📋 Analysis Log
Error Information
📁 Main Task Files (for subsequent analysis) （Inherited from parent）
📊 Task Summary
Result Files
Tool Introduction & Use Cases
Correlation Network is primarily used for calculating and visualizing correlations (between samples or genes).
Generate correlation network plot to show correlation relationships between genes
Main Use Cases:
- Assess overall consistency between samples or identify co-expression gene modules
- Provide basis for network analysis and module discovery
Key Features:
- Correlation matrix and heatmap
- Support for multiple correlation coefficients (Pearson/Spearman)
- Clustering and module visualization
Parameter Details
| Parameter | Meaning & Recommendations | Settings |
|---|---|---|
| Expression Matrix | 表达矩阵文件，行为基因，列为样本 | Required Default: None |
| Correlation Cutoff | 相关系数绝对值阈值，仅显示相关性大于此值的基因对 | Optional Default: 0.4 |
Input File Requirements
Please ensure your input file format is correct, as this is fundamental to successful analysis. Typically, you need to provide a data matrix containing gene/protein expression values.
This tool does not currently provide sample files. Please refer to the common format: typically CSV or TXT files with the first column as gene/protein IDs, followed by expression values for each sample.
Frequently Asked Questions
Q: How long does the analysis take?
A: Estimated execution time is approximately 120 seconds, depending on your data size and current server load.
Q: What if the analysis fails?
A: If the analysis fails, your credits will not be deducted. First, check if your input file format matches the sample file, or adjust parameters based on error messages. If the problem persists, please contact us through the page's feedback function.
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