support multigroup

R/lefser.R

@@ -169,9 +169,11 @@ filterKruskal <- function(relab, group, p.value, method = method) {
 #' when 'blockCol' is present (default 0.05). If multiple hypothesis testing is 
 #' performed, this threshold is applied to corrected p-values.
 #' @param lda.threshold numeric(1) The effect size threshold (default 2.0).
+#'
 #' @param groupCol character(1) Column name in `colData(relab)` indicating
-#' groups, usually a factor with two levels (e.g., `c("cases", "controls")`;
-#' default "GROUP").
+#'   groups, usually a factor with two or more levels (e.g.,
+#'   `c("cases", "controls")`; default `"GROUP"`).
+#'
 #' @param blockCol character(1) Optional column name in `colData(relab)`
 #' indicating the blocks, usually a factor with two levels (e.g.,
 #' `c("adult", "senior")`; default NULL).
@@ -253,10 +255,8 @@ lefser <-
     groupf <- colData(relab)[[groupCol]]
     groupf <- as.factor(groupf)
     lgroupf <- levels(groupf)
-    if (is.null(groupf) || !identical(length(lgroupf), 2L)) {
-        msg <- "'groupCol' must refer to a valid dichotomous (two-level) variable"
-        stop(msg) # ensure the class has only two levels
-    }
+    if (is.null(groupf) || length(lgroupf) < 2L)
+        stop("'groupCol' must be a valid two or more level variable")
     message(
         "The outcome variable is specified as '", groupCol,
         "' and the reference category is '", lgroupf[1],