--- name: sample-correlation-analysis-942729908791 description: Use when performing correlation analysis between two variables including Pearson and Spearman correlation methods. Supports command-line parameter input, automatic data format detection, parameter validation, result directory creation, and CSV or TXT format result export. license: MIT author: AIPOCH --- > **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills) # Correlation Analysis Use this skill to run correlation analysis on two variables from a tabular data file. ## Use This Skill When - You need Pearson or Spearman correlation between two variables stored either as columns or as first-column row labels. - You need a command-line workflow with parameter validation. - You need standardized output files in CSV or TXT format. ## Primary Command ```bash Rscript scripts/main.R \ --data_file \ --method \ --x_var \ --y_var \ --output_dir ``` ## Prerequisites - Rscript is available in the shell. - Required R packages: `optparse`, `data.table`. - Install missing packages with `Rscript -e 'install.packages(c("optparse", "data.table"), repos="https://cloud.r-project.org")'`. ## Core Arguments | Argument | Required | Description | |----------|----------|-------------| | `--data_file` | Yes | Input data file in CSV, TXT, or TSV format | | `--method` | No | Correlation method: `pearson` or `spearman`. Default `pearson` | | `--x_var` | No | First variable name. It can match a column name or a first-column row label. Default `variable1` | | `--y_var` | No | Second variable name. It can match a column name or a first-column row label. Default `variable2` | | `--output_dir` | No | Output directory, default `./Correlation_Results` | | `--alternative` | No | `two.sided`, `less`, or `greater`. Default `two.sided` | | `--conf_level` | No | Confidence level between 0 and 1, default `0.95` | | `--output_format` | No | `csv` or `txt`, default `csv` | | `--output_prefix` | No | Output filename prefix, default `correlation` | ## Input Requirements - The input file must contain both target variables. - Both variables must contain numeric values. - If the first column stores variable names and the remaining columns are samples, the script automatically reads variables by row label. - Rows with missing values in either variable are excluded. - At least 3 complete observation pairs are needed. Example input: ```csv variable1,variable2 10.2,8.5 11.5,9.2 9.8,7.9 ``` ## Minimal Workflow 1. Confirm the input file exists and variable names are correct. 2. Run `scripts/main.R` with the requested method and variable names. 3. Check the output directory for result files under `table/`. If you omit `--data_file`, the script exits with `SKILL_MISSING_INPUT`. ## Outputs Expected output structure: ```text / ├── table/ ├── figure/ └── data/ ``` Primary result file: - `table/_.csv` - `table/_.txt` Result fields include: - `method` - `correlation` - `statistic` - `p_value` - `conf_low` - `conf_high` - `sample_size` - `x_variable` - `y_variable` - `variable_orientation` ## Choose the Method - Use `pearson` for linear relationships between continuous variables. - Use `spearman` for monotonic relationships, non-normal data, or outlier-prone data. ## 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 Pearson: ```bash Rscript scripts/main.R \ --data_file tests/data/sample_correlation_1.csv \ --method pearson \ --x_var variable1 \ --y_var variable2 \ --output_dir tests/output_pearson ``` Spearman: ```bash Rscript scripts/main.R \ --data_file tests/data/sample_correlation_3.csv \ --method spearman \ --x_var "Activated CD8 T cell" \ --y_var "Central memory CD8 T cell" \ --output_dir tests/output_spearman ``` ## Validation ```bash Rscript scripts/main.R --help ``` ```bash Rscript scripts/main.R \ --data_file tests/data/sample_correlation_1.csv \ --method pearson \ --x_var variable1 \ --y_var variable2 \ --output_dir tests/validation_output ``` After running analysis, verify that `tests/validation_output/table/correlation_pearson.csv` exists. ## Common Errors - `SKILL_FILE_NOT_FOUND`: Input file path is wrong or inaccessible. - `SKILL_MISSING_COLUMNS`: One or both requested variables are missing. - `SKILL_INVALID_DATA`: Input data is malformed or unsuitable for analysis. - `SKILL_INVALID_PARAMETER`: An argument value is invalid. - `SKILL_INSUFFICIENT_DATA`: Too few complete observations remain after filtering. - `SKILL_DEPENDENCY_MISSING`: A required R package such as `optparse` or `data.table` is unavailable. If the issue is not obvious, read `references/troubleshooting.md`. --- Source attribution: aipoch Original project: https://github.com/aipoch/medical-research-skills License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Copyright (c) 2026 Gabriel Moreira Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: aipoch Original project: https://github.com/aipoch/medical-research-skills Attribution basis: Upstream repository explicitly recorded in package mirror path Fields of work: Data & Analytics Roles: Data Analyst, Data Scientist, Market Research Analyst Specialties: API Tools: Rscript Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: 5e0af4e59e4989d1f8eb6096551200c81207bfc629ece44b91705b793fca3500