Evaluation validation of a qPCR curve analysis method and conventional approaches

Abstract Background Reverse Transcription quantitative polymerase chain reaction (RT-qPCR) is a sensitive and reliable method for mRNA quantification and rapid analysis of gene expression from a large number of starting templates. It is based on the statistical significance of the beginning of expon...

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Autores principales:	Yashu Zhang, Hongping Li, Shucheng Shang, Shuoyu Meng, Ting Lin, Yanhui Zhang, Haixing Liu
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	Reverse transcription quantitative polymerase chain reaction Curve analysis method CqMAN Performance indicators Biotechnology TP248.13-248.65 Genetics QH426-470
Acceso en línea:	https://doaj.org/article/e6b02ca36b854d54a96f8447d2d8e56e
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spelling	oai:doaj.org-article:e6b02ca36b854d54a96f8447d2d8e56e2021-11-21T12:26:21ZEvaluation validation of a qPCR curve analysis method and conventional approaches10.1186/s12864-021-07986-41471-2164https://doaj.org/article/e6b02ca36b854d54a96f8447d2d8e56e2021-11-01T00:00:00Zhttps://doi.org/10.1186/s12864-021-07986-4https://doaj.org/toc/1471-2164Abstract Background Reverse Transcription quantitative polymerase chain reaction (RT-qPCR) is a sensitive and reliable method for mRNA quantification and rapid analysis of gene expression from a large number of starting templates. It is based on the statistical significance of the beginning of exponential phase in real-time PCR kinetics, reflecting quantitative cycle of the initial target quantity and the efficiency of the PCR reaction (the fold increase of product per cycle). Results We used the large clinical biomarker dataset and 94-replicates-4-dilutions set which was published previously as research tools, then proposed a new qPCR curve analysis method——CqMAN, to determine the position of quantitative cycle as well as the efficiency of the PCR reaction and applied in the calculations. To verify algorithm performance, 20 genes from biomarker and partial data with concentration gradients from 94-replicates-4-dilutions set of MYCN gene were used to compare our method with various publicly available methods and established a suitable evaluation index system. Conclusions The results show that CqMAN method is comparable to other methods and can be a feasible method which applied to our self-developed qPCR data processing and analysis software, providing a simple tool for qPCR analysis.Yashu ZhangHongping LiShucheng ShangShuoyu MengTing LinYanhui ZhangHaixing LiuBMCarticleReverse transcription quantitative polymerase chain reactionCurve analysis methodCqMANPerformance indicatorsBiotechnologyTP248.13-248.65GeneticsQH426-470ENBMC Genomics, Vol 22, Iss S5, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Reverse transcription quantitative polymerase chain reaction Curve analysis method CqMAN Performance indicators Biotechnology TP248.13-248.65 Genetics QH426-470
spellingShingle	Reverse transcription quantitative polymerase chain reaction Curve analysis method CqMAN Performance indicators Biotechnology TP248.13-248.65 Genetics QH426-470 Yashu Zhang Hongping Li Shucheng Shang Shuoyu Meng Ting Lin Yanhui Zhang Haixing Liu Evaluation validation of a qPCR curve analysis method and conventional approaches
description	Abstract Background Reverse Transcription quantitative polymerase chain reaction (RT-qPCR) is a sensitive and reliable method for mRNA quantification and rapid analysis of gene expression from a large number of starting templates. It is based on the statistical significance of the beginning of exponential phase in real-time PCR kinetics, reflecting quantitative cycle of the initial target quantity and the efficiency of the PCR reaction (the fold increase of product per cycle). Results We used the large clinical biomarker dataset and 94-replicates-4-dilutions set which was published previously as research tools, then proposed a new qPCR curve analysis method——CqMAN, to determine the position of quantitative cycle as well as the efficiency of the PCR reaction and applied in the calculations. To verify algorithm performance, 20 genes from biomarker and partial data with concentration gradients from 94-replicates-4-dilutions set of MYCN gene were used to compare our method with various publicly available methods and established a suitable evaluation index system. Conclusions The results show that CqMAN method is comparable to other methods and can be a feasible method which applied to our self-developed qPCR data processing and analysis software, providing a simple tool for qPCR analysis.
format	article
author	Yashu Zhang Hongping Li Shucheng Shang Shuoyu Meng Ting Lin Yanhui Zhang Haixing Liu
author_facet	Yashu Zhang Hongping Li Shucheng Shang Shuoyu Meng Ting Lin Yanhui Zhang Haixing Liu
author_sort	Yashu Zhang
title	Evaluation validation of a qPCR curve analysis method and conventional approaches
title_short	Evaluation validation of a qPCR curve analysis method and conventional approaches
title_full	Evaluation validation of a qPCR curve analysis method and conventional approaches
title_fullStr	Evaluation validation of a qPCR curve analysis method and conventional approaches
title_full_unstemmed	Evaluation validation of a qPCR curve analysis method and conventional approaches
title_sort	evaluation validation of a qpcr curve analysis method and conventional approaches
publisher	BMC
publishDate	2021
url	https://doaj.org/article/e6b02ca36b854d54a96f8447d2d8e56e
work_keys_str_mv	AT yashuzhang evaluationvalidationofaqpcrcurveanalysismethodandconventionalapproaches AT hongpingli evaluationvalidationofaqpcrcurveanalysismethodandconventionalapproaches AT shuchengshang evaluationvalidationofaqpcrcurveanalysismethodandconventionalapproaches AT shuoyumeng evaluationvalidationofaqpcrcurveanalysismethodandconventionalapproaches AT tinglin evaluationvalidationofaqpcrcurveanalysismethodandconventionalapproaches AT yanhuizhang evaluationvalidationofaqpcrcurveanalysismethodandconventionalapproaches AT haixingliu evaluationvalidationofaqpcrcurveanalysismethodandconventionalapproaches
_version_	1718419038119395328

Evaluation validation of a qPCR curve analysis method and conventional approaches

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