Statistical test for multiple groups

run_test_multiple_groups(
  ps,
  group,
  taxa_rank = "all",
  transform = c("identity", "log10", "log10p"),
  norm = "TSS",
  norm_para = list(),
  method = c("anova", "kruskal"),
  p_adjust = c("none", "fdr", "bonferroni", "holm", "hochberg", "hommel", "BH", "BY"),
  pvalue_cutoff = 0.05,
  effect_size_cutoff = NULL
)

Arguments

ps

a phyloseq::phyloseq object

group

character, the variable to set the group

taxa_rank

character to specify taxonomic rank to perform differential analysis on. Should be one of phyloseq::rank_names(phyloseq), or "all" means to summarize the taxa by the top taxa ranks (summarize_taxa(ps, level = rank_names(ps)[1])), or "none" means perform differential analysis on the original taxa (taxa_names(phyloseq), e.g., OTU or ASV).

transform

character, the methods used to transform the microbial abundance. See transform_abundances() for more details. The options include:

"identity", return the original data without any transformation (default).
"log10", the transformation is log10(object), and if the data contains zeros the transformation is log10(1 + object).
"log10p", the transformation is log10(1 + object).

norm

the methods used to normalize the microbial abundance data. See normalize() for more details. Options include:

"none": do not normalize.
"rarefy": random subsampling counts to the smallest library size in the data set.
"TSS": total sum scaling, also referred to as "relative abundance", the abundances were normalized by dividing the corresponding sample library size.
"TMM": trimmed mean of m-values. First, a sample is chosen as reference. The scaling factor is then derived using a weighted trimmed mean over the differences of the log-transformed gene-count fold-change between the sample and the reference.
"RLE", relative log expression, RLE uses a pseudo-reference calculated using the geometric mean of the gene-specific abundances over all samples. The scaling factors are then calculated as the median of the gene counts ratios between the samples and the reference.
"CSS": cumulative sum scaling, calculates scaling factors as the cumulative sum of gene abundances up to a data-derived threshold.
"CLR": centered log-ratio normalization.
"CPM": pre-sample normalization of the sum of the values to 1e+06.

norm_para

arguments passed to specific normalization methods

method

test method, must be one of "anova" or "kruskal"

p_adjust

method for multiple test correction, default none, for more details see stats::p.adjust.

pvalue_cutoff

numeric, p value cutoff, default 0.05.

effect_size_cutoff

numeric, cutoff of effect size default NULL which means no effect size filter. The eta squared is used to measure the effect size for anova/kruskal test.

Value

a microbiomeMarker object.

Examples

data(enterotypes_arumugam)
ps <- phyloseq::subset_samples(
    enterotypes_arumugam,
    Enterotype %in% c("Enterotype 3", "Enterotype 2", "Enterotype 1")
)
mm_anova <- run_test_multiple_groups(
    ps,
    group = "Enterotype",
    method = "anova"
)

Statistical test for multiple groups

Arguments

Value

See also

Examples