run_posthoc_test: Post hoc pairwise comparisons for multiple groups test.

In yiluheihei/microbiomeMarker: microbiome biomarker analysis toolkit

Post hoc pairwise comparisons for multiple groups test.

Description

Multiple group test, such as anova and Kruskal-Wallis rank sum test, can be used to uncover the significant feature among all groups. Post hoc tests are used to uncover specific mean differences between pair of groups.

Usage

run_posthoc_test(
  ps,
  group,
  transform = c("identity", "log10", "log10p"),
  norm = "TSS",
  norm_para = list(),
  conf_level = 0.95,
  method = c("tukey", "games_howell", "scheffe", "welch_uncorrected")
)

Arguments

ps	a phyloseq::phyloseq object
group	character, the variable to set the group
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: a integer, e.g. 1e6 (default), indicating pre-sample normalization of the sum of the values to 1e6. "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.
norm_para	arguments passed to specific normalization methods
conf_level	confidence level, default 0.95
method	one of "tukey", "games_howell", "scheffe", "welch_uncorrected", defining the method for the pairwise comparisons. See details for more information.

Value

a postHocTest object

See Also

postHocTest, run_test_multiple_groups()

Examples

data(enterotypes_arumugam)
ps <- phyloseq::subset_samples(
    enterotypes_arumugam,
    Enterotype %in% c("Enterotype 3", "Enterotype 2", "Enterotype 1")
) %>%
    phyloseq::subset_taxa(Phylum == "Bacteroidetes")
pht <- run_posthoc_test(ps, group = "Enterotype")
pht

yiluheihei/microbiomeMarker documentation built on Nov. 5, 2023, 7:19 a.m.