Generation method of integrated proteome analysis data group, integrated proteome analysis method using integrated proteome analysis data group generated by the generation method, and causative substance identification method using the same

摘要

The amount of expression fluctuation of both protein and gene can be considered comprehensively, and more appropriate analysis results can be obtained with higher accuracy than when analyzing the amount of expression change of protein or gene alone. A method for generating a data group for integrated proteome analysis that can be derived, an analysis method, and a method for identifying and using a causative protein such as a disease by using these methods are provided. The method for generating a data group for integrated proteome analysis according to the present invention includes a protein unique number sharing step for assigning a common unique number to the expression variation data for each protein, and a common uniqueness to the expression variation data for each gene. The gene peculiar number sharing step for assigning a number, the data combining step for combining both expression variation data groups, and the data for which the p value is equal to or greater than a predetermined value among the expression variation data constituting the combined data group are rejected. A data rejection step, a data adoption step for generating a data group to be used for integrated proteome analysis by adopting one of the data based on a predetermined condition for the data given the same common unique number, Have Furthermore, according to the present invention, the causative protein such as a disease or a disease state can be identified by GO analysis and network analysis from the generated data group for integrated proteome analysis, and the causative protein can be used as a tumor marker or the like.