tests/testthat/test_testInteractions.R
In BodenmillerGroup/imcRtools: Methods for imaging mass cytometry data analysis
test_that("testInteractions function works", {
library(cytomapper)
library(BiocParallel)
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
################################ classic ###################################
expect_silent(cur_out <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
colPairName = "knn_interaction_graph",
iter = 100))
expect_silent(cur_out <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "classic",
colPairName = "knn_interaction_graph",
iter = 100,
BPPARAM = SerialParam(RNGseed = 123)))
expect_silent(cur_out_2 <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "classic",
colPairName = "knn_interaction_graph",
iter = 100,
BPPARAM = SerialParam(RNGseed = 123)))
expect_identical(cur_out, cur_out_2)
# Check numerical values
expect_equal(cur_out$ct, c(1.8235294, 0.4705882, 0.7058824, 0.8750000, 0.2500000,
1.8750000, 0.1250000, 0.1704545, 2.7045455, 2.3111111, 0.5111111,
0.1777778, 0.7837838, 1.5675676, 0.6486486, 0.2000000, 0.6250000,
2.1750000, NA, NA, NA, NA, 2.3636364, 0.6363636, NA, 0.7049180, 2.2950820),
tolerance = 0.00001)
expect_equal(cur_out$p_gt, c(0.00990099, 0.01980198, 1.00000000, 0.02970297, 0.53465347, 0.96039604,
1.00000000, 0.90099010, 0.00990099, 0.00990099, 1.00000000, 1.00000000,
0.99009901, 0.00990099, 1.00000000, 1.00000000, 0.99009901, 0.00990099,
NA, NA, NA, NA, 0.00990099, 1.00000000, NA, 1.00000000, 0.00990099),
tolerance = 0.00001)
expect_equal(cur_out$p_lt, c(1.00000000, 0.99009901, 0.00990099, 1.00000000, 0.80198020,
0.06930693, 0.00990099, 0.19801980, 1.00000000, 1.00000000,
0.00990099, 0.00990099, 0.01980198, 1.00000000, 0.00990099,
0.00990099, 0.01980198, 1.00000000, NA, NA, NA, NA,
1.00000000, 0.00990099, NA, 0.00990099, 1.00000000),
tolerance = 0.00001)
# Check against countInteractions
expect_silent(cur_sn <- countInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "classic",
colPairName = "knn_interaction_graph"))
expect_equal(cur_out$group_by, as.character(cur_sn$group_by))
expect_equal(cur_out$from_label, as.character(cur_sn$from_label))
expect_equal(cur_out$to_label, as.character(cur_sn$to_label))
expect_equal(cur_out$ct, cur_sn$ct)
cur_test <- cur_out[!is.na(cur_out$ct),]
expect_equal(rowMin(as.matrix(cur_test[,c("p_gt", "p_lt")])), cur_test$p)
expect_equal(cur_test$p_gt < cur_test$p_lt, cur_test$interaction)
expect_equal(cur_test$p < 0.01, cur_test$sig)
expect_equal(cur_test$sig * sign(cur_test$interaction - 0.5), cur_test$sigval)
expect_silent(cur_out_2 <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "classic",
colPairName = "knn_interaction_graph",
iter = 100, p_threshold = 0.5,
BPPARAM = SerialParam(RNGseed = 123)))
expect_equal(cur_out_2$group_by, as.character(cur_sn$group_by))
expect_equal(cur_out_2$from_label, as.character(cur_sn$from_label))
expect_equal(cur_out_2$to_label, as.character(cur_sn$to_label))
expect_equal(cur_out_2$ct, cur_sn$ct)
cur_test <- cur_out_2[!is.na(cur_out_2$ct),]
expect_equal(rowMin(as.matrix(cur_test[,c("p_gt", "p_lt")])), cur_test$p)
expect_equal(cur_test$p_gt < cur_test$p_lt, cur_test$interaction)
expect_equal(cur_test$p < 0.5, cur_test$sig)
expect_equal(cur_test$sig * sign(cur_test$interaction - 0.5), cur_test$sigval)
################################ histocat ###################################
expect_silent(cur_out <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "histocat",
colPairName = "knn_interaction_graph",
iter = 100,
BPPARAM = SerialParam(RNGseed = 123)))
expect_silent(cur_out_2 <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "histocat",
colPairName = "knn_interaction_graph",
iter = 100,
BPPARAM = SerialParam(RNGseed = 123)))
expect_identical(cur_out, cur_out_2)
# Check numerical values
expect_equal(cur_out$ct, c(1.937500, 1.142857, 1.333333, 1.166667, 1.000000,
1.875000, 1.222222, 1.363636, 2.735632, 2.476190,
1.352941, 1.142857, 1.450000, 1.757576, 1.263158,
1.333333, 1.666667, 2.636364, NA, NA, NA, NA,
2.363636, 1.312500, NA, 1.653846, 2.456140),
tolerance = 0.00001)
expect_equal(cur_out$p_gt, c(0.02970297, 0.19801980, 1.00000000, 0.43564356,
0.71287129, 0.98019802, 0.19801980, 0.00990099,
0.00990099, 0.00990099, 0.51485149, 1.00000000,
0.57425743, 0.00990099, 0.93069307, 0.88118812,
0.00990099, 0.00990099, NA, NA, NA, NA, 0.00990099,
1.00000000, NA, 0.83168317, 0.00990099),
tolerance = 0.00001)
expect_equal(cur_out$p_lt, c(0.98019802, 0.81188119, 0.00990099, 0.57425743, 0.94059406,
0.02970297, 0.82178218, 1.00000000, 1.00000000,
1.00000000, 0.51485149, 0.00990099, 0.43564356,
1.00000000, 0.07920792, 0.15841584, 1.00000000,
1.00000000, NA, NA, NA, NA, 1.00000000, 0.00990099,
NA, 0.18811881, 1.00000000),
tolerance = 0.00001)
# Check against countInteractions
expect_silent(cur_sn <- countInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "histocat",
colPairName = "knn_interaction_graph"))
expect_equal(cur_out$group_by, as.character(cur_sn$group_by))
expect_equal(cur_out$from_label, as.character(cur_sn$from_label))
expect_equal(cur_out$to_label, as.character(cur_sn$to_label))
expect_equal(cur_out$ct, cur_sn$ct)
cur_test <- cur_out[!is.na(cur_out$ct),]
expect_equal(rowMin(as.matrix(cur_test[,c("p_gt", "p_lt")])), cur_test$p)
expect_equal(cur_test$p_gt < cur_test$p_lt, cur_test$interaction)
expect_equal(cur_test$p < 0.01, cur_test$sig)
expect_equal(cur_test$sig * sign(cur_test$interaction - 0.5), cur_test$sigval)
expect_silent(cur_out_2 <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "histocat",
colPairName = "knn_interaction_graph",
iter = 100, p_threshold = 0.5,
BPPARAM = SerialParam(RNGseed = 123)))
expect_equal(cur_out_2$group_by, as.character(cur_sn$group_by))
expect_equal(cur_out_2$from_label, as.character(cur_sn$from_label))
expect_equal(cur_out_2$to_label, as.character(cur_sn$to_label))
expect_equal(cur_out_2$ct, cur_sn$ct)
cur_test <- cur_out_2[!is.na(cur_out_2$ct),]
expect_equal(rowMin(as.matrix(cur_test[,c("p_gt", "p_lt")])), cur_test$p)
expect_equal(cur_test$p_gt < cur_test$p_lt, cur_test$interaction)
expect_equal(cur_test$p < 0.5, cur_test$sig)
expect_equal(cur_test$sig * sign(cur_test$interaction - 0.5), cur_test$sigval)
################################ patch ###################################
expect_silent(cur_out <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "patch",
patch_size = 3,
colPairName = "knn_interaction_graph",
iter = 100,
BPPARAM = SerialParam(RNGseed = 123)))
expect_silent(cur_out_2 <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "patch",
patch_size = 3,
colPairName = "knn_interaction_graph",
iter = 100,
BPPARAM = SerialParam(RNGseed = 123)))
expect_identical(cur_out, cur_out_2)
# Check numerical values
expect_equal(cur_out$ct, c(0.23529412, 0.00000000, 0.00000000, 0.00000000,
0.00000000, 0.25000000, 0.00000000, 0.00000000,
0.81818182, 0.55555556, 0.02222222, 0.00000000,
0.02702703, 0.05405405, 0.00000000, 0.00000000,
0.12500000, 0.52500000, NA, NA, NA, NA, 0.51515152,
0.00000000, NA, 0.06557377, 0.57377049),
tolerance = 0.00001)
expect_equal(cur_out$p_gt, c(0.00990099, 1.00000000, 1.00000000, 1.00000000, 1.00000000,
0.98019802, 1.00000000, 1.00000000, 0.00990099, 0.00990099,
0.63366337, 1.00000000, 0.82178218, 0.21782178, 1.00000000,
1.00000000, 0.00990099, 0.00990099, NA, NA, NA, NA, 0.00990099,
1.00000000, NA, 0.99009901, 0.00990099),
tolerance = 0.00001)
expect_equal(cur_out$p_lt, c(1.00000000, 1.00000000, 0.00990099, 0.97029703, 1.00000000,
0.18811881, 0.80198020, 0.97029703, 1.00000000, 1.00000000,
0.64356436, 0.22772277, 0.43564356, 0.94059406, 0.28712871,
0.14851485, 1.00000000, 1.00000000, NA, NA, NA, NA,
1.00000000, 0.00990099, NA, 0.03960396, 1.00000000),
tolerance = 0.00001)
# Check against countInteractions
expect_silent(cur_sn <- countInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "patch",
patch_size = 3,
colPairName = "knn_interaction_graph"))
expect_equal(cur_out$group_by, as.character(cur_sn$group_by))
expect_equal(cur_out$from_label, as.character(cur_sn$from_label))
expect_equal(cur_out$to_label, as.character(cur_sn$to_label))
expect_equal(cur_out$ct, cur_sn$ct)
cur_test <- cur_out[!is.na(cur_out$ct),]
expect_equal(rowMin(as.matrix(cur_test[,c("p_gt", "p_lt")])), cur_test$p)
expect_equal(cur_test$p_gt < cur_test$p_lt, cur_test$interaction)
expect_equal(cur_test$p < 0.01, cur_test$sig)
expect_equal(cur_test$sig * sign(cur_test$interaction - 0.5), cur_test$sigval)
expect_silent(cur_out_2 <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "patch",
patch_size = 3,
colPairName = "knn_interaction_graph",
iter = 100, p_threshold = 0.5,
BPPARAM = SerialParam(RNGseed = 123)))
expect_equal(cur_out_2$group_by, as.character(cur_sn$group_by))
expect_equal(cur_out_2$from_label, as.character(cur_sn$from_label))
expect_equal(cur_out_2$to_label, as.character(cur_sn$to_label))
expect_equal(cur_out_2$ct, cur_sn$ct)
cur_test <- cur_out_2[!is.na(cur_out_2$ct),]
expect_equal(rowMin(as.matrix(cur_test[,c("p_gt", "p_lt")])), cur_test$p)
expect_equal(cur_test$p_gt < cur_test$p_lt, cur_test$interaction)
expect_equal(cur_test$p < 0.5, cur_test$sig)
expect_equal(cur_test$sig * sign(cur_test$interaction - 0.5), cur_test$sigval)
# Corner case settings
# one cell of a given cell-type and no neighbors
cur_sce <- pancreasSCE
cur_sce$CellType[123] <- "test"
cur_sce <- buildSpatialGraph(cur_sce, img_id = "ImageNb",
type = "expansion", threshold = 7)
plotSpatial(cur_sce, node_color_by = "CellType", img_id = "ImageNb",
draw_edges = TRUE, colPairName = "expansion_interaction_graph")
expect_silent(cur_out <- testInteractions(cur_sce,
group_by = "ImageNb",
label = "CellType",
colPairName = "expansion_interaction_graph",
iter = 100,
BPPARAM = SerialParam(RNGseed = 123)))
# Check numerical values
expect_equal(cur_out$ct, c(0.235294117647059, 0, 0, NA, 0, 0, 0, NA, 0, 0, 0.204545454545455,
NA, NA, NA, NA, NA, 0.133333333333333, 0.0666666666666667, 0,
0, 0.0810810810810811, 0.0540540540540541, 0.0810810810810811,
0, 0, 0.0769230769230769, 0.102564102564103, 0, 0, 0, 0, 0, NA,
NA, NA, NA, NA, 0.303030303030303, 0.0606060606060606, NA, NA,
0.0655737704918033, 0.360655737704918, NA, NA, NA, NA, NA),
tolerance = 0.00001)
expect_equal(cur_out$p_gt, c(0.0198019801980198, 1, 1, NA, 1, 1, 1, NA, 1, 1, 0.108910891089109,
NA, NA, NA, NA, NA, 0.227722772277228, 0.504950495049505, 1,
1, 0.504950495049505, 0.702970297029703, 0.455445544554455, 1,
1, 0.455445544554455, 0.376237623762376, 1, 1, 1, 1, 1, NA, NA,
NA, NA, NA, 0.108910891089109, 1, NA, NA, 1, 0.0198019801980198,
NA, NA, NA, NA, NA),
tolerance = 0.00001)
expect_equal(cur_out$p_lt, c(1, 0.782178217821782, 0.0297029702970297, NA, 0.782178217821782,
0.97029702970297, 0.247524752475248, NA, 0.0297029702970297,
0.247524752475248, 0.99009900990099, NA, NA, NA, NA, NA, 0.940594059405941,
0.732673267326733, 0.0594059405940594, 0.930693069306931, 0.732673267326733,
0.693069306930693, 0.762376237623762, 0.940594059405941, 0.0594059405940594,
0.762376237623762, 0.940594059405941, 0.95049504950495, 0.930693069306931,
0.940594059405941, 0.95049504950495, 1, NA, NA, NA, NA, NA, 0.96039603960396,
0.0099009900990099, NA, NA, 0.0099009900990099, 1, NA, NA, NA,
NA, NA),
tolerance = 0.00001)
# Check against countInteractions
expect_silent(cur_sn <- countInteractions(cur_sce,
group_by = "ImageNb",
label = "CellType",
colPairName = "expansion_interaction_graph"))
expect_equal(cur_out$group_by, as.character(cur_sn$group_by))
expect_equal(cur_out$from_label, as.character(cur_sn$from_label))
expect_equal(cur_out$to_label, as.character(cur_sn$to_label))
expect_equal(cur_out$ct, cur_sn$ct)
cur_test <- cur_out[!is.na(cur_out$ct),]
expect_equal(rowMin(as.matrix(cur_test[,c("p_gt", "p_lt")])), cur_test$p)
expect_equal(cur_test$p_gt < cur_test$p_lt, cur_test$interaction)
expect_equal(cur_test$p < 0.01, cur_test$sig)
expect_equal(cur_test$sig * sign(cur_test$interaction - 0.5), cur_test$sigval)
## histocat
expect_silent(cur_out <- testInteractions(cur_sce,
group_by = "ImageNb",
label = "CellType",
method = "histocat",
colPairName = "expansion_interaction_graph",
iter = 100,
BPPARAM = SerialParam(RNGseed = 123)))
expect_equal(cur_out$ct, c(1.000000, 0.000000, 0.000000, NA, 0.000000, 0.000000,
0.000000, NA, 0.000000, 0.000000, 1.058824, NA,
NA, NA, NA, NA, 1.000000, 1.000000,
0.000000, 0.000000, 1.000000, 1.000000, 1.000000, 0.000000,
0.000000, 1.000000, 1.000000, 0.000000, 0.000000, 0.000000, 0.000000,
0.000000, NA, NA, NA, NA,
NA, 1.250000, 1.000000, NA, NA, 1.000000,
1.100000, NA, NA, NA, NA, NA),
tolerance = 0.00001)
expect_equal(cur_out$p_gt, c(0.158415841584158, 1, 1, NA, 1, 1, 1, NA, 1, 1, 0.495049504950495,
NA, NA, NA, NA, NA, 0.792079207920792, 0.920792079207921, 1,
1, 0.920792079207921, 0.702970297029703, 0.910891089108911, 1,
1, 0.910891089108911, 0.742574257425743, 1, 1, 1, 1, 1, NA, NA,
NA, NA, NA, 0.099009900990099, 1, NA, NA, 1, 0.465346534653465,
NA, NA, NA, NA, NA),
tolerance = 0.00001)
expect_equal(cur_out$p_lt, c(0.99009900990099, 0.782178217821782, 0.0297029702970297, NA,
0.782178217821782, 0.97029702970297, 0.247524752475248, NA, 0.0297029702970297,
0.247524752475248, 0.574257425742574, NA, NA, NA, NA, NA, 0.900990099009901,
0.930693069306931, 0.0594059405940594, 0.930693069306931, 0.900990099009901,
0.99009900990099, 0.96039603960396, 0.940594059405941, 0.0594059405940594,
0.95049504950495, 0.910891089108911, 0.95049504950495, 0.930693069306931,
0.940594059405941, 0.95049504950495, 1, NA, NA, NA, NA, NA, 0.940594059405941,
0.297029702970297, NA, NA, 0.297029702970297, 0.544554455445545,
NA, NA, NA, NA, NA),
tolerance = 0.00001)
# Check against countInteractions
expect_silent(cur_sn <- countInteractions(cur_sce,
group_by = "ImageNb",
label = "CellType",
method = "histocat",
colPairName = "expansion_interaction_graph"))
expect_equal(cur_out$group_by, as.character(cur_sn$group_by))
expect_equal(cur_out$from_label, as.character(cur_sn$from_label))
expect_equal(cur_out$to_label, as.character(cur_sn$to_label))
expect_equal(cur_out$ct, cur_sn$ct)
cur_test <- cur_out[!is.na(cur_out$ct),]
expect_equal(rowMin(as.matrix(cur_test[,c("p_gt", "p_lt")])), cur_test$p)
expect_equal(cur_test$p_gt < cur_test$p_lt, cur_test$interaction)
expect_equal(cur_test$p < 0.01, cur_test$sig)
expect_equal(cur_test$sig * sign(cur_test$interaction - 0.5), cur_test$sigval)
## patch
expect_silent(cur_out <- testInteractions(cur_sce,
group_by = "ImageNb",
label = "CellType",
method = "patch",
patch_size = 1,
colPairName = "expansion_interaction_graph",
iter = 100,
BPPARAM = SerialParam(RNGseed = 123)))
expect_equal(cur_out$ct, c(0.235294117647059, 0, 0, NA, 0, 0, 0, NA, 0, 0, 0.193181818181818,
NA, NA, NA, NA, NA, 0.133333333333333, 0.0666666666666667, 0,
0, 0.0810810810810811, 0.0540540540540541, 0.0810810810810811,
0, 0, 0.0769230769230769, 0.102564102564103, 0, 0, 0, 0, 0, NA,
NA, NA, NA, NA, 0.242424242424242, 0.0606060606060606, NA, NA,
0.0655737704918033, 0.327868852459016, NA, NA, NA, NA, NA),
tolerance = 0.00001)
expect_equal(cur_out$p_gt, c(0.0099009900990099, 1, 1, NA, 1, 1, 1, NA, 1, 1, 0.108910891089109,
NA, NA, NA, NA, NA, 0.198019801980198, 0.495049504950495, 1,
1, 0.495049504950495, 0.702970297029703, 0.455445544554455, 1,
1, 0.445544554455446, 0.326732673267327, 1, 1, 1, 1, 1, NA, NA,
NA, NA, NA, 0.168316831683168, 1, NA, NA, 1, 0.0099009900990099,
NA, NA, NA, NA, NA),
tolerance = 0.00001)
expect_equal(cur_out$p_lt, c(1, 0.782178217821782, 0.0297029702970297, NA, 0.782178217821782,
0.97029702970297, 0.247524752475248, NA, 0.0297029702970297,
0.247524752475248, 0.96039603960396, NA, NA, NA, NA, NA, 0.940594059405941,
0.752475247524752, 0.0594059405940594, 0.930693069306931, 0.792079207920792,
0.693069306930693, 0.762376237623762, 0.940594059405941, 0.0594059405940594,
0.772277227722772, 0.940594059405941, 0.95049504950495, 0.930693069306931,
0.940594059405941, 0.95049504950495, 1, NA, NA, NA, NA, NA, 0.900990099009901,
0.0099009900990099, NA, NA, 0.0099009900990099, 1, NA, NA, NA,
NA, NA),
tolerance = 0.00001)
# Check against countInteractions
expect_silent(cur_sn <- countInteractions(cur_sce,
group_by = "ImageNb",
label = "CellType",
method = "patch",
patch_size = 1,
colPairName = "expansion_interaction_graph"))
expect_equal(cur_out$group_by, as.character(cur_sn$group_by))
expect_equal(cur_out$from_label, as.character(cur_sn$from_label))
expect_equal(cur_out$to_label, as.character(cur_sn$to_label))
expect_equal(cur_out$ct, cur_sn$ct)
cur_test <- cur_out[!is.na(cur_out$ct),]
expect_equal(rowMin(as.matrix(cur_test[,c("p_gt", "p_lt")])), cur_test$p)
expect_equal(cur_test$p_gt < cur_test$p_lt, cur_test$interaction)
expect_equal(cur_test$p < 0.01, cur_test$sig)
expect_equal(cur_test$sig * sign(cur_test$interaction - 0.5), cur_test$sigval)
# Return samples
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "expansion",
threshold = 20)
expect_silent(cur_out <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "classic",
iter = 100,
colPairName = "expansion_interaction_graph",
return_samples = TRUE,
BPPARAM = SerialParam(RNGseed = 123)))
expect_silent(cur_out_2 <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "classic",
iter = 100,
colPairName = "expansion_interaction_graph",
BPPARAM = SerialParam(RNGseed = 123)))
expect_equal(cur_out$group_by, as.character(cur_out_2$group_by))
expect_equal(cur_out$from_label, as.character(cur_out_2$from_label))
expect_equal(cur_out$to_label, as.character(cur_out_2$to_label))
expect_equal(cur_out$ct, cur_out_2$ct)
expect_equal(cur_out$p_lt, cur_out_2$p_lt)
expect_equal(cur_out$p_gt, cur_out_2$p_gt)
expect_equal(cur_out$interaction, cur_out_2$interaction)
expect_equal(cur_out$p, cur_out_2$p)
expect_equal(cur_out$sig, cur_out_2$sig)
expect_equal(cur_out$sigval, cur_out_2$sigval)
expect_equal(dim(cur_out), c(27, 110))
expect_equal(cur_out$iter_1, c(1.29411764705882, 0.352941176470588, 7.29411764705882, 0.75,
0.25, 7.125, 1.40909090909091, 0.647727272727273, 7.34090909090909,
3.64444444444444, 3.22222222222222, 2.95555555555556, 3.91891891891892,
3.08108108108108, 3.37837837837838, 3.325, 3.125, 3.3, 0, 0,
0, 0, 5.6969696969697, 5.51515151515152, 0, 5.9672131147541,
4.81967213114754))
expect_equal(cur_out$iter_13, c(1.05882352941176, 0.470588235294118, 7.64705882352941, 1, 0.5,
6.5, 1.47727272727273, 0.590909090909091, 7.29545454545454, 4.31111111111111,
2.88888888888889, 2.75555555555556, 3.51351351351351, 3.67567567567568,
3.16216216216216, 3.1, 2.925, 3.6, 0, 0, 0, 0, 6.36363636363636,
5.03030303030303, 0, 5.44262295081967, 5.14754098360656))
expect_equal(cur_out$iter_26, c(1.29411764705882, 0.882352941176471, 7.58823529411765, 1.875,
0.25, 7.125, 1.46590909090909, 0.647727272727273, 7.02272727272727,
3.91111111111111, 3.42222222222222, 3.11111111111111, 4.16216216216216,
2.54054054054054, 3.13513513513514, 3.5, 2.9, 3.15, 0, 0, 0,
0, 6.06060606060606, 5.09090909090909, 0, 5.50819672131148, 5.34426229508197
))
expect_equal(cur_out$iter_67, c(1.64705882352941, 0.529411764705882, 6.29411764705882, 1.125,
0.25, 6.75, 1.21590909090909, 0.613636363636364, 7.65909090909091,
4.53333333333333, 2.86666666666667, 3.44444444444444, 3.48648648648649,
2.32432432432432, 3.13513513513514, 3.875, 2.9, 3.15, 0, 0, 0,
0, 5.96969696969697, 5.33333333333333, 0, 5.77049180327869, 4.91803278688525
))
expect_equal(cur_out$iter_99, c(1.41176470588235, 0, 7.35294117647059, 0, 1.75, 8, 1.42045454545455,
0.727272727272727, 7.13636363636364, 3.91111111111111, 3.13333333333333,
3.53333333333333, 3.81081081081081, 2.86486486486486, 3.08108108108108,
3.975, 2.85, 2.65, 0, 0, 0, 0, 6.15151515151515, 5.31818181818182,
0, 5.75409836065574, 4.75409836065574))
# Fail
expect_error(testInteractions("test"),
regexp = "'object' not of type 'SingleCellExperiment'.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "test", label = "CellType",
colPairName = "knn_interaction_graph"),
regexp = "'group_by' not in colData(object).",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = 1, label = "CellType",
colPairName = "knn_interaction_graph"),
regexp = "'group_by' must be a single string.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "test",
colPairName = "knn_interaction_graph"),
regexp = "'label' not in colData(object).",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = 1,
colPairName = "knn_interaction_graph"),
regexp = "'label' must be a single string.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType",
colPairName = "test"),
regexp = "'colPairName' not in colPairNames(object).",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType", colPairName = 1),
regexp = "'colPairName' must be a single string.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType",
colPairName = "knn_interaction_graph",
method = "patch"),
regexp = "When method = 'patch', please specify 'patch_size'.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType",
colPairName = "knn_interaction_graph",
method = "patch", patch_size = "test"),
regexp = "'patch_size' must be a single numeric.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType",
colPairName = "knn_interaction_graph",
iter = "test"),
regexp = "'iter' must be a single positive numeric.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType",
colPairName = "knn_interaction_graph",
iter = c(1,2)),
regexp = "'iter' must be a single positive numeric.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType",
colPairName = "knn_interaction_graph",
iter = -20),
regexp = "'iter' must be a single positive numeric.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType",
colPairName = "knn_interaction_graph",
p_threshold = "test"),
regexp = "'p_threshold' must be a single numeric between 0 and 1.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType",
colPairName = "knn_interaction_graph",
p_threshold = c(1,2)),
regexp = "'p_threshold' must be a single numeric between 0 and 1.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType",
colPairName = "knn_interaction_graph",
p_threshold = 3),
regexp = "'p_threshold' must be a single numeric between 0 and 1.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType",
colPairName = "knn_interaction_graph",
return_samples = 1),
regexp = "'return_samples' must be a single logical.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType",
colPairName = "knn_interaction_graph",
return_samples = c("test", "test2")),
regexp = "'return_samples' must be a single logical.",
fixed = TRUE)
})
test_that("testInteractions function works if cells are not grouped by image", {
library(cytomapper)
library(BiocParallel)
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "expansion",
threshold = 10)
plotSpatial(pancreasSCE, img_id = "ImageNb", draw_edges = TRUE,
colPairName = "expansion_interaction_graph",
node_color_by = "CellType", scales = "free")
out <- testInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "classic",
iter = 200, colPairName = "expansion_interaction_graph",
BPPARAM = SerialParam(RNGseed = 111))
set.seed(123)
cur_sce <- pancreasSCE[,sample(ncol(pancreasSCE))]
plotSpatial(cur_sce, img_id = "ImageNb", draw_edges = TRUE,
colPairName = "expansion_interaction_graph",
node_color_by = "CellType", scales = "free")
out2 <- testInteractions(cur_sce, group_by = "ImageNb",
label = "CellType", method = "classic",
iter = 200,
colPairName = "expansion_interaction_graph",
BPPARAM = SerialParam(RNGseed = 111))
## Sampling is different between grouped and non-grouped cells
## Therefore the p values are close but not identical
expect_equal(out$group_by, out2$group_by)
expect_equal(out$from_label, out2$from_label)
expect_equal(out$to_label, out2$to_label)
expect_equal(out$ct, out2$ct)
expect_equal(out$p_gt, out2$p_gt, tolerance = 0.1)
expect_equal(out$p_lt, out2$p_lt, tolerance = 0.1)
expect_equal(out$interaction, out2$interaction)
expect_equal(out$p, out2$p, tolerance = 0.1)
expect_equal(out$sig, out2$sig)
expect_equal(out$sigval, out2$sigval)
out <- testInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "histocat",
iter = 400, colPairName = "expansion_interaction_graph",
BPPARAM = SerialParam(RNGseed = 111))
out2 <- testInteractions(cur_sce, group_by = "ImageNb",
label = "CellType", method = "histocat",
iter = 400,
colPairName = "expansion_interaction_graph",
BPPARAM = SerialParam(RNGseed = 111))
expect_equal(out$group_by, out2$group_by)
expect_equal(out$from_label, out2$from_label)
expect_equal(out$to_label, out2$to_label)
expect_equal(out$ct, out2$ct)
expect_equal(out$p_gt, out2$p_gt, tolerance = 0.1)
expect_equal(out$p_lt, out2$p_lt, tolerance = 0.1)
expect_equal(out$interaction, out2$interaction)
expect_equal(out$p, out2$p, tolerance = 0.1)
#expect_equal(out$sig, out2$sig)
#expect_equal(out$sigval, out2$sigval)
out <- testInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "patch", patch_size = 2,
iter = 300, colPairName = "expansion_interaction_graph",
BPPARAM = SerialParam(RNGseed = 111))
out2 <- testInteractions(cur_sce, group_by = "ImageNb",
label = "CellType", method = "patch", patch_size = 2,
iter = 300,
colPairName = "expansion_interaction_graph",
BPPARAM = SerialParam(RNGseed = 111))
expect_equal(out$group_by, out2$group_by)
expect_equal(out$from_label, out2$from_label)
expect_equal(out$to_label, out2$to_label)
expect_equal(out$ct, out2$ct)
expect_equal(out$p_gt, out2$p_gt, tolerance = 0.1)
expect_equal(out$p_lt, out2$p_lt, tolerance = 0.1)
expect_equal(out$interaction, out2$interaction)
expect_equal(out$p, out2$p, tolerance = 0.1)
#expect_equal(out$sig, out2$sig)
#expect_equal(out$sigval, out2$sigval)
})
BodenmillerGroup/imcRtools documentation built on July 1, 2024, 5:15 p.m.
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test_that("testInteractions function works", {
library(cytomapper)
library(BiocParallel)
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
################################ classic ###################################
expect_silent(cur_out <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
colPairName = "knn_interaction_graph",
iter = 100))
expect_silent(cur_out <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "classic",
colPairName = "knn_interaction_graph",
iter = 100,
BPPARAM = SerialParam(RNGseed = 123)))
expect_silent(cur_out_2 <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "classic",
colPairName = "knn_interaction_graph",
iter = 100,
BPPARAM = SerialParam(RNGseed = 123)))
expect_identical(cur_out, cur_out_2)
# Check numerical values
expect_equal(cur_out$ct, c(1.8235294, 0.4705882, 0.7058824, 0.8750000, 0.2500000,
1.8750000, 0.1250000, 0.1704545, 2.7045455, 2.3111111, 0.5111111,
0.1777778, 0.7837838, 1.5675676, 0.6486486, 0.2000000, 0.6250000,
2.1750000, NA, NA, NA, NA, 2.3636364, 0.6363636, NA, 0.7049180, 2.2950820),
tolerance = 0.00001)
expect_equal(cur_out$p_gt, c(0.00990099, 0.01980198, 1.00000000, 0.02970297, 0.53465347, 0.96039604,
1.00000000, 0.90099010, 0.00990099, 0.00990099, 1.00000000, 1.00000000,
0.99009901, 0.00990099, 1.00000000, 1.00000000, 0.99009901, 0.00990099,
NA, NA, NA, NA, 0.00990099, 1.00000000, NA, 1.00000000, 0.00990099),
tolerance = 0.00001)
expect_equal(cur_out$p_lt, c(1.00000000, 0.99009901, 0.00990099, 1.00000000, 0.80198020,
0.06930693, 0.00990099, 0.19801980, 1.00000000, 1.00000000,
0.00990099, 0.00990099, 0.01980198, 1.00000000, 0.00990099,
0.00990099, 0.01980198, 1.00000000, NA, NA, NA, NA,
1.00000000, 0.00990099, NA, 0.00990099, 1.00000000),
tolerance = 0.00001)
# Check against countInteractions
expect_silent(cur_sn <- countInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "classic",
colPairName = "knn_interaction_graph"))
expect_equal(cur_out$group_by, as.character(cur_sn$group_by))
expect_equal(cur_out$from_label, as.character(cur_sn$from_label))
expect_equal(cur_out$to_label, as.character(cur_sn$to_label))
expect_equal(cur_out$ct, cur_sn$ct)
cur_test <- cur_out[!is.na(cur_out$ct),]
expect_equal(rowMin(as.matrix(cur_test[,c("p_gt", "p_lt")])), cur_test$p)
expect_equal(cur_test$p_gt < cur_test$p_lt, cur_test$interaction)
expect_equal(cur_test$p < 0.01, cur_test$sig)
expect_equal(cur_test$sig * sign(cur_test$interaction - 0.5), cur_test$sigval)
expect_silent(cur_out_2 <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "classic",
colPairName = "knn_interaction_graph",
iter = 100, p_threshold = 0.5,
BPPARAM = SerialParam(RNGseed = 123)))
expect_equal(cur_out_2$group_by, as.character(cur_sn$group_by))
expect_equal(cur_out_2$from_label, as.character(cur_sn$from_label))
expect_equal(cur_out_2$to_label, as.character(cur_sn$to_label))
expect_equal(cur_out_2$ct, cur_sn$ct)
cur_test <- cur_out_2[!is.na(cur_out_2$ct),]
expect_equal(rowMin(as.matrix(cur_test[,c("p_gt", "p_lt")])), cur_test$p)
expect_equal(cur_test$p_gt < cur_test$p_lt, cur_test$interaction)
expect_equal(cur_test$p < 0.5, cur_test$sig)
expect_equal(cur_test$sig * sign(cur_test$interaction - 0.5), cur_test$sigval)
################################ histocat ###################################
expect_silent(cur_out <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "histocat",
colPairName = "knn_interaction_graph",
iter = 100,
BPPARAM = SerialParam(RNGseed = 123)))
expect_silent(cur_out_2 <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "histocat",
colPairName = "knn_interaction_graph",
iter = 100,
BPPARAM = SerialParam(RNGseed = 123)))
expect_identical(cur_out, cur_out_2)
# Check numerical values
expect_equal(cur_out$ct, c(1.937500, 1.142857, 1.333333, 1.166667, 1.000000,
1.875000, 1.222222, 1.363636, 2.735632, 2.476190,
1.352941, 1.142857, 1.450000, 1.757576, 1.263158,
1.333333, 1.666667, 2.636364, NA, NA, NA, NA,
2.363636, 1.312500, NA, 1.653846, 2.456140),
tolerance = 0.00001)
expect_equal(cur_out$p_gt, c(0.02970297, 0.19801980, 1.00000000, 0.43564356,
0.71287129, 0.98019802, 0.19801980, 0.00990099,
0.00990099, 0.00990099, 0.51485149, 1.00000000,
0.57425743, 0.00990099, 0.93069307, 0.88118812,
0.00990099, 0.00990099, NA, NA, NA, NA, 0.00990099,
1.00000000, NA, 0.83168317, 0.00990099),
tolerance = 0.00001)
expect_equal(cur_out$p_lt, c(0.98019802, 0.81188119, 0.00990099, 0.57425743, 0.94059406,
0.02970297, 0.82178218, 1.00000000, 1.00000000,
1.00000000, 0.51485149, 0.00990099, 0.43564356,
1.00000000, 0.07920792, 0.15841584, 1.00000000,
1.00000000, NA, NA, NA, NA, 1.00000000, 0.00990099,
NA, 0.18811881, 1.00000000),
tolerance = 0.00001)
# Check against countInteractions
expect_silent(cur_sn <- countInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "histocat",
colPairName = "knn_interaction_graph"))
expect_equal(cur_out$group_by, as.character(cur_sn$group_by))
expect_equal(cur_out$from_label, as.character(cur_sn$from_label))
expect_equal(cur_out$to_label, as.character(cur_sn$to_label))
expect_equal(cur_out$ct, cur_sn$ct)
cur_test <- cur_out[!is.na(cur_out$ct),]
expect_equal(rowMin(as.matrix(cur_test[,c("p_gt", "p_lt")])), cur_test$p)
expect_equal(cur_test$p_gt < cur_test$p_lt, cur_test$interaction)
expect_equal(cur_test$p < 0.01, cur_test$sig)
expect_equal(cur_test$sig * sign(cur_test$interaction - 0.5), cur_test$sigval)
expect_silent(cur_out_2 <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "histocat",
colPairName = "knn_interaction_graph",
iter = 100, p_threshold = 0.5,
BPPARAM = SerialParam(RNGseed = 123)))
expect_equal(cur_out_2$group_by, as.character(cur_sn$group_by))
expect_equal(cur_out_2$from_label, as.character(cur_sn$from_label))
expect_equal(cur_out_2$to_label, as.character(cur_sn$to_label))
expect_equal(cur_out_2$ct, cur_sn$ct)
cur_test <- cur_out_2[!is.na(cur_out_2$ct),]
expect_equal(rowMin(as.matrix(cur_test[,c("p_gt", "p_lt")])), cur_test$p)
expect_equal(cur_test$p_gt < cur_test$p_lt, cur_test$interaction)
expect_equal(cur_test$p < 0.5, cur_test$sig)
expect_equal(cur_test$sig * sign(cur_test$interaction - 0.5), cur_test$sigval)
################################ patch ###################################
expect_silent(cur_out <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "patch",
patch_size = 3,
colPairName = "knn_interaction_graph",
iter = 100,
BPPARAM = SerialParam(RNGseed = 123)))
expect_silent(cur_out_2 <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "patch",
patch_size = 3,
colPairName = "knn_interaction_graph",
iter = 100,
BPPARAM = SerialParam(RNGseed = 123)))
expect_identical(cur_out, cur_out_2)
# Check numerical values
expect_equal(cur_out$ct, c(0.23529412, 0.00000000, 0.00000000, 0.00000000,
0.00000000, 0.25000000, 0.00000000, 0.00000000,
0.81818182, 0.55555556, 0.02222222, 0.00000000,
0.02702703, 0.05405405, 0.00000000, 0.00000000,
0.12500000, 0.52500000, NA, NA, NA, NA, 0.51515152,
0.00000000, NA, 0.06557377, 0.57377049),
tolerance = 0.00001)
expect_equal(cur_out$p_gt, c(0.00990099, 1.00000000, 1.00000000, 1.00000000, 1.00000000,
0.98019802, 1.00000000, 1.00000000, 0.00990099, 0.00990099,
0.63366337, 1.00000000, 0.82178218, 0.21782178, 1.00000000,
1.00000000, 0.00990099, 0.00990099, NA, NA, NA, NA, 0.00990099,
1.00000000, NA, 0.99009901, 0.00990099),
tolerance = 0.00001)
expect_equal(cur_out$p_lt, c(1.00000000, 1.00000000, 0.00990099, 0.97029703, 1.00000000,
0.18811881, 0.80198020, 0.97029703, 1.00000000, 1.00000000,
0.64356436, 0.22772277, 0.43564356, 0.94059406, 0.28712871,
0.14851485, 1.00000000, 1.00000000, NA, NA, NA, NA,
1.00000000, 0.00990099, NA, 0.03960396, 1.00000000),
tolerance = 0.00001)
# Check against countInteractions
expect_silent(cur_sn <- countInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "patch",
patch_size = 3,
colPairName = "knn_interaction_graph"))
expect_equal(cur_out$group_by, as.character(cur_sn$group_by))
expect_equal(cur_out$from_label, as.character(cur_sn$from_label))
expect_equal(cur_out$to_label, as.character(cur_sn$to_label))
expect_equal(cur_out$ct, cur_sn$ct)
cur_test <- cur_out[!is.na(cur_out$ct),]
expect_equal(rowMin(as.matrix(cur_test[,c("p_gt", "p_lt")])), cur_test$p)
expect_equal(cur_test$p_gt < cur_test$p_lt, cur_test$interaction)
expect_equal(cur_test$p < 0.01, cur_test$sig)
expect_equal(cur_test$sig * sign(cur_test$interaction - 0.5), cur_test$sigval)
expect_silent(cur_out_2 <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "patch",
patch_size = 3,
colPairName = "knn_interaction_graph",
iter = 100, p_threshold = 0.5,
BPPARAM = SerialParam(RNGseed = 123)))
expect_equal(cur_out_2$group_by, as.character(cur_sn$group_by))
expect_equal(cur_out_2$from_label, as.character(cur_sn$from_label))
expect_equal(cur_out_2$to_label, as.character(cur_sn$to_label))
expect_equal(cur_out_2$ct, cur_sn$ct)
cur_test <- cur_out_2[!is.na(cur_out_2$ct),]
expect_equal(rowMin(as.matrix(cur_test[,c("p_gt", "p_lt")])), cur_test$p)
expect_equal(cur_test$p_gt < cur_test$p_lt, cur_test$interaction)
expect_equal(cur_test$p < 0.5, cur_test$sig)
expect_equal(cur_test$sig * sign(cur_test$interaction - 0.5), cur_test$sigval)
# Corner case settings
# one cell of a given cell-type and no neighbors
cur_sce <- pancreasSCE
cur_sce$CellType[123] <- "test"
cur_sce <- buildSpatialGraph(cur_sce, img_id = "ImageNb",
type = "expansion", threshold = 7)
plotSpatial(cur_sce, node_color_by = "CellType", img_id = "ImageNb",
draw_edges = TRUE, colPairName = "expansion_interaction_graph")
expect_silent(cur_out <- testInteractions(cur_sce,
group_by = "ImageNb",
label = "CellType",
colPairName = "expansion_interaction_graph",
iter = 100,
BPPARAM = SerialParam(RNGseed = 123)))
# Check numerical values
expect_equal(cur_out$ct, c(0.235294117647059, 0, 0, NA, 0, 0, 0, NA, 0, 0, 0.204545454545455,
NA, NA, NA, NA, NA, 0.133333333333333, 0.0666666666666667, 0,
0, 0.0810810810810811, 0.0540540540540541, 0.0810810810810811,
0, 0, 0.0769230769230769, 0.102564102564103, 0, 0, 0, 0, 0, NA,
NA, NA, NA, NA, 0.303030303030303, 0.0606060606060606, NA, NA,
0.0655737704918033, 0.360655737704918, NA, NA, NA, NA, NA),
tolerance = 0.00001)
expect_equal(cur_out$p_gt, c(0.0198019801980198, 1, 1, NA, 1, 1, 1, NA, 1, 1, 0.108910891089109,
NA, NA, NA, NA, NA, 0.227722772277228, 0.504950495049505, 1,
1, 0.504950495049505, 0.702970297029703, 0.455445544554455, 1,
1, 0.455445544554455, 0.376237623762376, 1, 1, 1, 1, 1, NA, NA,
NA, NA, NA, 0.108910891089109, 1, NA, NA, 1, 0.0198019801980198,
NA, NA, NA, NA, NA),
tolerance = 0.00001)
expect_equal(cur_out$p_lt, c(1, 0.782178217821782, 0.0297029702970297, NA, 0.782178217821782,
0.97029702970297, 0.247524752475248, NA, 0.0297029702970297,
0.247524752475248, 0.99009900990099, NA, NA, NA, NA, NA, 0.940594059405941,
0.732673267326733, 0.0594059405940594, 0.930693069306931, 0.732673267326733,
0.693069306930693, 0.762376237623762, 0.940594059405941, 0.0594059405940594,
0.762376237623762, 0.940594059405941, 0.95049504950495, 0.930693069306931,
0.940594059405941, 0.95049504950495, 1, NA, NA, NA, NA, NA, 0.96039603960396,
0.0099009900990099, NA, NA, 0.0099009900990099, 1, NA, NA, NA,
NA, NA),
tolerance = 0.00001)
# Check against countInteractions
expect_silent(cur_sn <- countInteractions(cur_sce,
group_by = "ImageNb",
label = "CellType",
colPairName = "expansion_interaction_graph"))
expect_equal(cur_out$group_by, as.character(cur_sn$group_by))
expect_equal(cur_out$from_label, as.character(cur_sn$from_label))
expect_equal(cur_out$to_label, as.character(cur_sn$to_label))
expect_equal(cur_out$ct, cur_sn$ct)
cur_test <- cur_out[!is.na(cur_out$ct),]
expect_equal(rowMin(as.matrix(cur_test[,c("p_gt", "p_lt")])), cur_test$p)
expect_equal(cur_test$p_gt < cur_test$p_lt, cur_test$interaction)
expect_equal(cur_test$p < 0.01, cur_test$sig)
expect_equal(cur_test$sig * sign(cur_test$interaction - 0.5), cur_test$sigval)
## histocat
expect_silent(cur_out <- testInteractions(cur_sce,
group_by = "ImageNb",
label = "CellType",
method = "histocat",
colPairName = "expansion_interaction_graph",
iter = 100,
BPPARAM = SerialParam(RNGseed = 123)))
expect_equal(cur_out$ct, c(1.000000, 0.000000, 0.000000, NA, 0.000000, 0.000000,
0.000000, NA, 0.000000, 0.000000, 1.058824, NA,
NA, NA, NA, NA, 1.000000, 1.000000,
0.000000, 0.000000, 1.000000, 1.000000, 1.000000, 0.000000,
0.000000, 1.000000, 1.000000, 0.000000, 0.000000, 0.000000, 0.000000,
0.000000, NA, NA, NA, NA,
NA, 1.250000, 1.000000, NA, NA, 1.000000,
1.100000, NA, NA, NA, NA, NA),
tolerance = 0.00001)
expect_equal(cur_out$p_gt, c(0.158415841584158, 1, 1, NA, 1, 1, 1, NA, 1, 1, 0.495049504950495,
NA, NA, NA, NA, NA, 0.792079207920792, 0.920792079207921, 1,
1, 0.920792079207921, 0.702970297029703, 0.910891089108911, 1,
1, 0.910891089108911, 0.742574257425743, 1, 1, 1, 1, 1, NA, NA,
NA, NA, NA, 0.099009900990099, 1, NA, NA, 1, 0.465346534653465,
NA, NA, NA, NA, NA),
tolerance = 0.00001)
expect_equal(cur_out$p_lt, c(0.99009900990099, 0.782178217821782, 0.0297029702970297, NA,
0.782178217821782, 0.97029702970297, 0.247524752475248, NA, 0.0297029702970297,
0.247524752475248, 0.574257425742574, NA, NA, NA, NA, NA, 0.900990099009901,
0.930693069306931, 0.0594059405940594, 0.930693069306931, 0.900990099009901,
0.99009900990099, 0.96039603960396, 0.940594059405941, 0.0594059405940594,
0.95049504950495, 0.910891089108911, 0.95049504950495, 0.930693069306931,
0.940594059405941, 0.95049504950495, 1, NA, NA, NA, NA, NA, 0.940594059405941,
0.297029702970297, NA, NA, 0.297029702970297, 0.544554455445545,
NA, NA, NA, NA, NA),
tolerance = 0.00001)
# Check against countInteractions
expect_silent(cur_sn <- countInteractions(cur_sce,
group_by = "ImageNb",
label = "CellType",
method = "histocat",
colPairName = "expansion_interaction_graph"))
expect_equal(cur_out$group_by, as.character(cur_sn$group_by))
expect_equal(cur_out$from_label, as.character(cur_sn$from_label))
expect_equal(cur_out$to_label, as.character(cur_sn$to_label))
expect_equal(cur_out$ct, cur_sn$ct)
cur_test <- cur_out[!is.na(cur_out$ct),]
expect_equal(rowMin(as.matrix(cur_test[,c("p_gt", "p_lt")])), cur_test$p)
expect_equal(cur_test$p_gt < cur_test$p_lt, cur_test$interaction)
expect_equal(cur_test$p < 0.01, cur_test$sig)
expect_equal(cur_test$sig * sign(cur_test$interaction - 0.5), cur_test$sigval)
## patch
expect_silent(cur_out <- testInteractions(cur_sce,
group_by = "ImageNb",
label = "CellType",
method = "patch",
patch_size = 1,
colPairName = "expansion_interaction_graph",
iter = 100,
BPPARAM = SerialParam(RNGseed = 123)))
expect_equal(cur_out$ct, c(0.235294117647059, 0, 0, NA, 0, 0, 0, NA, 0, 0, 0.193181818181818,
NA, NA, NA, NA, NA, 0.133333333333333, 0.0666666666666667, 0,
0, 0.0810810810810811, 0.0540540540540541, 0.0810810810810811,
0, 0, 0.0769230769230769, 0.102564102564103, 0, 0, 0, 0, 0, NA,
NA, NA, NA, NA, 0.242424242424242, 0.0606060606060606, NA, NA,
0.0655737704918033, 0.327868852459016, NA, NA, NA, NA, NA),
tolerance = 0.00001)
expect_equal(cur_out$p_gt, c(0.0099009900990099, 1, 1, NA, 1, 1, 1, NA, 1, 1, 0.108910891089109,
NA, NA, NA, NA, NA, 0.198019801980198, 0.495049504950495, 1,
1, 0.495049504950495, 0.702970297029703, 0.455445544554455, 1,
1, 0.445544554455446, 0.326732673267327, 1, 1, 1, 1, 1, NA, NA,
NA, NA, NA, 0.168316831683168, 1, NA, NA, 1, 0.0099009900990099,
NA, NA, NA, NA, NA),
tolerance = 0.00001)
expect_equal(cur_out$p_lt, c(1, 0.782178217821782, 0.0297029702970297, NA, 0.782178217821782,
0.97029702970297, 0.247524752475248, NA, 0.0297029702970297,
0.247524752475248, 0.96039603960396, NA, NA, NA, NA, NA, 0.940594059405941,
0.752475247524752, 0.0594059405940594, 0.930693069306931, 0.792079207920792,
0.693069306930693, 0.762376237623762, 0.940594059405941, 0.0594059405940594,
0.772277227722772, 0.940594059405941, 0.95049504950495, 0.930693069306931,
0.940594059405941, 0.95049504950495, 1, NA, NA, NA, NA, NA, 0.900990099009901,
0.0099009900990099, NA, NA, 0.0099009900990099, 1, NA, NA, NA,
NA, NA),
tolerance = 0.00001)
# Check against countInteractions
expect_silent(cur_sn <- countInteractions(cur_sce,
group_by = "ImageNb",
label = "CellType",
method = "patch",
patch_size = 1,
colPairName = "expansion_interaction_graph"))
expect_equal(cur_out$group_by, as.character(cur_sn$group_by))
expect_equal(cur_out$from_label, as.character(cur_sn$from_label))
expect_equal(cur_out$to_label, as.character(cur_sn$to_label))
expect_equal(cur_out$ct, cur_sn$ct)
cur_test <- cur_out[!is.na(cur_out$ct),]
expect_equal(rowMin(as.matrix(cur_test[,c("p_gt", "p_lt")])), cur_test$p)
expect_equal(cur_test$p_gt < cur_test$p_lt, cur_test$interaction)
expect_equal(cur_test$p < 0.01, cur_test$sig)
expect_equal(cur_test$sig * sign(cur_test$interaction - 0.5), cur_test$sigval)
# Return samples
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "expansion",
threshold = 20)
expect_silent(cur_out <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "classic",
iter = 100,
colPairName = "expansion_interaction_graph",
return_samples = TRUE,
BPPARAM = SerialParam(RNGseed = 123)))
expect_silent(cur_out_2 <- testInteractions(pancreasSCE,
group_by = "ImageNb",
label = "CellType",
method = "classic",
iter = 100,
colPairName = "expansion_interaction_graph",
BPPARAM = SerialParam(RNGseed = 123)))
expect_equal(cur_out$group_by, as.character(cur_out_2$group_by))
expect_equal(cur_out$from_label, as.character(cur_out_2$from_label))
expect_equal(cur_out$to_label, as.character(cur_out_2$to_label))
expect_equal(cur_out$ct, cur_out_2$ct)
expect_equal(cur_out$p_lt, cur_out_2$p_lt)
expect_equal(cur_out$p_gt, cur_out_2$p_gt)
expect_equal(cur_out$interaction, cur_out_2$interaction)
expect_equal(cur_out$p, cur_out_2$p)
expect_equal(cur_out$sig, cur_out_2$sig)
expect_equal(cur_out$sigval, cur_out_2$sigval)
expect_equal(dim(cur_out), c(27, 110))
expect_equal(cur_out$iter_1, c(1.29411764705882, 0.352941176470588, 7.29411764705882, 0.75,
0.25, 7.125, 1.40909090909091, 0.647727272727273, 7.34090909090909,
3.64444444444444, 3.22222222222222, 2.95555555555556, 3.91891891891892,
3.08108108108108, 3.37837837837838, 3.325, 3.125, 3.3, 0, 0,
0, 0, 5.6969696969697, 5.51515151515152, 0, 5.9672131147541,
4.81967213114754))
expect_equal(cur_out$iter_13, c(1.05882352941176, 0.470588235294118, 7.64705882352941, 1, 0.5,
6.5, 1.47727272727273, 0.590909090909091, 7.29545454545454, 4.31111111111111,
2.88888888888889, 2.75555555555556, 3.51351351351351, 3.67567567567568,
3.16216216216216, 3.1, 2.925, 3.6, 0, 0, 0, 0, 6.36363636363636,
5.03030303030303, 0, 5.44262295081967, 5.14754098360656))
expect_equal(cur_out$iter_26, c(1.29411764705882, 0.882352941176471, 7.58823529411765, 1.875,
0.25, 7.125, 1.46590909090909, 0.647727272727273, 7.02272727272727,
3.91111111111111, 3.42222222222222, 3.11111111111111, 4.16216216216216,
2.54054054054054, 3.13513513513514, 3.5, 2.9, 3.15, 0, 0, 0,
0, 6.06060606060606, 5.09090909090909, 0, 5.50819672131148, 5.34426229508197
))
expect_equal(cur_out$iter_67, c(1.64705882352941, 0.529411764705882, 6.29411764705882, 1.125,
0.25, 6.75, 1.21590909090909, 0.613636363636364, 7.65909090909091,
4.53333333333333, 2.86666666666667, 3.44444444444444, 3.48648648648649,
2.32432432432432, 3.13513513513514, 3.875, 2.9, 3.15, 0, 0, 0,
0, 5.96969696969697, 5.33333333333333, 0, 5.77049180327869, 4.91803278688525
))
expect_equal(cur_out$iter_99, c(1.41176470588235, 0, 7.35294117647059, 0, 1.75, 8, 1.42045454545455,
0.727272727272727, 7.13636363636364, 3.91111111111111, 3.13333333333333,
3.53333333333333, 3.81081081081081, 2.86486486486486, 3.08108108108108,
3.975, 2.85, 2.65, 0, 0, 0, 0, 6.15151515151515, 5.31818181818182,
0, 5.75409836065574, 4.75409836065574))
# Fail
expect_error(testInteractions("test"),
regexp = "'object' not of type 'SingleCellExperiment'.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "test", label = "CellType",
colPairName = "knn_interaction_graph"),
regexp = "'group_by' not in colData(object).",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = 1, label = "CellType",
colPairName = "knn_interaction_graph"),
regexp = "'group_by' must be a single string.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "test",
colPairName = "knn_interaction_graph"),
regexp = "'label' not in colData(object).",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = 1,
colPairName = "knn_interaction_graph"),
regexp = "'label' must be a single string.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType",
colPairName = "test"),
regexp = "'colPairName' not in colPairNames(object).",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType", colPairName = 1),
regexp = "'colPairName' must be a single string.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType",
colPairName = "knn_interaction_graph",
method = "patch"),
regexp = "When method = 'patch', please specify 'patch_size'.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType",
colPairName = "knn_interaction_graph",
method = "patch", patch_size = "test"),
regexp = "'patch_size' must be a single numeric.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType",
colPairName = "knn_interaction_graph",
iter = "test"),
regexp = "'iter' must be a single positive numeric.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType",
colPairName = "knn_interaction_graph",
iter = c(1,2)),
regexp = "'iter' must be a single positive numeric.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType",
colPairName = "knn_interaction_graph",
iter = -20),
regexp = "'iter' must be a single positive numeric.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType",
colPairName = "knn_interaction_graph",
p_threshold = "test"),
regexp = "'p_threshold' must be a single numeric between 0 and 1.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType",
colPairName = "knn_interaction_graph",
p_threshold = c(1,2)),
regexp = "'p_threshold' must be a single numeric between 0 and 1.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType",
colPairName = "knn_interaction_graph",
p_threshold = 3),
regexp = "'p_threshold' must be a single numeric between 0 and 1.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType",
colPairName = "knn_interaction_graph",
return_samples = 1),
regexp = "'return_samples' must be a single logical.",
fixed = TRUE)
expect_error(testInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType",
colPairName = "knn_interaction_graph",
return_samples = c("test", "test2")),
regexp = "'return_samples' must be a single logical.",
fixed = TRUE)
})
test_that("testInteractions function works if cells are not grouped by image", {
library(cytomapper)
library(BiocParallel)
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "expansion",
threshold = 10)
plotSpatial(pancreasSCE, img_id = "ImageNb", draw_edges = TRUE,
colPairName = "expansion_interaction_graph",
node_color_by = "CellType", scales = "free")
out <- testInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "classic",
iter = 200, colPairName = "expansion_interaction_graph",
BPPARAM = SerialParam(RNGseed = 111))
set.seed(123)
cur_sce <- pancreasSCE[,sample(ncol(pancreasSCE))]
plotSpatial(cur_sce, img_id = "ImageNb", draw_edges = TRUE,
colPairName = "expansion_interaction_graph",
node_color_by = "CellType", scales = "free")
out2 <- testInteractions(cur_sce, group_by = "ImageNb",
label = "CellType", method = "classic",
iter = 200,
colPairName = "expansion_interaction_graph",
BPPARAM = SerialParam(RNGseed = 111))
## Sampling is different between grouped and non-grouped cells
## Therefore the p values are close but not identical
expect_equal(out$group_by, out2$group_by)
expect_equal(out$from_label, out2$from_label)
expect_equal(out$to_label, out2$to_label)
expect_equal(out$ct, out2$ct)
expect_equal(out$p_gt, out2$p_gt, tolerance = 0.1)
expect_equal(out$p_lt, out2$p_lt, tolerance = 0.1)
expect_equal(out$interaction, out2$interaction)
expect_equal(out$p, out2$p, tolerance = 0.1)
expect_equal(out$sig, out2$sig)
expect_equal(out$sigval, out2$sigval)
out <- testInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "histocat",
iter = 400, colPairName = "expansion_interaction_graph",
BPPARAM = SerialParam(RNGseed = 111))
out2 <- testInteractions(cur_sce, group_by = "ImageNb",
label = "CellType", method = "histocat",
iter = 400,
colPairName = "expansion_interaction_graph",
BPPARAM = SerialParam(RNGseed = 111))
expect_equal(out$group_by, out2$group_by)
expect_equal(out$from_label, out2$from_label)
expect_equal(out$to_label, out2$to_label)
expect_equal(out$ct, out2$ct)
expect_equal(out$p_gt, out2$p_gt, tolerance = 0.1)
expect_equal(out$p_lt, out2$p_lt, tolerance = 0.1)
expect_equal(out$interaction, out2$interaction)
expect_equal(out$p, out2$p, tolerance = 0.1)
#expect_equal(out$sig, out2$sig)
#expect_equal(out$sigval, out2$sigval)
out <- testInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "patch", patch_size = 2,
iter = 300, colPairName = "expansion_interaction_graph",
BPPARAM = SerialParam(RNGseed = 111))
out2 <- testInteractions(cur_sce, group_by = "ImageNb",
label = "CellType", method = "patch", patch_size = 2,
iter = 300,
colPairName = "expansion_interaction_graph",
BPPARAM = SerialParam(RNGseed = 111))
expect_equal(out$group_by, out2$group_by)
expect_equal(out$from_label, out2$from_label)
expect_equal(out$to_label, out2$to_label)
expect_equal(out$ct, out2$ct)
expect_equal(out$p_gt, out2$p_gt, tolerance = 0.1)
expect_equal(out$p_lt, out2$p_lt, tolerance = 0.1)
expect_equal(out$interaction, out2$interaction)
expect_equal(out$p, out2$p, tolerance = 0.1)
#expect_equal(out$sig, out2$sig)
#expect_equal(out$sigval, out2$sigval)
})
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