bio-metabolomics-normalization-qc

npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-metabolomics-normalization-qc --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

## Version Compatibility Reference examples tested with: xcms 4.0+ Before using code patterns, verify installed versions match. If versions differ: - R: `packageVersion('<pkg>')` then `?function_name` to verify parameters If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # Metabolomics Normalization and QC ## Load and Inspect Data **Goal:** Load the feature table and sample metadata, separating QC and biological samples for downstream processing. **Approach:** Read CSV files, partition by sample type, and assess missing value prevalence. **"Normalize my metabolomics data and correct for batch effects"** → Apply QC-based signal correction, handle missing values, transform intensities, and assess normalization quality via RSD and PCA. ```r library(tidyverse) library(pcaMethods) # Load feature table (samples x features) data <- read.csv('feature_table.csv', row.names = 1) sample_info <- read.csv('sample_info.csv') # Separate QC samples qc_samples <- sample_info$sample_name[sample_info$sample_type == 'QC'] bio_samples <- sample_info$sample_name[sample_info$sample_type != 'QC'] d