPCR-DAMS. Available from: URL: http://www.genequantification.de/ download.html#qpcrdams [cited 2014].
118. Jin N, He K, Liu L. qPCR-DAMS: a database tool to analyze, manage, and store both relative and absolute quantitative real-time PCR data. Physiol Genomics 2006;25(3):525-7.
119. qpcrNorm. Available from: URL: http://www.bioconductor.org/packages/ release/bioc/html/qpcrNorm.html [cited 2014].
120. MarJC, Kimura Y, Schroder K, Irvine KM, Hayashizaki Y, Suzuki H, et al. Datadriven normalization strategies for high-throughput quantitative RT-PCR. BMC Bioinformatics 2009;10:110.
121. REST. Available from: URL: http://rest.gene-quantification.info/ [cited 2014].
122. Pfaffl MW, Horgan GW, Dempfle L. Relative Expression Software Tool (REST) for group-wise comparison and statistical analysis of relative expression results in real-time PCR. Nucleic Acids Res 2002;30(9):e36.
123. SARS. Available from: URL: http://people.tamu.edu/ syuan/sars/ [cited 2014].
124. YuanJS, Reed A, Chen F, Stewart CN. Statistical analysis of real-time PCR data. BMC Bioinformatics 2006;7:85.
125. SASqPCR. Available from: URL: https://code.google.com/p/sasqpcr/ [cited 2014].
126. Ling D. SASqPCR: robust and rapid analysis of RT-qPCR data in SAS. PLOS ONE 2012;7(1):e29788.