Use when performing time-dependent ROC curve analysis for survival data with follow-up time, event status, and a numeric marker. Supports CSV/TXT/TSV/Excel input, `risk_score` as the default marker unless `--marker_col` is provided, parameter validation, standardized output directories, AUC table...
BY aipochUPDATED Oct 27, 2026
INTENDED FOR◈OpenClawInstall in a listed agent.
instructions.md
---
name: time-dependent-roc
description: Use when performing time-dependent ROC curve analysis for survival data with follow-up time, event status, and a numeric marker. Supports CSV/TXT/TSV/Excel input, `risk_score` as the default marker unless `--marker_col` is provided, parameter validation, standardized output directories, AUC table export, ROC point export, and PDF figure generation.
license: MIT
author: AIPOCH
---
> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)
# Time-Dependent ROC Analysis
Use this skill to compute and plot time-dependent ROC curves for survival outcomes.
## Use This Skill When
- You have survival data with `futime` and `fustat` columns.
- You need time-specific ROC curves and AUC values for a numeric risk marker.
- You want a command-line workflow with parameter validation and standardized outputs.
- Your file contains a numeric marker column named `risk_score`, or you will provide another marker explicitly with `--marker_col`.
## Primary Command
```bash
Rscript scripts/main.R \
--data_file <input_file> \
--times <comma_separated_times> \
--output_dir <output_dir>
```
## Prerequisites
- `Rscript` is available in the shell.
- Required R packages: `optparse`, `timeROC`, `survival`, `ggplot2`.
- Optional package for Excel input: `openxlsx`.
- Install missing packages with `Rscript -e 'install.packages(c("optparse", "timeROC", "survival", "ggplot2", "openxlsx"), repos="https://cloud.r-project.org")'`.
## Core Arguments
| Argument | Required | Description |
|----------|----------|-------------|
| `--data_file` | Yes | Input data file in CSV, TXT, TSV, TAB, XLS, or XLSX format |
| `--times` | No | Prediction time points, comma-separated. Default `1,3,5` |
| `--marker_col` | No | Marker column name. Default `risk_score`; provide this option when your file uses a different marker |
| `--output_dir` | No | Output directory, default `./TimeROC_Results` |
| `--time_unit` | No | Time unit label for plot/output: `year`, `month`, or `day`. Default `year` |
| `--auto_convert_days` | No | If `TRUE`, convert large `futime` values from days to the selected unit when appropriate. Default `TRUE` |
| `--weighting` | No | IPCW weighting method: `aalen`, `marginal`, or `cox`. Default `aalen` |
| `--cause` | No | Event code treated as the outcome of interest. Default `1` |
## Input Requirements
- The input file must contain `futime` and `fustat` columns.
- The selected marker column must exist and be numeric or coercible to numeric.
- If `--marker_col` is omitted, the input file must contain `risk_score`.
- `futime` must be numeric or coercible to numeric.
- `fustat` must be numeric or coercible to numeric.
- Rows with missing `futime`, `fustat`, or marker values are excluded.
- At least 5 complete rows and at least 1 event for the requested `cause` are required.
Example input:
```text
id fustat futime risk_score risk_group GPR161 RIBC2
TCGA-C5-A1M5 1 5.6219 -1.1070 low 2.8252 5.3532
TCGA-EA-A5O9 0 2.1589 -0.8964 low 2.6046 4.4293
TCGA-C5-A3HL 0 1.7014 -0.9044 low 4.1248 4.9166
```
## Minimal Workflow
1. Confirm the input file exists and includes `futime`, `fustat`, and `risk_score`, or plan to pass `--marker_col`.
2. Run `scripts/main.R` with the requested time points.
3. Check the output directory for the AUC table and PDF figure.
If you omit `--data_file`, the script exits with `SKILL_MISSING_INPUT`.
## Outputs
Expected output structure:
```text
<output_dir>/
├── data/
│ └── time_roc_points.<csv|txt>
├── session_info.txt
├── figure/
│ └── time_roc.pdf
└── table/
└── time_roc_auc.<csv|txt>
```
Primary output files:
- `data/time_roc_points.csv` or `data/time_roc_points.txt`
- `table/time_roc_auc.csv` or `table/time_roc_auc.txt`
- `figure/time_roc.pdf`
- `session_info.txt`
Exported result fields include:
- `time`
- `time_unit`
- `auc`
- `marker_col`
- `n_complete`
- `n_events`
Exported ROC point fields include:
- `false_positive_rate`
- `sensitivity`
- `time`
- `time_unit`
- `auc`
- `curve_label`
## Read These Files When Needed
| Need | File |
|------|------|
| Statistical details and assumptions | `references/algorithm.md` |
| More CLI examples | `references/cli-guide.md` |
| Error diagnosis | `references/troubleshooting.md` |
| Main execution entry point | `scripts/main.R` |
| Sample test data | `tests/data/` |
## Quick Examples
Basic analysis:
```bash
Rscript scripts/main.R \
--data_file tests/data/time_roc_sample1.txt \
--times 1,3,5 \
--output_dir tests/output_basic
```
Specify marker column and plot styling:
```bash
Rscript scripts/main.R \
--data_file tests/data/time_roc_sample2.txt \
--marker_col GPR161 \
--times 1,2,4 \
--line_colors "#4DBBD5,#E64B35,#00A087" \
--legend_position bottom \
--output_dir tests/output_gpr161
```
## Validation
```bash
Rscript scripts/main.R --help
```
```bash
Rscript scripts/main.R \
--data_file tests/data/time_roc_sample1.txt \
--times 1,3,5 \
--output_dir tests/validation_output
```
After running analysis, verify that these files exist:
- `tests/validation_output/data/time_roc_points.csv`
- `tests/validation_output/table/time_roc_auc.csv`
- `tests/validation_output/figure/time_roc.pdf`
- `tests/validation_output/session_info.txt`
## Common Errors
- `SKILL_FILE_NOT_FOUND`: Input file path is wrong or inaccessible.
- `SKILL_MISSING_COLUMNS`: `futime` or `fustat` is missing.
- `SKILL_INVALID_DATA`: The marker column is non-numeric, no complete rows remain, event coding is unsuitable, or requested time points yield unusable AUC values.
- `SKILL_INVALID_PARAMETER`: An argument value is invalid.
- `SKILL_INSUFFICIENT_DATA`: Too few complete rows or no target events remain.
- `SKILL_DEPENDENCY_MISSING`: A required R package such as `optparse`, `timeROC`, `survival`, `ggplot2`, or `openxlsx` is unavailable.
If the issue is not obvious, read `references/troubleshooting.md`.
---
name: time-dependent-roc
description: Use when performing time-dependent ROC curve analysis for survival data with follow-up time, event status, and a numeric marker. Supports CSV/TXT/TSV/Excel input, `risk_score` as the default marker unless `--marker_col` is provided, parameter validation, standardized output directories, AUC table export, ROC point export, and PDF figure generation.
license: MIT
author: AIPOCH
---
> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)
# Time-Dependent ROC Analysis
Use this skill to compute and plot time-dependent ROC curves for survival outcomes.
## Use This Skill When
- You have survival data with `futime` and `fustat` columns.
- You need time-specific ROC curves and AUC values for a numeric risk marker.
- You want a command-line workflow with parameter validation and standardized outputs.
- Your file contains a numeric marker column named `risk_score`, or you will provide another marker explicitly with `--marker_col`.
## Primary Command
```bash
Rscript scripts/main.R \
--data_file <input_file> \
--times <comma_separated_times> \
--output_dir <output_dir>
```
## Prerequisites
- `Rscript` is available in the shell.
- Required R packages: `optparse`, `timeROC`, `survival`, `ggplot2`.
- Optional package for Excel input: `openxlsx`.
- Install missing packages with `Rscript -e 'install.packages(c("optparse", "timeROC", "survival", "ggplot2", "openxlsx"), repos="https://cloud.r-project.org")'`.
## Core Arguments
| Argument | Required | Description |
|----------|----------|-------------|
| `--data_file` | Yes | Input data file in CSV, TXT, TSV, TAB, XLS, or XLSX format |
| `--times` | No | Prediction time points, comma-separated. Default `1,3,5` |
| `--marker_col` | No | Marker column name. Default `risk_score`; provide this option when your file uses a different marker |
| `--output_dir` | No | Output directory, default `./TimeROC_Results` |
| `--time_unit` | No | Time unit label for plot/output: `year`, `month`, or `day`. Default `year` |
| `--auto_convert_days` | No | If `TRUE`, convert large `futime` values from days to the selected unit when appropriate. Default `TRUE` |
| `--weighting` | No | IPCW weighting method: `aalen`, `marginal`, or `cox`. Default `aalen` |
| `--cause` | No | Event code treated as the outcome of interest. Default `1` |
## Input Requirements
- The input file must contain `futime` and `fustat` columns.
- The selected marker column must exist and be numeric or coercible to numeric.
- If `--marker_col` is omitted, the input file must contain `risk_score`.
- `futime` must be numeric or coercible to numeric.
- `fustat` must be numeric or coercible to numeric.
- Rows with missing `futime`, `fustat`, or marker values are excluded.
- At least 5 complete rows and at least 1 event for the requested `cause` are required.
Example input:
```text
id fustat futime risk_score risk_group GPR161 RIBC2
TCGA-C5-A1M5 1 5.6219 -1.1070 low 2.8252 5.3532
TCGA-EA-A5O9 0 2.1589 -0.8964 low 2.6046 4.4293
TCGA-C5-A3HL 0 1.7014 -0.9044 low 4.1248 4.9166
```
## Minimal Workflow
1. Confirm the input file exists and includes `futime`, `fustat`, and `risk_score`, or plan to pass `--marker_col`.
2. Run `scripts/main.R` with the requested time points.
3. Check the output directory for the AUC table and PDF figure.
If you omit `--data_file`, the script exits with `SKILL_MISSING_INPUT`.
## Outputs
Expected output structure:
```text
<output_dir>/
├── data/
│ └── time_roc_points.<csv|txt>
├── session_info.txt
├── figure/
│ └── time_roc.pdf
└── table/
└── time_roc_auc.<csv|txt>
```
Primary output files:
- `data/time_roc_points.csv` or `data/time_roc_points.txt`
- `table/time_roc_auc.csv` or `table/time_roc_auc.txt`
- `figure/time_roc.pdf`
- `session_info.txt`
Exported result fields include:
- `time`
- `time_unit`
- `auc`
- `marker_col`
- `n_complete`
- `n_events`
Exported ROC point fields include:
- `false_positive_rate`
- `sensitivity`
- `time`
- `time_unit`
- `auc`
- `curve_label`
## Read These Files When Needed
| Need | File |
|------|------|
| Statistical details and assumptions | `references/algorithm.md` |
| More CLI examples | `references/cli-guide.md` |
| Error diagnosis | `references/troubleshooting.md` |
| Main execution entry point | `scripts/main.R` |
| Sample test data | `tests/data/` |
## Quick Examples
Basic analysis:
```bash
Rscript scripts/main.R \
--data_file tests/data/time_roc_sample1.txt \
--times 1,3,5 \
--output_dir tests/output_basic
```
Specify marker column and plot styling:
```bash
Rscript scripts/main.R \
--data_file tests/data/time_roc_sample2.txt \
--marker_col GPR161 \
--times 1,2,4 \
--line_colors "#4DBBD5,#E64B35,#00A087" \
--legend_position bottom \
--output_dir tests/output_gpr161
```
## Validation
```bash
Rscript scripts/main.R --help
```
```bash
Rscript scripts/main.R \
--data_file tests/data/time_roc_sample1.txt \
--times 1,3,5 \
--output_dir tests/validation_output
```
After running analysis, verify that these files exist:
- `tests/validation_output/data/time_roc_points.csv`
- `tests/validation_output/table/time_roc_auc.csv`
- `tests/validation_output/figure/time_roc.pdf`
- `tests/validation_output/session_info.txt`
## Common Errors
- `SKILL_FILE_NOT_FOUND`: Input file path is wrong or inaccessible.
- `SKILL_MISSING_COLUMNS`: `futime` or `fustat` is missing.
- `SKILL_INVALID_DATA`: The marker column is non-numeric, no complete rows remain, event coding is unsuitable, or requested time points yield unusable AUC values.
- `SKILL_INVALID_PARAMETER`: An argument value is invalid.
- `SKILL_INSUFFICIENT_DATA`: Too few complete rows or no target events remain.
- `SKILL_DEPENDENCY_MISSING`: A required R package such as `optparse`, `timeROC`, `survival`, `ggplot2`, or `openxlsx` is unavailable.
If the issue is not obvious, read `references/troubleshooting.md`.
COMPATIBILITY & REFERENCES
Platform guidance
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.
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