PMC:3475481 / 5121-5967 JSONTXT

{"target":"https://pubannotation.org/docs/sourcedb/PMC/sourceid/3475481","sourcedb":"PMC","sourceid":"3475481","source_url":"https://www.ncbi.nlm.nih.gov/pmc/3475481","text":"Identification of significant genes from a combined dataset\nAfter the summarization of gene expression ratios in the form of a contingency table for each gene, as shown in Table 3, a nonparametric statistical method was applied to the datasets for independence testing between gene expression patterns and experimental groups. The test statistics are calculated as follows for each gene:\n\nWhen the sample size is small - generally Ê(nij) less than 5 - Fisher's exact test is recommended rather than chi-square test.\nThe significant genes can be selected by an independence test between the phenotypes and gene expressions using this type of summarized dataset. ci and ri represent the marginal sums of the ith column and row, respectively. nij is the number of experiments belonging to Ei and Pj, and n represents the total number of experiments.","divisions":[{"label":"Title","span":{"begin":0,"end":59}}],"tracks":[]}