Significance analysis method

Abstract

The invention discloses a significance analysis method. A p value and a p (k) value are obtained through utilizing fisher accurate checking and x2 checking respectively; an FDR (False Positive Rate) of a pathway is determined through a plurality of times of comparing and checking. Under the condition of a small sample, differential gene screening is carried out through commonly utilizing t checking or F checking of a random variance model; with regard to two types of differential genes, the difference is identified by adopting the t checking. In order to reduce differential screening errors caused by the small sample, two groups are compared through utilizing T checking revised by the random variance model to calculate a significance level and the false positive rate between the genes, so that the differential genes are obtained; the method has the characteristic of high accuracy and is suitable for popularization and application.

Description

technical field [0001] The invention belongs to the technical field of genes, and relates to a significance analysis method, in particular to a pathway significance analysis method. Background technique [0002] The full name of KEGG (Kyoto Encyclopedia of Genes and Genomes) is the Kyoto Encyclopedia of Genes and Genomes. It is a database that systematically analyzes the relationship between genes (and their encoded products), gene functions, and genome information. It helps researchers to combine genes and expression information. Research the network as a whole. Genomic information is stored in the GENES database, including complete and partially sequenced genome sequences; more advanced functional information is stored in the PATHWAY database, including graphical cell biochemical processes such as metabolism, membrane transport, signal transmission, cell cycle, and homologous conservation sub-channels and other information. The integrated metabolic pathway (pathway) quer...

AI Technical Summary

Problems solved by technology

When studying the difference between the two groups of samples, we take the differential gene as the research object for further research. Since there are only 3 chips in each group during the chip detection process, which belongs to small sample data (less than 30), it is easy to cause high errors.

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