test_differential_abundance_Wilcoxon: Wilcoxon rank sum differential abundance test

In TBrach/MicrobiomeX: eXtended Functions for Microbiome Analysis and Visualization

Description

Perform Wilcoxon rank sum test on individual taxa in a phylseq object. If block is specified, then it is used as a blocking factor. If block is NULL, then standard Wilcoxon test is applied.

Usage

test_differential_abundance_Wilcoxon(physeq, group, compare = NULL,
  block = NULL, excludeZeros = FALSE, p.adjust.method = "fdr")

Arguments

physeq	Phyloseq object.
group	Name of column in sample metadata to perform group-wise comparisons on.
compare	List of 2 groups to be compared, which are present in the group column. Can be ignored or set to NULL when there are only 2 levels in the factor.
block	Name of column in sample metadata to control for the group-wise comparisons.
excludeZeros	logical. Should abundance=0 for a taxon in a sample be ignored when performing Wilcoxon test?
p.adjust.method	Method for adjusting P-values for multiple hypothesis testing.

Value

Returns a list containing the following:

• table: data frame containing the prevalence test results, with the following columns:
  Taxon, teststat, W, pvalue, Med_1, Med_2, padj, Significance, Direction, tax_table(phyloseq).
  The teststatistic is based on the standardized teststatistic, equation provided by multtest::mt.minP.

• test_name: Name of test used - in this case "Wilcoxon rank sum test".

• block : Name of variable used as blocking factor.

Examples

## Not run: 

# If there are only 2 levels for \code{Diet}
res <- test_differential_abundance_Wilcoxon(physeq, group = "Diet", block = "Gender")

# If there are multiple levels for \code{Diet}
res <- test_differential_abundance_Wilcoxon(physeq, group = "Diet", compare=c("Control", "High_Fat"), block = "Gender")
res <- test_differential_abundance_Wilcoxon(physeq, group = "Diet", compare=c("Control", "High_Fibre"), block = "Gender")

## End(Not run)

TBrach/MicrobiomeX documentation built on May 14, 2019, 2:28 p.m.