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MIrExpress: A Database for Gene Coexpression Correlation in Immune Cells Based on Mutual Information and Pearson
Luman Wang1, Qiaochu Mo2, Jianxin Wang3
1School of Information, Beijing Forestry University, Beijing 100083, China; Department of Natural Science in Medicine, Peking University Health Science Center, Beijing 100191, China.
MIrExpress is a new database that measures both linear and nonlinear gene coexpression strengths in immune cells. It uses information theory and Pearson correlation to provide a more precise understanding of gene relationships.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Current gene coexpression databases primarily analyze linear correlations, limiting the precise evaluation of gene-gene coexpression strengths.
- Nonlinear correlations are crucial for a comprehensive understanding of gene interactions.
Purpose of the Study:
- To introduce MIrExpress, a novel database for analyzing cell-specific gene coexpressions in immune cells.
- To enable the measurement of linear, nonlinear, and hybrid correlations between gene pairs.
Main Methods:
- Utilizes information theory (mutual information, MI) and the Pearson linear correlation coefficient (r).
- Calculates MI and r for user-input gene or probe set pairs.
- Reports MI and r values, rank orderings, rank comparisons, and hybrid correlation values.
Main Results:
- MIrExpress provides a comprehensive analysis of gene coexpression, including nonlinear relationships.
- The database displays the top 10 most relevant genes for a given gene based on MI, r, or hybrid correlation.
- Includes data for 16 human cell groups and 20,283 human genes.
Conclusions:
- MIrExpress enhances the analysis of gene coexpression by incorporating nonlinear measures.
- The database offers valuable insights into cell-specific gene interactions in immune cells.
- Provides interactive access to expression data and correlation results for research applications.
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