tests/testthat/test_countInteractions.R
In BodenmillerGroup/imcRtools: Methods for imaging mass cytometry data analysis
test_that("countInteractions function works", {
library(cytomapper)
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
########################### classic ############################
expect_silent(cur_out <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "classic",
colPairName = "knn_interaction_graph"))
cur_out <- as.data.frame(cur_out)
cur_out <- cur_out[order(cur_out$group_by, cur_out$from_label, cur_out$to_label),]
# Check against manual calculations
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["CellType"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["CellType"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageNb"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label), .drop = FALSE) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(n))
test <- as.data.frame(test)
test <- test[order(test$image, test$from_label, test$`as.factor(to_label)`),]
cur_out_2 <- cur_out
cur_out_2 <- cur_out_2[match(paste(test$image, test$from_label, test$`as.factor(to_label)`),
paste(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label)),]
expect_equal(cur_out_2$ct[!is.na(cur_out_2$ct)], test$ct[!is.na(cur_out_2$ct)])
# As factor
pancreasSCE$CellType <- as.factor(pancreasSCE$CellType)
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "classic",
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
expect_equal(cur_out_2$ct, cur_out$ct)
# As character
pancreasSCE$CellType <- as.character(pancreasSCE$CellType)
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "classic",
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
expect_equal(cur_out_2, cur_out)
# As numeric
pancreasSCE$CellType <- as.numeric(as.factor(pancreasSCE$CellType))
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "classic",
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
expect_equal(cur_out_2$ct, cur_out$ct)
# Logical
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "Pattern", method = "classic",
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["Pattern"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["Pattern"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageNb"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label), .drop = FALSE) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(n))
expect_equal(cur_out_2$ct[!is.na(cur_out_2$ct)], test$ct[!is.na(cur_out_2$ct)])
# One image only contains one cell type
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
pancreasSCE$test <- pancreasSCE$CellType
pancreasSCE$test[pancreasSCE$ImageNb == 3] <- "test"
expect_silent(cur_out_3 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "test", method = "classic",
colPairName = "knn_interaction_graph"))
cur_out_3 <- as.data.frame(cur_out_3)
cur_out_3 <- cur_out_3[order(cur_out_3$group_by, cur_out_3$from_label, cur_out_3$to_label),]
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["test"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["test"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageNb"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label), .drop = FALSE) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(n))
cur_out_4 <- cur_out_3
cur_out_4 <- cur_out_4[match(paste(test$image, test$from_label, test$`as.factor(to_label)`),
paste(cur_out_4$group_by, cur_out_4$from_label, cur_out_4$to_label)),]
expect_equal(cur_out_4$ct[!is.na(cur_out_4$ct)], test$ct[!is.na(cur_out_4$ct)])
expect_equal(cur_out_3$ct[!is.na(cur_out_3$ct) & cur_out_3$group_by != 3], cur_out$ct[!is.na(cur_out$ct) & cur_out$group_by != 3])
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
pancreasSCE$ImageName <- "test"
expect_silent(cur_out <- countInteractions(pancreasSCE, group_by = "ImageName",
label = "CellType", method = "classic",
colPairName = "knn_interaction_graph"))
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["CellType"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["CellType"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageName"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label), .drop = FALSE) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(n))
expect_equal(cur_out$ct, test$ct)
########################### histocat ############################
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
expect_silent(cur_out <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "histocat",
colPairName = "knn_interaction_graph"))
cur_out <- as.data.frame(cur_out)
cur_out <- cur_out[order(cur_out$group_by, cur_out$from_label, cur_out$to_label),]
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["CellType"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["CellType"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageNb"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label)) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(n))
test <- as.data.frame(test)
test <- test[order(test$image, test$from_label, test$`as.factor(to_label)`),]
expect_equal(cur_out$ct[!is.na(cur_out$ct)], test$ct)
# As factor
pancreasSCE$CellType <- as.factor(pancreasSCE$CellType)
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "histocat",
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
expect_equal(cur_out_2$ct, cur_out$ct)
# As character
pancreasSCE$CellType <- as.character(pancreasSCE$CellType)
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "histocat",
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
expect_equal(cur_out_2$ct, cur_out$ct)
# As numeric
pancreasSCE$CellType <- as.numeric(as.factor(pancreasSCE$CellType))
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "histocat",
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
expect_equal(cur_out_2$ct, cur_out$ct)
# Logical
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "Pattern", method = "histocat",
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["Pattern"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["Pattern"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageNb"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label)) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(n))
expect_equal(cur_out_2$ct, test$ct)
# One image only contains one cell type
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
pancreasSCE$test <- pancreasSCE$CellType
pancreasSCE$test[pancreasSCE$ImageNb == 3] <- "test"
expect_silent(cur_out_3 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "test", method = "histocat",
colPairName = "knn_interaction_graph"))
cur_out_3 <- as.data.frame(cur_out_3)
cur_out_3 <- cur_out_3[order(cur_out_3$group_by, cur_out_3$from_label, cur_out_3$to_label),]
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["test"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["test"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageNb"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label)) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(n))
expect_equal(cur_out_3$ct[!is.na(cur_out_3$ct)], test$ct)
expect_equal(cur_out_3$ct[cur_out_3$group_by != 3 & !is.na(cur_out_3$ct)],
cur_out$ct[cur_out$group_by != 3])
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
pancreasSCE$ImageName <- "test"
expect_silent(cur_out <- countInteractions(pancreasSCE, group_by = "ImageName",
label = "CellType", method = "histocat",
colPairName = "knn_interaction_graph"))
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["CellType"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["CellType"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageName"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label)) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(n))
expect_equal(cur_out$ct, test$ct)
########################### patch ############################
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
expect_silent(cur_out <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "patch",
patch_size = 3,
colPairName = "knn_interaction_graph"))
cur_out <- as.data.frame(cur_out)
cur_out <- cur_out[order(cur_out$group_by, cur_out$from_label, cur_out$to_label),]
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["CellType"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["CellType"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageNb"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label), .drop = FALSE) %>% ungroup() %>%
mutate(ct = n >= 3) %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(ct))
test <- as.data.frame(test)
test <- test[order(test$image, test$from_label, test$`as.factor(to_label)`),]
cur_out_2 <- cur_out
cur_out_2 <- cur_out_2[match(paste(test$image, test$from_label, test$`as.factor(to_label)`),
paste(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label)),]
expect_equal(cur_out_2$ct[!is.na(cur_out_2$ct)], test$ct[!is.na(cur_out_2$ct)])
# As factor
pancreasSCE$CellType <- as.factor(pancreasSCE$CellType)
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "patch",
patch_size = 3,
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
expect_equal(cur_out_2$ct, cur_out$ct)
# As character
pancreasSCE$CellType <- as.character(pancreasSCE$CellType)
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "patch",
patch_size = 3,
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
expect_equal(cur_out_2$ct, cur_out$ct)
# As numeric
pancreasSCE$CellType <- as.numeric(as.factor(pancreasSCE$CellType))
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "patch",
patch_size = 3,
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
expect_equal(cur_out_2$ct, cur_out$ct)
# Logical
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "Pattern", method = "patch",
patch_size = 3,
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["Pattern"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["Pattern"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageNb"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label), .drop = FALSE) %>%
mutate(ct = n >= 3) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(ct))
expect_equal(cur_out_2$ct[!is.na(cur_out_2$ct)], test$ct[!is.na(cur_out_2$ct)])
# One image only contains one cell type
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
pancreasSCE$test <- pancreasSCE$CellType
pancreasSCE$test[pancreasSCE$ImageNb == 3] <- "test"
expect_silent(cur_out_3 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "test", method = "patch",
patch_size = 3,
colPairName = "knn_interaction_graph"))
cur_out_3 <- as.data.frame(cur_out_3)
cur_out_3 <- cur_out_3[order(cur_out_3$group_by, cur_out_3$from_label, cur_out_3$to_label),]
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["test"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["test"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageNb"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label), .drop = FALSE) %>%
mutate(ct = n >= 3) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(ct))
cur_out_4 <- cur_out_3
cur_out_4 <- cur_out_4[match(paste(test$image, test$from_label, test$`as.factor(to_label)`),
paste(cur_out_4$group_by, cur_out_4$from_label, cur_out_4$to_label)),]
expect_equal(cur_out_4$ct[!is.na(cur_out_4$ct)], test$ct[!is.na(cur_out_4$ct)])
expect_equal(cur_out_3$ct[!is.na(cur_out_3$ct) & cur_out_3$group_by != 3], cur_out$ct[!is.na(cur_out$ct) & cur_out$group_by != 3])
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
expect_silent(cur_out <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "patch",
patch_size = 4,
colPairName = "knn_interaction_graph"))
expect_true(all(cur_out$ct[!is.na(cur_out$ct)] == 0))
expect_silent(cur_out <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "patch",
patch_size = 0,
colPairName = "knn_interaction_graph"))
expect_true(all(cur_out$ct[!is.na(cur_out$ct)] == 1))
expect_silent(cur_out <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "patch",
patch_size = 1,
colPairName = "knn_interaction_graph"))
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["CellType"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["CellType"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageNb"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label), .drop = FALSE) %>%
mutate(ct = n >= 1) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(ct))
cur_out_2 <- cur_out
cur_out_2 <- cur_out_2[match(paste(test$image, test$from_label, test$`as.factor(to_label)`),
paste(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label)),]
expect_equal(cur_out_2$ct[!is.na(cur_out_2$ct)], test$ct[!is.na(cur_out_2$ct)])
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
pancreasSCE$ImageName <- "test"
expect_silent(cur_out <- countInteractions(pancreasSCE, group_by = "ImageName",
label = "CellType", method = "patch",
patch_size = 3,
colPairName = "knn_interaction_graph"))
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["CellType"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["CellType"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageName"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label), .drop = FALSE) %>%
mutate(ct = n >= 3) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(ct))
expect_equal(cur_out$ct, test$ct)
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
# Fail
expect_error(countInteractions("test"),
regexp = "'object' not of type 'SingleCellExperiment'.",
fixed = TRUE)
expect_error(countInteractions(pancreasSCE, group_by = "test_test", label = "CellType", colPairName = "knn_interaction_graph"),
regexp = "'group_by' not in colData(object).",
fixed = TRUE)
expect_error(countInteractions(pancreasSCE, group_by = 1, label = "CellType", colPairName = "knn_interaction_graph"),
regexp = "'group_by' must be a single string.",
fixed = TRUE)
expect_error(countInteractions(pancreasSCE, group_by = "ImageNb", label = "test_test", colPairName = "knn_interaction_graph"),
regexp = "'label' not in colData(object).",
fixed = TRUE)
expect_error(countInteractions(pancreasSCE, group_by = "ImageNb", label = 1, colPairName = "knn_interaction_graph"),
regexp = "'label' must be a single string.",
fixed = TRUE)
expect_error(countInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType", colPairName = "test"),
regexp = "'colPairName' not in colPairNames(object).",
fixed = TRUE)
expect_error(countInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType", colPairName = 1),
regexp = "'colPairName' must be a single string.",
fixed = TRUE)
expect_error(countInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType", colPairName = "knn_interaction_graph",
method = "patch"),
regexp = "When method = 'patch', please specify 'patch_size'.",
fixed = TRUE)
expect_error(countInteractions(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)
})
BodenmillerGroup/imcRtools documentation built on July 1, 2024, 5:15 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
test_that("countInteractions function works", {
library(cytomapper)
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
########################### classic ############################
expect_silent(cur_out <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "classic",
colPairName = "knn_interaction_graph"))
cur_out <- as.data.frame(cur_out)
cur_out <- cur_out[order(cur_out$group_by, cur_out$from_label, cur_out$to_label),]
# Check against manual calculations
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["CellType"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["CellType"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageNb"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label), .drop = FALSE) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(n))
test <- as.data.frame(test)
test <- test[order(test$image, test$from_label, test$`as.factor(to_label)`),]
cur_out_2 <- cur_out
cur_out_2 <- cur_out_2[match(paste(test$image, test$from_label, test$`as.factor(to_label)`),
paste(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label)),]
expect_equal(cur_out_2$ct[!is.na(cur_out_2$ct)], test$ct[!is.na(cur_out_2$ct)])
# As factor
pancreasSCE$CellType <- as.factor(pancreasSCE$CellType)
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "classic",
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
expect_equal(cur_out_2$ct, cur_out$ct)
# As character
pancreasSCE$CellType <- as.character(pancreasSCE$CellType)
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "classic",
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
expect_equal(cur_out_2, cur_out)
# As numeric
pancreasSCE$CellType <- as.numeric(as.factor(pancreasSCE$CellType))
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "classic",
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
expect_equal(cur_out_2$ct, cur_out$ct)
# Logical
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "Pattern", method = "classic",
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["Pattern"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["Pattern"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageNb"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label), .drop = FALSE) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(n))
expect_equal(cur_out_2$ct[!is.na(cur_out_2$ct)], test$ct[!is.na(cur_out_2$ct)])
# One image only contains one cell type
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
pancreasSCE$test <- pancreasSCE$CellType
pancreasSCE$test[pancreasSCE$ImageNb == 3] <- "test"
expect_silent(cur_out_3 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "test", method = "classic",
colPairName = "knn_interaction_graph"))
cur_out_3 <- as.data.frame(cur_out_3)
cur_out_3 <- cur_out_3[order(cur_out_3$group_by, cur_out_3$from_label, cur_out_3$to_label),]
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["test"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["test"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageNb"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label), .drop = FALSE) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(n))
cur_out_4 <- cur_out_3
cur_out_4 <- cur_out_4[match(paste(test$image, test$from_label, test$`as.factor(to_label)`),
paste(cur_out_4$group_by, cur_out_4$from_label, cur_out_4$to_label)),]
expect_equal(cur_out_4$ct[!is.na(cur_out_4$ct)], test$ct[!is.na(cur_out_4$ct)])
expect_equal(cur_out_3$ct[!is.na(cur_out_3$ct) & cur_out_3$group_by != 3], cur_out$ct[!is.na(cur_out$ct) & cur_out$group_by != 3])
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
pancreasSCE$ImageName <- "test"
expect_silent(cur_out <- countInteractions(pancreasSCE, group_by = "ImageName",
label = "CellType", method = "classic",
colPairName = "knn_interaction_graph"))
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["CellType"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["CellType"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageName"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label), .drop = FALSE) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(n))
expect_equal(cur_out$ct, test$ct)
########################### histocat ############################
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
expect_silent(cur_out <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "histocat",
colPairName = "knn_interaction_graph"))
cur_out <- as.data.frame(cur_out)
cur_out <- cur_out[order(cur_out$group_by, cur_out$from_label, cur_out$to_label),]
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["CellType"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["CellType"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageNb"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label)) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(n))
test <- as.data.frame(test)
test <- test[order(test$image, test$from_label, test$`as.factor(to_label)`),]
expect_equal(cur_out$ct[!is.na(cur_out$ct)], test$ct)
# As factor
pancreasSCE$CellType <- as.factor(pancreasSCE$CellType)
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "histocat",
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
expect_equal(cur_out_2$ct, cur_out$ct)
# As character
pancreasSCE$CellType <- as.character(pancreasSCE$CellType)
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "histocat",
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
expect_equal(cur_out_2$ct, cur_out$ct)
# As numeric
pancreasSCE$CellType <- as.numeric(as.factor(pancreasSCE$CellType))
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "histocat",
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
expect_equal(cur_out_2$ct, cur_out$ct)
# Logical
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "Pattern", method = "histocat",
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["Pattern"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["Pattern"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageNb"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label)) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(n))
expect_equal(cur_out_2$ct, test$ct)
# One image only contains one cell type
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
pancreasSCE$test <- pancreasSCE$CellType
pancreasSCE$test[pancreasSCE$ImageNb == 3] <- "test"
expect_silent(cur_out_3 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "test", method = "histocat",
colPairName = "knn_interaction_graph"))
cur_out_3 <- as.data.frame(cur_out_3)
cur_out_3 <- cur_out_3[order(cur_out_3$group_by, cur_out_3$from_label, cur_out_3$to_label),]
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["test"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["test"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageNb"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label)) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(n))
expect_equal(cur_out_3$ct[!is.na(cur_out_3$ct)], test$ct)
expect_equal(cur_out_3$ct[cur_out_3$group_by != 3 & !is.na(cur_out_3$ct)],
cur_out$ct[cur_out$group_by != 3])
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
pancreasSCE$ImageName <- "test"
expect_silent(cur_out <- countInteractions(pancreasSCE, group_by = "ImageName",
label = "CellType", method = "histocat",
colPairName = "knn_interaction_graph"))
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["CellType"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["CellType"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageName"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label)) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(n))
expect_equal(cur_out$ct, test$ct)
########################### patch ############################
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
expect_silent(cur_out <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "patch",
patch_size = 3,
colPairName = "knn_interaction_graph"))
cur_out <- as.data.frame(cur_out)
cur_out <- cur_out[order(cur_out$group_by, cur_out$from_label, cur_out$to_label),]
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["CellType"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["CellType"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageNb"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label), .drop = FALSE) %>% ungroup() %>%
mutate(ct = n >= 3) %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(ct))
test <- as.data.frame(test)
test <- test[order(test$image, test$from_label, test$`as.factor(to_label)`),]
cur_out_2 <- cur_out
cur_out_2 <- cur_out_2[match(paste(test$image, test$from_label, test$`as.factor(to_label)`),
paste(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label)),]
expect_equal(cur_out_2$ct[!is.na(cur_out_2$ct)], test$ct[!is.na(cur_out_2$ct)])
# As factor
pancreasSCE$CellType <- as.factor(pancreasSCE$CellType)
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "patch",
patch_size = 3,
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
expect_equal(cur_out_2$ct, cur_out$ct)
# As character
pancreasSCE$CellType <- as.character(pancreasSCE$CellType)
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "patch",
patch_size = 3,
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
expect_equal(cur_out_2$ct, cur_out$ct)
# As numeric
pancreasSCE$CellType <- as.numeric(as.factor(pancreasSCE$CellType))
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "patch",
patch_size = 3,
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
expect_equal(cur_out_2$ct, cur_out$ct)
# Logical
expect_silent(cur_out_2 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "Pattern", method = "patch",
patch_size = 3,
colPairName = "knn_interaction_graph"))
cur_out_2 <- as.data.frame(cur_out_2)
cur_out_2 <- cur_out_2[order(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label),]
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["Pattern"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["Pattern"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageNb"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label), .drop = FALSE) %>%
mutate(ct = n >= 3) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(ct))
expect_equal(cur_out_2$ct[!is.na(cur_out_2$ct)], test$ct[!is.na(cur_out_2$ct)])
# One image only contains one cell type
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
pancreasSCE$test <- pancreasSCE$CellType
pancreasSCE$test[pancreasSCE$ImageNb == 3] <- "test"
expect_silent(cur_out_3 <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "test", method = "patch",
patch_size = 3,
colPairName = "knn_interaction_graph"))
cur_out_3 <- as.data.frame(cur_out_3)
cur_out_3 <- cur_out_3[order(cur_out_3$group_by, cur_out_3$from_label, cur_out_3$to_label),]
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["test"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["test"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageNb"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label), .drop = FALSE) %>%
mutate(ct = n >= 3) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(ct))
cur_out_4 <- cur_out_3
cur_out_4 <- cur_out_4[match(paste(test$image, test$from_label, test$`as.factor(to_label)`),
paste(cur_out_4$group_by, cur_out_4$from_label, cur_out_4$to_label)),]
expect_equal(cur_out_4$ct[!is.na(cur_out_4$ct)], test$ct[!is.na(cur_out_4$ct)])
expect_equal(cur_out_3$ct[!is.na(cur_out_3$ct) & cur_out_3$group_by != 3], cur_out$ct[!is.na(cur_out$ct) & cur_out$group_by != 3])
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
expect_silent(cur_out <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "patch",
patch_size = 4,
colPairName = "knn_interaction_graph"))
expect_true(all(cur_out$ct[!is.na(cur_out$ct)] == 0))
expect_silent(cur_out <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "patch",
patch_size = 0,
colPairName = "knn_interaction_graph"))
expect_true(all(cur_out$ct[!is.na(cur_out$ct)] == 1))
expect_silent(cur_out <- countInteractions(pancreasSCE, group_by = "ImageNb",
label = "CellType", method = "patch",
patch_size = 1,
colPairName = "knn_interaction_graph"))
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["CellType"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["CellType"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageNb"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label), .drop = FALSE) %>%
mutate(ct = n >= 1) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(ct))
cur_out_2 <- cur_out
cur_out_2 <- cur_out_2[match(paste(test$image, test$from_label, test$`as.factor(to_label)`),
paste(cur_out_2$group_by, cur_out_2$from_label, cur_out_2$to_label)),]
expect_equal(cur_out_2$ct[!is.na(cur_out_2$ct)], test$ct[!is.na(cur_out_2$ct)])
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
pancreasSCE$ImageName <- "test"
expect_silent(cur_out <- countInteractions(pancreasSCE, group_by = "ImageName",
label = "CellType", method = "patch",
patch_size = 3,
colPairName = "knn_interaction_graph"))
cur_table <- as.data.frame(colPair(pancreasSCE, "knn_interaction_graph"))
cur_table$from_label <- colData(pancreasSCE)[["CellType"]][cur_table$from]
cur_table$to_label <- colData(pancreasSCE)[["CellType"]][cur_table$to]
cur_table$image <- colData(pancreasSCE)[["ImageName"]][cur_table$from]
test <- cur_table %>% group_by(from, image, from_label) %>%
count(as.factor(to_label), .drop = FALSE) %>%
mutate(ct = n >= 3) %>% ungroup() %>%
group_by(image, from_label, `as.factor(to_label)`) %>% summarize(ct = mean(ct))
expect_equal(cur_out$ct, test$ct)
data(pancreasSCE)
pancreasSCE <- buildSpatialGraph(pancreasSCE, img_id = "ImageNb", type = "knn",
k = 3)
# Fail
expect_error(countInteractions("test"),
regexp = "'object' not of type 'SingleCellExperiment'.",
fixed = TRUE)
expect_error(countInteractions(pancreasSCE, group_by = "test_test", label = "CellType", colPairName = "knn_interaction_graph"),
regexp = "'group_by' not in colData(object).",
fixed = TRUE)
expect_error(countInteractions(pancreasSCE, group_by = 1, label = "CellType", colPairName = "knn_interaction_graph"),
regexp = "'group_by' must be a single string.",
fixed = TRUE)
expect_error(countInteractions(pancreasSCE, group_by = "ImageNb", label = "test_test", colPairName = "knn_interaction_graph"),
regexp = "'label' not in colData(object).",
fixed = TRUE)
expect_error(countInteractions(pancreasSCE, group_by = "ImageNb", label = 1, colPairName = "knn_interaction_graph"),
regexp = "'label' must be a single string.",
fixed = TRUE)
expect_error(countInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType", colPairName = "test"),
regexp = "'colPairName' not in colPairNames(object).",
fixed = TRUE)
expect_error(countInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType", colPairName = 1),
regexp = "'colPairName' must be a single string.",
fixed = TRUE)
expect_error(countInteractions(pancreasSCE, group_by = "ImageNb", label = "CellType", colPairName = "knn_interaction_graph",
method = "patch"),
regexp = "When method = 'patch', please specify 'patch_size'.",
fixed = TRUE)
expect_error(countInteractions(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)
})
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.