Description Usage Arguments Value Examples
Perform a LEfSe analysis: the function carries out differential analysis between two sample groups for multiple microorganisms and uses linear discirminant analysis to establish their effect sizes. Subclass information for each class can be incorporated into the analysis (see examples). Microorganisms with large differences between two sample groups are identified as biomarkers.
1 2 3 4 5 6 7 8 9 10 |
expr |
A |
kruskal.threshold |
numeric(1) The p-value for the Kruskal-Wallis Rank Sum Test (default 0.05). |
wilcox.threshold |
numeric(1) The p-value for the Wilcoxon Rank-Sum Test when 'blockCol' is present (default 0.05). |
lda.threshold |
numeric(1) The effect size threshold (default 2.0). |
groupCol |
character(1) Column name in 'colData(expr)' indicating groups, usually a factor with two levels (e.g., 'c("cases", "controls")'; default "GROUP"). |
blockCol |
character(1) Optional column name in 'colData(expr)' indicating the blocks, usually a factor with two levels (e.g., 'c("adult", "senior")'; default NULL). |
assay |
The i-th assay matrix in the ‘SummarizedExperiment' (’expr'; default 1). |
trim.names |
If 'TRUE' extracts the most specific taxonomic rank of organism. |
The function returns a dataframe with two columns, which are names of microorganisms and their LDA scores.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | # (1) Using classes only
data(zeller14)
# exclude 'adenoma'
zeller14 <- zeller14[, zeller14$study_condition != "adenoma"]
res_group <- lefser(zeller14, groupCol = "study_condition")
head(res_group)
# (2) Using classes and sublasses
data(zeller14)
# exclude 'adenoma'
zeller14 <- zeller14[, zeller14$study_condition != "adenoma"]
res_block <- lefser(
zeller14, groupCol = "study_condition", blockCol = "age_category"
)
head(res_block)
|
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