📋 Analysis Log
Error Information
📁 Main Task Files (for subsequent analysis) （Inherited from parent）
📊 Task Summary
Result Files
Tool Introduction & Use Cases
Differential Box Plot is primarily used for differential expression analysis.
Create box plots with automatic Wilcoxon statistical testing between groups and p-value annotations
Main Use Cases:
- Compare treatment and control groups to identify up/down-regulated key genes or proteins
- Assess the impact of drug treatment, gene knockout/overexpression on expression profiles
- Provide high-confidence candidate sets for subsequent enrichment and pathway analysis
Key Features:
- Differential expression statistics and significance assessment
- Support for multiple testing correction (FDR/q-values)
- Output standard results usable for volcano plots/heatmaps/enrichment
Parameter Details
| Parameter | Meaning & Recommendations | Settings |
|---|---|---|
| Input File | 数据文件，需包含3列：ID（样本ID）、Type（分组）、Expression（表达值） | Required Default: None |
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 40 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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