📋 Analysis Log
Error Information
📁 Main Task Files (for subsequent analysis) （Inherited from parent）
📊 Task Summary
Result Files
Tool Introduction & Use Cases
DEG Analysis is primarily used for differential expression analysis.
Differential expression gene analysis using DESeq2 or Limma, supporting counts/fpkm/tpm data types
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 |
|---|---|---|
| Sample Grouping File | Experimental Grouping/Control Setting: Defines comparison groups (two or more) and reference group. Recommendation: Reference group is typically "control/untreated". Ensure grouping matches sample annotations. | Required Default: None |
| log2FC Threshold | Log2 Fold Change Threshold: Measures the magnitude of difference. For example, a threshold of 1 means you only care about genes with more than 2-fold upregulation or more than 50% downregulation. Recommendation: Typically set to 1 or 1.5. Higher values yield more dramatic differences. | Required Default: 1 |
| Adjusted P-value Threshold | Multiple Testing Correction Threshold (FDR/q): Controls false positive rates from multiple comparisons. Recommendation: Commonly 0.05; can be relaxed to 0.1 for smaller sample sizes or higher noise to maintain recall. | Required Default: 0.05 |
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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