Fix CI trouble and problem with R3.5.1 (#6)

* test travis with one core fore xcell

* fix problem with quantiseq rownames in R3.5

* fix docstring of deconvolute

* update man

DESCRIPTION

@@ -53,4 +53,4 @@ Roxygen: list(markdown = TRUE)
 LazyData: true
 URL: https://github.com/grst/immunedeconv
 BugReports: https://github.com/grst/immunedeconv/issues
-RoxygenNote: 6.0.1
+RoxygenNote: 6.1.1

R/immune_deconvolution_methods.R

@@ -134,11 +134,15 @@ deconvolute_epic = function(gene_expression_matrix, tumor, scale_mrna, ...) {
 
 
 deconvolute_quantiseq = function(gene_expresssion_matrix, tumor, arrays, scale_mrna) {
-  deconvolute_quantiseq.default(gene_expresssion_matrix, tumor=tumor, arrays=arrays, mRNAscale = scale_mrna) %>%
+  res = deconvolute_quantiseq.default(gene_expresssion_matrix, tumor=tumor, arrays=arrays, mRNAscale = scale_mrna)
+  sample_names = res$Sample
+  res_mat = res %>%
     as_tibble() %>%
     select(-Sample) %>%
-    as.matrix() %>%
-    t()
+    as.matrix()
+  rownames(res_mat) = sample_names
+
+  t(res_mat)
 }
 
 deconvolute_cibersort = function(gene_expression_matrix,
@@ -212,7 +216,7 @@ eset_to_matrix = function(eset, column) {
 #'   Use this to exclude e.g. noisy genes.
 #' @param scale_mrna logical. If FALSE, disable correction for mRNA content of different cell types.
 #'   This is supported by methods that compute an absolute score (EPIC and quanTIseq)
-#' @param expected_cell_types. Limit the anlysis to the cell types given in this list. If the cell
+#' @param expected_cell_types Limit the anlysis to the cell types given in this list. If the cell
 #'   types present in the sample are known *a priori*, setting this can improve results for
 #'   xCell (see https://github.com/grst/immunedeconv/issues/1).
 #' @param ... arguments passed to the respective method

tests/testthat/test_deconvolution.R

@@ -55,6 +55,7 @@ test_that("generic deconvolution works for all methods", {
   lapply(deconvolution_methods, function(method) {
     # cibersort requires the binary path to be set, n/a in unittest.
     if(!method %in% c("cibersort", "cibersort_abs")) {
+      print(paste0("method is ", method))
       res = deconvolute(test_mat, method, indications=rep("brca", ncol(test_mat)),
                         tumor=TRUE, arrays=FALSE, rmgenes=c("ALB", "ERBB2"),
                         expected_cell_types=c("T cell CD4+", "T cell CD8+", "Macrophage", "NK cell"),
@@ -71,6 +72,7 @@ test_that("generic deconvolution works for all methods, without extra arguments"
   lapply(deconvolution_methods, function(method) {
     # cibersort requires the binary path to be set, n/a in unittest.
     if(!method %in% c("cibersort", "cibersort_abs")) {
+      print(paste0("method is ", method))
       res = deconvolute(test_mat, method, indications=rep("brca", ncol(test_mat)))
       # matrix has the 'cell type' column -> +1
       assert("matrix dimensions consistent", ncol(res) == ncol(test_mat) + 1)