MWAS_bootstrapping {MWASTools} | R Documentation

## MWAS bootstrap resampling

### Description

This function generates bootstrap replicates (non-parametric resampling) of a model testing for association between a given metabolite and a disease phenotype, and calculates the confidence interval of model coefficients. Confidence intervals are calculated using the adjusted bootstrap percentile (BCa) method.

### Usage

    MWAS_bootstrapping (metabo_SE, metabolite_id, disease_id, confounder_ids = NULL,
                        assoc_method, iterations = 10000)

### Arguments

`metabo_SE` | SummarizedExperiment object. See "MWAS_SummarizedExperiment()".
`metabolite_id` | character vector corresponding to the id of the metabolite to be modeled.
`disease_id` | character vector corresponding to the id of the response to be modeled.
`confounder_ids` | optional character vector corresponding to the ids of covariates to be included in the model (e.g. age or gender).
`assoc_method` | character constant indicating the association method that will be used. Possible values for assoc_method are: "pearson" (pearson correlation), "spearman" (spearman correlation), "kendall" (kendall correlation), "linear" (linear regression) or "logistic" (logistic regression).
`iterations` | numeric value indicating the number of bootstrap replicates

### Value

A list with 3 elements, each list element reporting the following information: i) object of class "boot"; ii) summary of the previous object; iii) 95-confidence interval of the metabolite model coefficient. For more details, check the function "boot()" from the "boot" package.

### References

Davison AC, Hinkley, DV. (1997). Bootstrap Methods and Their Application. Cambridge University Press.

### Examples

    ## Load data
    data(targetMetabo_SE)

    ## Bootstrap model testing for association between diabetes (T2D) and 3OH-butyrate
    MWAS_bootstrapping (targetMetabo_SE, metabolite_id = "3-Hydroxybutyrate",
                        disease_id = "T2D",assoc_method = "logistic",
                        iterations = 1000)

[Package MWASTools version 1.11.0 Index]