MWAS_filter {MWASTools} | R Documentation

## Filter MWAS results by p-value and/or CV

### Description

This function allows filtering the output matrix from "MWAS_stats()", by p-value and/or coefficient of variation (CV).

### Usage

    MWAS_filter(MWAS_matrix, type = "pvalue", alpha_th = 0.05, CV_th = 0.30, sort = FALSE)

### Arguments

`MWAS_matrix` | numeric matrix generated by the function "MWAS_stats()".
`type` | character constant indicating the filtering criteria. If type = "pvalue", only metabolic variables with p-value below alpha_th will be retained in the MWAS_matrix. If type = "CV", only metabolic variables with CV below CV_th will be retained. If type = "all", only metabolic variables with CV below CV_th and p-value below alpha_th will be retained.
`alpha_th` | numeric value indicating the significance threshold.
`CV_th` | numeric value indicating the CV threshold.
`sort` | logical constant indicating whether the filter MWAS_matrix will be sorted based on p-values.

### Value

A numeric matrix corresponding to the filtered MWAS_matrix. The matrix has an additional column, which indicates the index of each metabolic variable in the original MWAS_matrix.

### Examples

    ## Load data
    data(targetMetabo_SE)

    ## Test for association between diabetes and target_metabolites
    T2D_model <- MWAS_stats (targetMetabo_SE, disease_id = "T2D",
                             assoc_method = "logistic")

    ## Filter T2D_model by p-value
    MWAS_filter(T2D_model, type = "pvalue", alpha_th = 0.001, sort = TRUE)

    ## Subset targetMetabo_SE based on pvalue_filter
    pvalue_filter <- MWAS_filter(T2D_model, type = "pvalue", alpha_th = 0.001)
    index_features <- pvalue_filter[, 4]
    targetMetabo_SE[index_features, ]

[Package MWASTools version 1.16.0 Index]