📋 Analysis Log
Error Information
📁 Main Task Files (for subsequent analysis) （Inherited from parent）
📊 Task Summary
Result Files
Tool Introduction & Use Cases
Decision Tree Classification is primarily used for bioinformatics analysis.
Decision tree is a classic machine learning classification algorithm that makes classification decisions by building a tree structure. Sample names must contain group information in the format: SampleID_Group (e.g., GSM123_control, GSM124_treat). The tool automatically extracts group information from sample names, trains a decision tree model, and outputs gene importance ranking and decision tree visualization.
Main Use Cases:
- Explore data patterns and support subsequent in-depth analysis
Key Features:
- Standardized processing and result export
- Key charts and table output
- Can be used as input for subsequent analysis
Parameter Details
| Parameter | Meaning & Recommendations | Settings |
|---|---|---|
| Differential Gene Expression Matrix | 差异基因表达矩阵文件，样本名需包含分组信息（格式：SampleID_Group） | Required Default: None |
| CP Value (Complexity Parameter) | P-value Threshold: This is the statistical significance threshold. Only genes/proteins with P-values below this threshold are considered significantly changed, not just random fluctuations. Recommendation: Typically set to 0.05 or 0.01. Lower values are more stringent and reliable but may miss some potentially important molecules. | Optional Default: 0.00028 |
| Figure Size | 图片尺寸设置，格式：高*宽 | Optional Default: 8*12 |
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 300 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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