test_differential_prevalence: Differential prevalence testing
In TBrach/MicrobiomeX: eXtended Functions for Microbiome Analysis and Visualization

Description Usage Arguments Value Examples

Perform differential prevalence test on individual taxa in a phylseq object. If block is specified, then Cochran-Mantel-Haenszel test is used. If block is NULL, then Fisher's exact test is used.

1 2	test_differential_prevalence(physeq, group, compare = NULL, block = NULL, p.adjust.method = "fdr", minCount = 0L)

`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.
`p.adjust.method`	Method for adjusting P-values for multiple hypothesis testing.
`minCount`	Minimal threshold for a taxon to be considered present in a sample. Note: the check is `count > minCount` to distinguish zero from non-zero.

Returns a list containing the following:

table: data frame containing the prevalence test results, with the following columns:
Taxon, pvalue, Direction, OR, OR_lb, OR_ub, padj, Significance, tax_table(phyloseq).
OR_lb and OR_ub represent 95-percent confidence intervals for odds-ratio (OR).
test_name: Name of test used - one of c("Fisher's exact test", "Cochran-Mantel-Haenszel test").
block : Name of variable used as blocking factor.

## Not run: 

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

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

## End(Not run)