Covariance Analysis, a New Approach for Relative Quantification Competitive PCR in Evaluation of Rumen Anaerobic Fungal Populations
Mohammad Hadi Sekhavati,
Mahdi Elahi Torshizi,
Mahyar Heydarpour,
Adham Fani Maleki
Issue:
Volume 2, Issue 5, December 2014
Pages:
44-50
Received:
8 December 2014
Accepted:
23 December 2014
Published:
4 January 2015
DOI:
10.11648/j.abb.20140205.11
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Abstract: Quantitative competitive polymerase chain reaction (QC-PCR) technique is playing an important role in nucleic acid quantification. This paper describes a new statistical approach for data analyzing in relative quantitative competitive PCR assays. In order to test the accuracy of this statistical model for quantifying anaerobic rumen fungi, samples of rumen fluid were collected from six fistulated Holstein steers which were fed in two different diets groups (soybean meal diet and canola meal diet). Competitor intensity signal (CIS) and efficiency of PCR (EFF) were assumed as two covariates in ANCOVA method. The assumptions for using of these two covariates were tested. A high positive correlation between the mean of the template intensity signal (TIS) through serial dilutions showed an appropriate efficiency of the competitive PCR assays. Results showed that the accuracy of data analyzing for relative quantification anaerobic fungi was considerable improved in ANCOVA model in comparison with ANOVA method and also the power of test is much greater. So, it seems that considering of the CIS and EFF as two co-variables was suitable.
Abstract: Quantitative competitive polymerase chain reaction (QC-PCR) technique is playing an important role in nucleic acid quantification. This paper describes a new statistical approach for data analyzing in relative quantitative competitive PCR assays. In order to test the accuracy of this statistical model for quantifying anaerobic rumen fungi, samples ...
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