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Author: Wang, Jiying; Wang, Yanping; Wang, Huaizhong; Hao, Xiaojing; Wu, Ying; Guo, Jianfeng
Title: Selection of Reference Genes for Gene Expression Studies in Porcine Whole Blood and Peripheral Blood Mononuclear Cells under Polyinosinic:Polycytidylic Acid Stimulation
  • Document date: 2014_4_23
  • ID: xf4yy6i1_15
    Snippet: The data obtained from the qRT-PCR assays were converted into correct input files, according to the requirements of the software, and analyzed using geNorm version 3.5 (Vandesompele et al., 2002) and NormFinder (version 0.953) (Andersen et al., 2004) . In brief, geNorm calculates the gene expression stability measure M for a reference gene as the average pairwise variation V for that gene with all other tested reference genes. Besides the M value.....
    Document: The data obtained from the qRT-PCR assays were converted into correct input files, according to the requirements of the software, and analyzed using geNorm version 3.5 (Vandesompele et al., 2002) and NormFinder (version 0.953) (Andersen et al., 2004) . In brief, geNorm calculates the gene expression stability measure M for a reference gene as the average pairwise variation V for that gene with all other tested reference genes. Besides the M values, geNorm also calculates average expression stability values of remaining control genes during stepwise exclusion of the least stable control gene. Finally, to determine the optimal number of control genes for normalization, by the program, we calculated the pairwise variation V n /V n+1 between two sequential normalization factors NF n and NF n+1 containing an increasing number of reference genes. NormFinder uses the model-based strategy to estimate not only the overall expression variation of the candidate normalization genes, but also the variation between sample subgroups of the sample set, i.e. nonstimulation group and stimulation group in the study. The output of the program provides a stability value for each gene, which is a direct measure for the estimated expression variation enabling the user to evaluate the systematic error introduced when using the gene for normalization.

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