Data processing, analysis method of gene expression data to identify endogenous reference genes

    公开(公告)号:US11107552B2

    公开(公告)日:2021-08-31

    申请号:US16129206

    申请日:2018-09-12

    Abstract: Disclosed are data processing and analysis methods for gene expression data for identifying endogenous reference genes and a composition for the quantitative analysis of gene expression, comprising a pair of primers and/or probes useful in amplifying the identified endogenous reference genes. Introduced with the concepts of “Zero's proportion” and CV, the method allows different datasets to be integrally analyzed, thereby searching for novel reference genes. By the method, 2,087 genes are first found as housekeeping genes which are expressed in most tissues, and the usefulness thereof in the relative quantification of different target genes is determined by analyzing their expression stability. Of the 2,087 genes, 13 genes show higher expression stability with lower expression levels across a wide range of samples than traditional reference genes such as GAPDH and ACTS, and therefore are suitable for the normalization of universal genes having relatively low expression levels.

    DATA PROCESSING, ANALYSIS METHOD OF GENE EXPRESSION DATA TO IDENTIFY ENDOGENOUS REFERENCE GENES

    公开(公告)号:US20190012429A1

    公开(公告)日:2019-01-10

    申请号:US16129206

    申请日:2018-09-12

    Abstract: Disclosed are data processing and analysis methods for gene expression data for identifying endogenous reference genes and a composition for the quantitative analysis of gene expression, comprising a pair of primers and/or probes useful in amplifying the identified endogenous reference genes. Introduced with the concepts of “Zero's proportion” and CV, the method allows different datasets to be integrally analyzed, thereby searching for novel reference genes. By the method, 2,087 genes are first found as housekeeping genes which are expressed in most tissues, and the usefulness thereof in the relative quantification of different target genes is determined by analyzing their expression stability. Of the 2,087 genes, 13 genes show higher expression stability with lower expression levels across a wide range of samples than traditional reference genes such as GAPDH and ACTS, and therefore are suitable for the normalization of universal genes having relatively low expression levels.

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