Shape based kinetic outlier detection in real-time PCR.
BACKGROUND
Real-time PCR has recently become the technique of choice for absolute and relative nucleic acid quantification. The gold standard quantification method in real-time PCR assumes that the compared samples have similar PCR efficiency. However, many factors present in biological samples affect PCR kinetic, confounding quantification analysis. In this work we propose a new strategy to detect outlier samples, called SOD.


RESULTS
Richards function was fitted on fluorescence readings to parameterize the amplification curves. There was not a significant correlation between calculated amplification parameters (plateau, slope and y-coordinate of the inflection point) and the Log of input DNA demonstrating that this approach can be used to achieve a "fingerprint" for each amplification curve. To identify the outlier runs, the calculated parameters of each unknown sample were compared to those of the standard samples. When a significant underestimation of starting DNA molecules was found, due to the presence of biological inhibitors such as tannic acid, IgG or quercitin, SOD efficiently marked these amplification profiles as outliers. SOD was subsequently compared with KOD, the current approach based on PCR efficiency estimation. The data obtained showed that SOD was more sensitive than KOD, whereas SOD and KOD were equally specific.


CONCLUSIONS
Our results demonstrated, for the first time, that outlier detection can be based on amplification shape instead of PCR efficiency. SOD represents an improvement in real-time PCR analysis because it decreases the variance of data thus increasing the reliability of quantification.
Sisti
Davide
D
Dipartimento DiSUAN, Sezione di Biomatematica, Università degli Studi di Urbino Carlo Bo, Campus Scientifico Sogesta; Località Crocicchia - 61029 Urbino, Italy. davide.sisti@uniurb.it
Guescini
Michele
M
Rocchi
Marco B L
MB
Tibollo
Pasquale
P
D'Atri
Mario
M
Stocchi
Vilberto
V
D019295:Computational Biology / Q000379:methods*; D007700:Kinetics; D010363:Pattern Recognition, Automated / Q000379:methods; D016133:Polymerase Chain Reaction / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods
BMC Mol Biol. 2008 Oct 30;9:96
18973660
Biochim Biophys Acta. 2000 Nov 15;1494(1-2):23-7
11072065
J Forensic Sci. 2006 Jul;51(4):795-804
16882221
J Clin Microbiol. 1998 Jan;36(1):191-7
9431945
Appl Environ Microbiol. 1997 Oct;63(10):3741-51
9327537
Int J Food Microbiol. 1992 Sep;17(1):37-45
1476866
Appl Environ Microbiol. 1998 Feb;64(2):669-77
9464406
Nucleic Acids Res. 2004 Dec 15;32(22):e178
15601990
Biochem Biophys Res Commun. 2002 Jun 7;294(2):347-53
12051718
BMC Mol Biol. 2007 Dec 20;8:113
18093344
BMC Biotechnol. 2008 May 08;8:47
18466619
BMC Mol Biol. 2005 Apr 26;6:10
15854230
Anal Biochem. 2006 Apr 15;351(2):308-10
16524557
Biotechniques. 2007 Mar;42(3):355-62
17390542
BMC Bioinformatics. 2008 Jul 30;9:326
18667053
Biotechniques. 2002 Apr;32(4):790-2, 794-6
11962601
Clin Chem. 2005 Mar;51(3):661-71
15650028
Nat Protoc. 2006;1(3):1559-82
17406449
J Forensic Sci. 1994 Mar;39(2):362-72
8195750
Adv Clin Chem. 2005;40:219-59
16355924
BMC Bioinformatics. 2006 Mar 03;7:107
16515700
Biotechniques. 2003 Feb;34(2):324-32
12613255
Nucleic Acids Res. 2001 May 1;29(9):e45
11328886
Biotechniques. 2008 Apr;44(5):619-26
18474036
Anal Biochem. 2003 Jun 15;317(2):218-25
12758260
BMC Bioinformatics. 2008 Apr 29;9:221
18445269
J Ethnopharmacol. 2005 Jun 3;99(2):221-7
15894131
Mol Aspects Med. 2006 Apr-Jun;27(2-3):254-98
16481036
Mol Cell Probes. 2004 Feb;18(1):45-50
15036369
Appl Environ Microbiol. 1993 Jun;59(6):1972-4
16348974
Methods. 2001 Dec;25(4):402-8
11846609
Nucleic Acids Res. 2003 Sep 1;31(17):e105
12930979
J Clin Virol. 2008 Dec;43(4):372-5
18977692
Expert Rev Mol Diagn. 2009 Mar;9(2):187-97
19298142
Nucleic Acids Res. 2009 Apr;37(6):e45
19237396
Anal Biochem. 2002 Mar 1;302(1):52-9
11846375
Neurosci Lett. 2003 Mar 13;339(1):62-6
12618301
Methods. 2010 Apr;50(4):308-12
20109549