Survival Cutoff Analysis

Survival Analysis

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Tool Introduction & Use Cases

Survival Cutoff Analysis is primarily used for bioinformatics analysis.

Features: 1. Automatically determine optimal cutoff value 2. Use surv_cutpoint function from survminer package 3. Automatic grouping into High and Low groups based on cutoff 4. Automatic calculation of Log-rank test p-value for group differences 5. Generate Kaplan-Meier survival curves (High in red, Low in blue) 6. Display confidence intervals and risk table 7. Suitable for gene expression, protein levels and other continuous variables 8. Input file requires: id (sample ID), futime (survival time), fustat (survival status, 0=censored, 1=death), and continuous variable

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id、futime(生存时间)、fustat(生存状态)和连续型变量列的文件
Required
Default: None
Continuous Variable用于生存分析的连续型变量列名(如:基因名、蛋白名等)
Optional
Default: MATN3

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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