Analysis System For Gene Co-expression Correlation In Human Immune Cells Based On Linear And Nonlinear Correlation

Present popular gene co-expression system provides linear correlation analysis for gene pairs, but ignoring nonlinear correlation, which might make misunderstanding in evaluating the gene-gene co-expression strengths precisely. System of this thesis design, an analysis system for gene co-expression correlation in human immune cells based on linear and nonlinear correlation, can enhance the comprehension of gene co-expression correlation by synthesizing Pearson linear correlation (r) and mutual information (MI). Besides, this thesis design a synthesize model MIr to help understand the rank of co-expression correlation of one given gene pairs. Furthermore, after executing the query, system shows the most relevant genes to a given gene displayed with the MI, r or MIr and the correlation rank of its cell on result page. Besides, the ranking value with MI and r on the cellular level is also available for users.