Quality Metrics Summarization

quality-metrics-summarization

License: restricted — no clear open-source license detected for the underlying tool; verify licensing before commercial use or redistribution.

Summary

Compute and report cumulative distributions of quality control metrics (e.g., coefficient of variation) across metabolomic features to validate dataset reproducibility against regulatory thresholds. This skill aggregates pre-computed per-feature QC values into interpretable summary statistics and visualizations that confirm fitness for downstream analysis.

When to use

After running QC analysis on NMR or MS metabolomic data and obtaining per-feature CV values, use this skill to validate that the dataset meets FDA thresholds (CV < 0.30 for discovery, CV < 0.15 for quantification) and to report the proportion of features meeting each threshold. This is a validation gate before proceeding to association modeling.

When NOT to use

• Input is raw NMR or MS spectra (not yet processed through QC analysis)
• Per-feature CV values have not yet been computed or are missing
• The analysis goal is to identify individual features requiring reanalysis rather than to summarize overall dataset reproducibility

Inputs

• Pre-computed per-feature CV values (numeric vector or table, output from MWASTools QC analysis)
• FDA regulatory thresholds (CV < 0.30 for discovery, CV < 0.15 for quantification)

Outputs

• Summary table: feature counts and proportions meeting each CV threshold
• Distribution plot: histogram or empirical CDF of CV values with threshold lines at 0.15 and 0.30
• Validation report: confirmation that observed percentages match expected thresholds

How to apply

Load pre-computed per-feature CV values from QC output. Calculate the empirical cumulative distribution function (CDF) of CV and determine what proportion of features fall below each FDA threshold (0.30 and 0.15). Generate a summary table reporting feature counts and proportions in each CV category. Produce a distribution plot (histogram or empirical CDF) overlaid with vertical threshold lines at CV = 0.15 and 0.30. Validate that computed percentages match reported expectations (e.g., 99% < 0.30, 92% < 0.15) to confirm reproducibility and quality before advancing to metabolite-phenotype association models.

Related tools

• MWASTools (R package that performs QC analysis and outputs per-feature CV values; used to load and aggregate QC metrics for threshold-based validation) — github.com/AndreaRMICL/MWASTools
• R (Statistical environment used to compute empirical CDF, calculate proportions, and generate summary tables and distribution plots)

Examples

# In R using MWASTools output: cv_data <- read.csv('cv_values.csv'); prop_030 <- sum(cv_data$CV < 0.30) / nrow(cv_data); prop_015 <- sum(cv_data$CV < 0.15) / nrow(cv_data); cat('Proportion < 0.30:', prop_030, '\nProportion < 0.15:', prop_015, '\n'); hist(cv_data$CV, breaks=50, main='CV Distribution', xlab='Coefficient of Variation'); abline(v=c(0.15, 0.30), col=c('blue', 'red'), lty=2)

Evaluation signals

• Computed percentages at CV thresholds (0.30 and 0.15) match reported expectations (99% and 92%, respectively)
• Sum of feature counts across all CV categories equals total number of features in the dataset
• Distribution plot displays both threshold lines (0.15 and 0.30) and reflects the empirical shape of the CV distribution
• Summary table contains non-negative integers for feature counts and proportions that sum to 100% (or 1.0 as decimal)
• No missing or undefined CV values in the input data; all features have valid numeric CV measurements

Limitations

• Summary is descriptive only; does not identify which specific features are outliers or fail thresholds — separate investigation needed
• Thresholds (0.30, 0.15) are FDA recommendations; applicability may vary by regulatory context or assay platform (NMR vs. MS)
• Does not account for potential batch effects or platform-specific CV distributions that might differ across cohorts or experimental runs

Evidence

• [intro] FDA threshold interpretation and task objective: "What proportion of NMR metabolic features meet the FDA coefficient of variation (CV) thresholds of <0.30 for biomarker discovery and <0.15 for quantification?"
• [other] Core workflow for metrics summarization: "Calculate the cumulative distribution of CV values and determine the percentage of features meeting each FDA threshold (CV < 0.30 and CV < 0.15). Generate a summary table reporting the count and"
• [other] Visualization and validation requirement: "Produce a distribution plot (histogram or empirical CDF) showing CV values with threshold lines marked at 0.15 and 0.30. Validate that reported percentages (99% at 0.30 threshold, 92% at 0.15"
• [other] Input data type: "Load the pre-computed per-feature CV values (output from quality control analysis)."
• [abstract] MWASTools QC capability: "Key functionalities of the package include: quality control (QC) analysis; metabolite-phenotype association models"