set_ALDEx2 {benchdamic} | R Documentation

## set_ALDEx2

### Description

Set the parameters for ALDEx2 differential abundance detection method.

### Usage

    set_ALDEx2(
      pseudo_count = FALSE,
      conditions = NULL,
      mc.samples = 128,
      test = "t",
      denom = "iqlr",
      norm = "TSS",
      expand = TRUE
    )

### Arguments

`pseudo_count` | add 1 to all counts if TRUE (default `pseudo_count = FALSE`).
`conditions` | A character vector. A description of the data structure used for testing. Typically, a vector of group labels. For `aldex.glm`, use a `model.matrix`.
`mc.samples` | An integer. The number of Monte Carlo samples to use when estimating the underlying distributions. Since we are estimating central tendencies, 128 is usually sufficient.
`test` | A character string. Indicates which tests to perform. "t" runs Welch's t and Wilcoxon tests. "kw" runs Kruskal-Wallace and glm tests. "glm" runs a generalized linear model using a `model.matrix`. "corr" runs a correlation test using `cor.test`.
`denom` | A character string. Indicates which features to retain as the denominator for the Geometric Mean calculation. Using "iqlr" accounts for data with systematic variation and centers the features on the set features that have variance that is between the lower and upper quartile of variance. Using "zero" is a more extreme case where there are many non-zero features in one condition but many zeros in another. In this case the geometric mean of each group is calculated using the set of per-group non-zero features.
`norm` | name of the normalization method used to compute the normalization factors to use in the differential abundance analysis. If `norm` is equal to "TMM", "TMMwsp", "RLE", "upperquartile", "posupperquartile", "CSSmedian", "CSSdefault", "TSS" the scaling factors are automatically transformed into normalization factors.
`expand` | logical, if TRUE create all combinations of input parameters (default `expand = TRUE`)

### Value

A named list containing the set of parameters for `DA_ALDEx2` method.

### See Also

`DA_ALDEx2`

### Examples

    # Set some basic combinations of parameters for ALDEx2
    base_ALDEx2 <- set_ALDEx2(conditions = "group")
    # Set a specific set of normalization for ALDEx2 (even of other
    # packages!)
    setNorm_ALDEx2 <- set_ALDEx2(conditions = "group", norm = c("TSS", "TMM"))
    # Set many possible combinations of parameters for ALDEx2
    all_ALDEx2 <- set_ALDEx2(conditions = "group", denom = c("iqlr", "zero"),
        test = c("t", "wilcox"))

[Package benchdamic version 1.0.0 Index]