findVariableFeatures: Find highly variable peptides

In msImpute: Imputation of label-free mass spectrometry peptides

Description

For each peptide, the total variance is decomposed into biological and technical variance using package scran

Usage

findVariableFeatures(y)

Arguments

y	numeric matrix giving log-intensity. Can contain NA values. Peptides with insufficient observations will be ignored.

Details

A loess trend is fitted to total sample variances and mean intensities. For each peptide, the biological variance is then computed by subtracting the estimated technical variance from the loess fit from the total sample variance.

Value

A data frame where rows are peptides and columns contain estimates of biological and technical variances. Peptides are ordered by biological variance.

See Also

computeStructuralMetrics

Examples

data(pxd007959)
findVariableFeatures(data.matrix(log2(pxd007959$y)))

msImpute documentation built on Nov. 8, 2020, 5:26 p.m.