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2 changes: 2 additions & 0 deletions .Rbuildignore
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Expand Up @@ -4,3 +4,5 @@
^README\.Rmd$
^\.github$
^codecov\.yml$
^pkgdown$
^README\.html$
17 changes: 12 additions & 5 deletions DESCRIPTION
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Expand Up @@ -15,17 +15,24 @@ BugReports: https://github.com/microbiome/daa/issues/
biocViews: Software, Microbiome
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
RoxygenNote: 7.3.3
Depends:
R (>= 4.5.0)
R (>= 4.5.0),
mia
Imports:
dplyr
dplyr,
methods,
miaViz,
purrr,
rstatix,
S4Vectors,
SingleCellExperiment,
SummarizedExperiment
Suggests:
BiocStyle,
knitr,
RefManageR,
MultiAssayExperiment,
rmarkdown,
sessioninfo,
testthat
Config/testthat/edition: 3
VignetteBuilder: knitr
24 changes: 24 additions & 0 deletions NAMESPACE
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@@ -1,2 +1,26 @@
# Generated by roxygen2: do not edit by hand

export(addTtest)
export(addWilcoxon)
export(getTtest)
export(getWilcoxon)
exportMethods(addTtest)
exportMethods(addWilcoxon)
exportMethods(getTtest)
exportMethods(getWilcoxon)
importFrom(S4Vectors,DataFrame)
importFrom(SingleCellExperiment,altExp)
importFrom(SummarizedExperiment,assay)
importFrom(SummarizedExperiment,colData)
importFrom(SummarizedExperiment,rowData)
importFrom(dplyr,across)
importFrom(dplyr,all_of)
importFrom(dplyr,arrange)
importFrom(dplyr,group_split)
importFrom(methods,callNextMethod)
importFrom(mia,meltSE)
importFrom(purrr,map_df)
importFrom(rstatix,adjust_pvalue)
importFrom(rstatix,t_test)
importFrom(rstatix,wilcox_test)
importFrom(stats,as.formula)
25 changes: 25 additions & 0 deletions R/AllGenerics.R
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@@ -0,0 +1,25 @@
# This file contains all the generics

#' @rdname getWilcoxon
#' @export
setGeneric( "getWilcoxon", signature = "x", function ( x, ... ){
standardGeneric("getWilcoxon")
})

#' @rdname getWilcoxon
#' @export
setGeneric( "addWilcoxon", signature = "x", function ( x, ... ){
standardGeneric("addWilcoxon")
})

#' @rdname getTtest
#' @export
setGeneric( "getTtest", signature = "x", function ( x, ... ){
standardGeneric("getTtest")
})

#' @rdname getTtest
#' @export
setGeneric( "addTtest", signature = "x", function ( x, ... ){
standardGeneric("addTtest")
})
149 changes: 149 additions & 0 deletions R/getTtest.R
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@@ -0,0 +1,149 @@
#' @name
#' getTtest
#'
#' @title
#' Perform t-test
#'
#' @description
#' These functions perform t-test to compare values between two groups.
#'
#' @details
#' By default, Welch's t-test is used which does not assume equal variances.
#' Set \code{var.equal = TRUE} for Student's t-test.
#'
#' Specify exactly one of \code{assay.type}, \code{row.var}, or \code{col.var}
#' to define the values to test.
#'
#' @return
#' \code{getTtest} returns a \code{DataFrame} with test results.
#' \code{addTtest} returns \code{x} with results added to \code{rowData(x)}.
#'
#' @param x A \code{SummarizedExperiment} object.
#'
#' @param assay.type \code{Character scalar} or \code{NULL}. Specifies assay to
#' test. Tests are run per feature. (Default: \code{NULL})
#'
#' @param row.var \code{Character scalar} or \code{NULL}. Specifies variable
#' from \code{rowData(x)} to test. (Default: \code{NULL})
#'
#' @param col.var \code{Character scalar} or \code{NULL}. Specifies variable
#' from \code{colData(x)} to test. (Default: \code{NULL})
#'
#' @param formula \code{formula}. A formula specifying the grouping variable,
#' e.g., \code{~ SampleType}. The RHS specifies the comparison groups.
#' For >2 levels, pairwise comparisons are performed.
#'
#' @param split.by \code{Character vector} or \code{NULL}. Columns to split by.
#' Tests are run separately for each combination. (Default: \code{NULL})
#'
#' @param pair.by \code{Character scalar} or \code{NULL}. Column for pairing
#' samples in paired tests. (Default: \code{NULL})
#'
#' @param features \code{Character vector} or \code{NULL}. Specific features
#' to test when using \code{assay.type}. (Default: \code{NULL})
#'
#' @param var.equal \code{Logical scalar}. Assume equal variances?
#' (Default: \code{FALSE})
#'
#' @param p.adjust.method \code{Character scalar}. Method for p-value
#' adjustment. (Default: \code{"fdr"})
#'
#' @param name \code{Character scalar}. Column name prefix for results.
#' (Default: \code{"ttest"})
#'
#' @param ... Additional arguments passed to \code{rstatix::t_test}.
#'
#' @examples
#' data(GlobalPatterns, package = "mia")
#' tse <- GlobalPatterns
#' tse <- tse[1:50, tse$SampleType %in% c("Feces", "Skin")]
#'
#' # Test assay values (per feature)
#' res <- getTtest(tse, assay.type = "counts", formula = ~SampleType)
#'
#' # Test colData variable (e.g., alpha diversity)
#' tse <- mia::addAlpha(tse, index = "shannon_diversity")
#' res <- getTtest(tse, col.var = "shannon_diversity", formula = ~SampleType)
#'
#' @seealso
#' \code{\link[rstatix:t_test]{rstatix::t_test}},
#' \code{\link[daa:getWilcoxon]{getWilcoxon}}
#'
#' @export
NULL

#' @rdname getTtest
#' @export
#' @importFrom SingleCellExperiment altExp
#' @importFrom methods callNextMethod
setMethod("getTtest", "SingleCellExperiment", function (x, ... ){
x <- .check_and_get_altExp(x, ...)
res <- callNextMethod(x, ...)
return(res)
})

#' @rdname getTtest
#' @export
#' @importFrom SummarizedExperiment assay colData rowData
#' @importFrom rstatix t_test adjust_pvalue
#' @importFrom S4Vectors DataFrame
setMethod(
"getTtest", "SummarizedExperiment",
function (x, assay.type = NULL, row.var = NULL, col.var = NULL,
formula, split.by = NULL, pair.by = NULL, features = NULL,
var.equal = FALSE, p.adjust.method = "fdr", ... ){
############################# Input check ##############################
group <- .check_input(
x, assay.type, row.var, col.var, formula,
split.by, pair.by, features
)
if( !.is_a_bool(var.equal) ){
stop("'var.equal' must be TRUE or FALSE.", call. = FALSE)
}
########################### Input check end ############################
# Get y variable name (the column to test)
y <- c(assay.type, row.var, col.var)
# Get data based on source
df <- .get_data(
x, assay.type, row.var, col.var, group,
split.by, pair.by, features
)
# Run tests
paired <- !is.null(pair.by)
res <- .run_ttest(
df, y, group, split.by, paired, var.equal,
p.adjust.method, features, ...
)
return(res)
}
)

#' @rdname getTtest
#' @export
setMethod(
"addTtest", "SummarizedExperiment",
function (x, name = "ttest", ... ){
if( !.is_non_empty_string(name) ){
stop("'name' must be a single character value.", call. = FALSE)
}
res <- getTtest(x, ...)
x <- .add_values_to_colData(x, list(res$p.adj), paste0(name, "_padj"),
MARGIN = 1
)
return(x)
}
)

################################################################################
# Internal function using .calc_daa engine
################################################################################

#' @importFrom rstatix t_test
.run_ttest <- function (df, y, group, split.by, paired, var.equal,
p.adjust.method, features = NULL, ... ){
.calc_daa(
df = df, y = y, group = group, split.by = split.by,
paired = paired, FUN = rstatix::t_test,
p.adjust.method = p.adjust.method, features = features, var.equal = var.equal, ...
)
}
144 changes: 144 additions & 0 deletions R/getWilcoxon.R
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#' @name
#' getWilcoxon
#'
#' @title
#' Perform Wilcoxon rank-sum test
#'
#' @description
#' These functions perform Wilcoxon rank-sum test (Mann-Whitney U) to compare
#' values between two groups.
#'
#' @details
#' The Wilcoxon rank-sum test is a non-parametric test used to compare two
#' independent groups. It is suitable when data does not meet normality
#' assumptions.
#'
#' Specify exactly one of \code{assay.type}, \code{row.var}, or \code{col.var}
#' to define the values to test.
#'
#' @return
#' \code{getWilcoxon} returns a \code{DataFrame} with test results.
#' \code{addWilcoxon} returns \code{x} with results added to \code{rowData(x)}.
#'
#' @param x A \code{SummarizedExperiment} object.
#'
#' @param assay.type \code{Character scalar} or \code{NULL}. Specifies assay to
#' test. Tests are run per feature. (Default: \code{NULL})
#'
#' @param row.var \code{Character scalar} or \code{NULL}. Specifies variable
#' from \code{rowData(x)} to test. (Default: \code{NULL})
#'
#' @param col.var \code{Character scalar} or \code{NULL}. Specifies variable
#' from \code{colData(x)} to test. (Default: \code{NULL})
#'
#' @param formula \code{formula}. A formula specifying the grouping variable,
#' e.g., \code{~ SampleType}. The RHS specifies the comparison groups.
#' For >2 levels, pairwise comparisons are performed.
#'
#' @param split.by \code{Character vector} or \code{NULL}. Columns to split by.
#' Tests are run separately for each combination. (Default: \code{NULL})
#'
#' @param pair.by \code{Character scalar} or \code{NULL}. Column for pairing
#' samples in paired tests. (Default: \code{NULL})
#'
#' @param features \code{Character vector} or \code{NULL}. Specific features
#' to test when using \code{assay.type}. (Default: \code{NULL})
#'
#' @param p.adjust.method \code{Character scalar}. Method for p-value
#' adjustment. (Default: \code{"fdr"})
#'
#' @param name \code{Character scalar}. Column name prefix for results.
#' (Default: \code{"wilcoxon"})
#'
#' @param ... Additional arguments passed to \code{rstatix::wilcox_test}.
#'
#' @examples
#' data(GlobalPatterns, package = "mia")
#' tse <- GlobalPatterns
#' tse <- tse[1:50, tse$SampleType %in% c("Feces", "Skin")]
#'
#' # Test assay values (per feature)
#' res <- getWilcoxon(tse, assay.type = "counts", formula = ~SampleType)
#'
#' # Test colData variable (e.g., alpha diversity)
#' tse <- mia::addAlpha(tse, index = "shannon_diversity")
#' res <- getWilcoxon(tse, col.var = "shannon_diversity", formula = ~SampleType)
#'
#' @seealso
#' \code{\link[rstatix:wilcox_test]{rstatix::wilcox_test}},
#' \code{\link[daa:getTtest]{getTtest}}
#'
#' @export
NULL

#' @rdname getWilcoxon
#' @export
#' @importFrom SingleCellExperiment altExp
#' @importFrom methods callNextMethod
setMethod("getWilcoxon", "SingleCellExperiment", function (x, ... ){
x <- .check_and_get_altExp(x, ...)
res <- callNextMethod(x, ...)
return(res)
})

#' @rdname getWilcoxon
#' @export
#' @importFrom SummarizedExperiment assay colData rowData
#' @importFrom rstatix wilcox_test adjust_pvalue
#' @importFrom S4Vectors DataFrame
setMethod(
"getWilcoxon", "SummarizedExperiment",
function (x, assay.type = NULL, row.var = NULL, col.var = NULL,
formula, split.by = NULL, pair.by = NULL, features = NULL,
p.adjust.method = "fdr", ... ){
############################# Input check ##############################
group <- .check_input(
x, assay.type, row.var, col.var, formula,
split.by, pair.by, features
)
########################### Input check end ############################
# Get y variable name (the column to test)
y <- c(assay.type, row.var, col.var)
# Get data based on source
df <- .get_data(
x, assay.type, row.var, col.var, group,
split.by, pair.by, features
)
# Run tests
paired <- !is.null(pair.by)
res <- .run_wilcoxon(
df, y, group, split.by, paired,
p.adjust.method, features, ...
)
return(res)
}
)

#' @rdname getWilcoxon
#' @export
setMethod(
"addWilcoxon", "SummarizedExperiment",
function (x, name = "wilcoxon", ... ){
if( !.is_non_empty_string(name) ){
stop("'name' must be a single character value.", call. = FALSE)
}
res <- getWilcoxon(x, ...)
x <- .add_values_to_colData(x, list(res$p.adj), paste0(name, "_padj"),
MARGIN = 1
)
return(x)
}
)

################################################################################
# Internal function using .calc_daa engine
################################################################################

#' @importFrom rstatix wilcox_test
.run_wilcoxon <- function (df, y, group, split.by, paired, p.adjust.method, features = NULL, ... ){
.calc_daa(
df = df, y = y, group = group, split.by = split.by,
paired = paired, FUN = rstatix::wilcox_test,
p.adjust.method = p.adjust.method, features = features, ...
)
}
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