set_linda | R Documentation |
Set the parameters for linda differential abundance detection method.
set_linda(
assay_name = "counts",
formula = NULL,
contrast = NULL,
is.winsor = TRUE,
outlier.pct = 0.03,
zero.handling = c("pseudo-count", "imputation"),
pseudo.cnt = 0.5,
alpha = 0.05,
p.adj.method = "BH",
expand = TRUE
)
assay_name |
the name of the assay to extract from the
TreeSummarizedExperiment object (default |
formula |
a character string for the formula. The formula should conform to that used by |
contrast |
character vector with exactly, three elements: a string indicating the name of factor whose levels are the conditions to be compared, the name of the level of interest, and the name of the other level. |
is.winsor |
a logical value indicating whether winsorization should be performed to replace outliers (high values). The default is TRUE. |
outlier.pct |
the expected percentage of outliers. These outliers will be winsorized. The default is 0.03. |
zero.handling |
a character string of 'pseudo-count' or 'imputation' indicating the zero handling method
used when |
pseudo.cnt |
a positive numeric value for the pseudo-count to be added if |
alpha |
a numerical value between 0 and 1 indicating the significance level for declaring differential features. Default is 0.05. |
p.adj.method |
a character string indicating the p-value adjustment approach for
addressing multiple testing. See R function |
expand |
logical, if TRUE create all combinations of input parameters
(default |
A named list containing the set of parameters for DA_linda
method.
DA_linda
# Set some basic combinations of parameters for ANCOM with bias correction
base_linda <- set_linda(formula = "~ group", contrast = c("group", "B", "A"),
zero.handling = "pseudo-count", expand = TRUE)
many_linda <- set_linda(formula = "~ group", contrast = c("group", "B", "A"),
is.winsor = c(TRUE, FALSE),
zero.handling = c("pseudo-count", "imputation"), expand = TRUE)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.