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Compute dataset-level MNAR metric

Source: R/fits.R
compute_dataset_mnar.Rd

Calculates Spearman correlation between log(mean_abundance) and NA rate across peptides to detect whether low-abundance peptides have more missing values than high-abundance peptides.

Usage

compute_dataset_mnar(missingness)

Arguments

missingness

A tibble with columns na_rate and mean_abundance (as produced by fit_distributions)

Value

A list with:

  • correlation: Spearman correlation coefficient (negative = MNAR pattern)

  • p_value: p-value for the correlation

  • n_peptides: Number of peptides with missing data used in calculation

  • interpretation: Human-readable interpretation string

MNAR Detection

MNAR (Missing Not At Random) in mass spectrometry typically manifests as low-abundance peptides having higher rates of missing values due to detection limits. This function detects this pattern by correlating mean abundance with NA rate across all peptides.

A negative correlation indicates that low-abundance peptides have more missing values - the hallmark of detection-limit-driven MNAR.

Interpretation

Correlation (r)Interpretation
r > -0.1No evidence of MNAR
-0.3 < r < -0.1Weak evidence
-0.5 < r < -0.3Moderate evidence
r < -0.5Strong evidence of MNAR