generate_met_z_scores: Generate Metabolite Z Scores

In KevinGHicks/MIDAS: MIDAS

Generate Metabolite Z Scores

Description

Estimate the mean, and SD of abundances changes and resulting statistical significance based on a Wald test.

Usage

generate_met_z_scores(met_data, sd_method = "holdout", quantile_range = 0.5)

Arguments

met_data	a tibble containing metabolite, protein and log2_abundance_corrected
sd_method	method to use when estimating standard deviation: holdout For a given value, calculate SD by removing that value and calculating SD over all other measurements of that metabolite. Conservative when there are many enrichments or depletions of a given metabolite. central_quantiles Estimate SD from the central quantiles of the relative abundance distribution. For intuition, 66 % of Normally-distribute observations are expected to fall within 1 SD of the mean. So, the range of the central 66 % of the Normal distribution would approximate twice the standard deviation.
quantile_range	For central_quantiles, fraction of relative abundance distribution to use when estimating SD.

Value

met_data containing estimates of the SD of an observation and p-values.

KevinGHicks/MIDAS documentation built on May 12, 2022, 8:14 a.m.