run_posthoc_test {microbiomeMarker} | R Documentation |
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
[Package
microbiomeMarker version 1.0.2
Index]