Two-Variable Survival Analysis

Survival Analysis

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Tool Introduction & Use Cases

Two-Variable Survival Analysis is primarily used for bioinformatics analysis.

Features: 1. Combined survival analysis for two continuous variables 2. Each variable divided into high and low based on median 3. Combined into four groups (e.g., var1 high + var2 high, var1 high + var2 low, etc.) 4. Automatic calculation of Log-rank test p-value for multi-group differences 5. Generate Kaplan-Meier survival curves 6. Suitable for multi-gene combined prediction, gene-clinical indicator combined analysis 7. Input file requires: futime (survival time), fustat (survival status, 0=censored, 1=death), and two continuous variables

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

ParameterMeaning & RecommendationsSettings
Survival Data File包含futime(生存时间)、fustat(生存状态)和两个连续型变量列的文件
Required
Default: None
First Variable第一个用于生存分析的连续型变量列名
Required
Default: None
Second Variable第二个用于生存分析的连续型变量列名
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 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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