tests/testthat/test-analysis-functions.R
In calabrialab/ISAnalytics: Analyze gene therapy vector insertion sites data identified from genomics next generation sequencing reads for clonal tracking studies
#------------------------------------------------------------------------------#
# Global vars
#------------------------------------------------------------------------------#
withr::local_options(
ISAnalytics.verbose = FALSE,
ISAnalytics.reports = FALSE
)
minimal_agg_example <- tibble::tibble(
chr = c("1", "2", "2", "5", "5", "3", "3", "10", "11"),
integration_locus = c(
14505,
1005,
15513,
4561,
10167,
5247,
10951,
23403,
25611
),
strand = c(
"+", "-", "+", "+", "-", "-",
"+", "-", "-"
),
SubjectID = c(
rep_len("S1", 5),
rep_len("S2", 4)
),
CellMarker = c(
rep_len("CM1", 5),
rep_len("CM2", 4)
),
Tissue = c(
rep_len("T1", 5),
rep_len("T2", 4)
),
TimePoint = c(
rep_len("0001", 3),
"0010", "0015",
rep_len("0001", 2),
rep_len("0020", 2)
),
Value_sum = c(
50, 80, 650, 46, 79, 633,
875, 99, 123
)
)
#------------------------------------------------------------------------------#
# Test sample_statistics
#------------------------------------------------------------------------------#
test_that("sample_statistics works as expected with default functions", {
val_cols <- c("seqCount", "fragmentEstimate")
stats <- sample_statistics(
x = integration_matrices,
metadata = association_file,
value_columns = val_cols
)
fun_names <- names(default_stats())
fun_names <- fun_names[fun_names != "describe"]
desc_fun_names <- paste("describe", c(
"vars", "n", "mean", "sd",
"median", "trimmed", "mad",
"min", "max", "range", "skew",
"kurtosis", "se"
), sep = "_")
fun_names <- c(fun_names, desc_fun_names)
expected_name_cols <- unlist(purrr::map(
val_cols,
~ paste(.x, fun_names, sep = "_")
))
expect_true(all(c(expected_name_cols, "nIS") %in% colnames(stats$x)))
expect_true(all(c(expected_name_cols, "nIS") %in% colnames(stats$metadata)))
})
#------------------------------------------------------------------------------#
# Test top_integrations
#------------------------------------------------------------------------------#
test_that("top_integrations works as expected", {
example <- tibble::tribble(
~chr, ~integration_locus, ~strand, ~SubjectID, ~Tissue, ~abundance,
"1", 34254, "+", "S1", "T1", 0.27,
"1", 56423, "+", "S1", "T1", 0.02,
"2", 85834, "-", "S1", "T1", 0.12,
"5", 12334, "-", "S1", "T1", 0.05,
"6", 64721, "+", "S1", "T1", 0.16,
"1", 96473, "-", "S1", "T1", 0.29,
"7", 31434, "+", "S1", "T1", 0.09,
"1", 34254, "+", "S2", "T1", 0.56,
"X", 31246, "+", "S2", "T1", 0.01,
"8", 12354, "-", "S2", "T1", 0.08,
"9", 13468, "+", "S2", "T1", 0.15,
"5", 86534, "-", "S2", "T1", 0.19,
"1", 74567, "+", "S2", "T1", 0.01
)
top_3 <- top_integrations(example,
n = 3,
columns = "abundance"
)
expected_top_3 <- tibble::tribble(
~chr, ~integration_locus, ~strand, ~abundance, ~SubjectID, ~Tissue,
"1", 34254, "+", 0.56, "S2", "T1",
"1", 96473, "-", 0.29, "S1", "T1",
"1", 34254, "+", 0.27, "S1", "T1"
)
expect_equal(top_3, expected_top_3)
top_3 <- top_integrations(example,
n = 3,
columns = "abundance",
key = c("SubjectID", "Tissue")
)
expected_top_3 <- tibble::tribble(
~SubjectID, ~Tissue, ~chr, ~integration_locus, ~strand, ~abundance,
"S1", "T1", "1", 96473, "-", 0.29,
"S1", "T1", "1", 34254, "+", 0.27,
"S1", "T1", "6", 64721, "+", 0.16,
"S2", "T1", "1", 34254, "+", 0.56,
"S2", "T1", "5", 86534, "-", 0.19,
"S2", "T1", "9", 13468, "+", 0.15,
)
expect_equal(top_3, expected_top_3)
})
#------------------------------------------------------------------------------#
# Test cumulative_is
#------------------------------------------------------------------------------#
test_that("cumulative_is produces correct output", {
c_is <- cumulative_is(minimal_agg_example,
expand = FALSE,
keep_og_is = TRUE
)
expect_true(nrow(c_is$coordinates) == 5)
expect_true(all(c("is", "cumulative_is") %in% colnames(c_is$coordinates)))
expect_equal(c_is$counts$is_n_cumulative, c(3, 4, 5, 2, 4))
c_is <- cumulative_is(minimal_agg_example,
keep_og_is = FALSE,
expand = FALSE
)
expect_true(nrow(c_is$coordinates) == 5)
expect_true(all(c("cumulative_is") %in% colnames(c_is$coordinates)))
expect_equal(c_is$counts$is_n_cumulative, c(3, 4, 5, 2, 4))
c_is <- cumulative_is(minimal_agg_example,
keep_og_is = FALSE,
expand = TRUE
)
expect_true(all(mandatory_IS_vars() %in% colnames(c_is$coordinates)))
})
test_that("cumulative_is works as expected with tp 0", {
all_zeros <- minimal_agg_example |>
dplyr::mutate(TimePoint = "0000")
expect_message(
{
c_is <- cumulative_is(all_zeros)
},
class = "only_zero_tps"
)
expect_null(c_is)
some_zeros <- minimal_agg_example
some_zeros[c(1, 2, 3), ]$TimePoint <- "0000"
c_is <- cumulative_is(some_zeros, expand = FALSE)
expect_true(c_is$counts[1, ]$TimePoint == 10 &
c_is$counts[1, ]$is_n_cumulative == 1)
})
#------------------------------------------------------------------------------#
# Test .assign_iss_by_tp
#------------------------------------------------------------------------------#
test_that(".assign_iss_by_tp assigns iss correctly", {
test_df <- tibble::tribble(
~chr, ~integration_locus, ~strand, ~CellMarker, ~Tissue, ~TimePoint,
"1", 12345, "+", "CD34", "BM", "03",
"1", 12345, "+", "CD34", "BM", "01",
"1", 12345, "+", "CD34", "BM", "06",
"2", 54321, "-", "CD34", "BM", "01",
"3", 62135, "+", "CD34", "BM", "02",
"3", 62135, "+", "CD34", "BM", "08"
)
expected_assign <- tibble::tribble(
~chr, ~integration_locus, ~strand, ~CellMarker, ~Tissue, ~TimePoint,
"1", 12345, "+", "CD34", "BM", 1,
"2", 54321, "-", "CD34", "BM", 1,
"3", 62135, "+", "CD34", "BM", 2
)
re_assigned <- .assign_iss_by_tp(
df = test_df,
timepoint_column = "TimePoint"
)
expect_equal(re_assigned, expected_assign)
})
#------------------------------------------------------------------------------#
# Test iss_source
#------------------------------------------------------------------------------#
test_df2 <- tibble::tibble(
chr = c(
"1", "1", "1", "1", "2", "2", "3", "3",
"1", "1", "1", "1", "1", "2", "3", "3"
),
integration_locus = c(
12345, 43524, 12345, 12345, 54321,
76835, 62135, 62135, 12345, 12345,
56832, 12345, 12345, 54321, 62135,
62135
),
strand = c(
"+", "+", "+", "+", "-", "-", "+", "+", "+",
"+", "-", "+", "+", "-", "+", "+"
),
SubjectID = c(
"PT01", "PT02", "PT01", "PT01", "PT01",
"PT02", "PT01", "PT01", "PT01", "PT01",
"PT02", "PT01", "PT02", "PT01", "PT01",
"PT01"
),
CellMarker = c(
"CD34", "CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "CD34", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole", "Whole",
"Whole"
),
Tissue = c(
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM"
),
TimePoint = c(
"03", "03", "01", "06", "01", "01", "02",
"08", "03", "01", "01", "06", "06", "01",
"02", "08"
)
)
test_df3 <- tibble::tibble(
chr = c(
"1", "1", "1", "1", "2", "2", "3", "3", "1",
"1", "1", "1", "1", "2", "3", "3"
),
integration_locus = c(
56252, 43524, 12345, 86435, 54321,
76835, 62135, 432245, 12345, 534587,
56832, 12345, 12345, 578635, 62135,
62135
),
strand = c(
"+", "+", "+", "+", "-", "-", "+", "+", "+",
"+", "-", "+", "+", "-", "+", "+"
),
SubjectID = c(
"PT02", "PT02", "PT01", "PT01", "PT01",
"PT02", "PT01", "PT01", "PT01", "PT01",
"PT02", "PT01", "PT02", "PT01", "PT02",
"PT01"
),
CellMarker = c(
"CD14", "CD13", "CD15", "CD14", "CD14",
"CD13", "CD14", "CD13", "CD14", "CD15",
"CD15", "CD14", "CD15", "CD13", "CD14",
"CD13"
),
Tissue = c(
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB"
),
TimePoint = c(
"03", "03", "01", "06", "01", "01", "02",
"08", "03", "01", "01", "06", "06", "01",
"02", "08"
)
)
expected_res1 <- list(
PT01 = tibble::tibble(
g1 = c(
"PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_Whole_BM_1", "PT01_Whole_BM_2",
"PT01_Whole_BM_1", "PT01_Whole_BM_2",
"PT01_Whole_BM_1", "PT01_Whole_BM_2",
"PT01_Whole_BM_1", "PT01_Whole_BM_2",
"PT01_Whole_BM_1", "PT01_Whole_BM_2",
"PT01_Whole_BM_1", "PT01_Whole_BM_2",
"PT01_Whole_BM_1", "PT01_Whole_BM_2"
) |> paste0("-1"),
g1_SubjectID = c(
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01"
),
g1_CellMarker = c(
"CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole"
),
g1_Tissue = c(
"BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM"
),
g1_TimePoint = c(
1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2,
1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2,
1, 2, 1, 2
),
g2 = c(
"PT01_CD15_PB_01", "PT01_CD15_PB_01",
"PT01_CD14_PB_06", "PT01_CD14_PB_06",
"PT01_CD14_PB_01", "PT01_CD14_PB_01",
"PT01_CD14_PB_02", "PT01_CD14_PB_02",
"PT01_CD13_PB_08", "PT01_CD13_PB_08",
"PT01_CD14_PB_03", "PT01_CD14_PB_03",
"PT01_CD13_PB_01", "PT01_CD13_PB_01",
"PT01_CD15_PB_01", "PT01_CD15_PB_01",
"PT01_CD14_PB_06", "PT01_CD14_PB_06",
"PT01_CD14_PB_01", "PT01_CD14_PB_01",
"PT01_CD14_PB_02", "PT01_CD14_PB_02",
"PT01_CD13_PB_08", "PT01_CD13_PB_08",
"PT01_CD14_PB_03", "PT01_CD14_PB_03",
"PT01_CD13_PB_01", "PT01_CD13_PB_01"
) |> paste0("-2"),
g2_SubjectID = c(
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01"
),
g2_CellMarker = c(
"CD15", "CD15", "CD14", "CD14",
"CD14", "CD14", "CD14", "CD14",
"CD13", "CD13", "CD14", "CD14",
"CD13", "CD13", "CD15", "CD15",
"CD14", "CD14", "CD14", "CD14",
"CD14", "CD14", "CD13", "CD13",
"CD14", "CD14", "CD13", "CD13"
),
g2_Tissue = c(
"PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB"
),
g2_TimePoint = c(
1, 1, 6, 6, 1, 1, 2, 2, 8, 8, 3, 3,
1, 1, 1, 1, 6, 6, 1, 1, 2, 2, 8, 8,
3, 3, 1, 1
),
chr = c(
"1", NA, "1", NA, "2", NA, NA, "3",
NA, "3", "1", NA, NA, NA, "1", NA,
"1", NA, "2", NA, NA, "3", NA, "3",
"1", NA, NA, NA
),
integration_locus = c(
12345, NA, 12345, NA, 54321,
NA, NA, 62135, NA, 62135, 12345,
NA, NA, NA, 12345, NA, 12345,
NA, 54321, NA, NA, 62135, NA,
62135, 12345, NA, NA, NA
),
strand = c(
"+", NA, "+", NA, "-", NA, NA,
"+", NA, "+", "+", NA, NA, NA,
"+", NA, "+", NA, "-", NA, NA,
"+", NA, "+", "+", NA, NA, NA
),
sharing_perc = c(
50, 0, 50, 0, 100, 0, 0, 100, 0, 50,
100, 0, 0, 0, 50, 0, 50, 0, 100, 0,
0, 100, 0, 50, 100, 0, 0, 0
)
) |>
dplyr::arrange(.data$g1, .data$g2),
PT02 = tibble::tibble(
g1 = c(
"PT02_CD34_BM_3", "PT02_CD34_BM_1",
"PT02_CD34_BM_3", "PT02_CD34_BM_1",
"PT02_CD34_BM_3", "PT02_CD34_BM_1",
"PT02_CD34_BM_3", "PT02_CD34_BM_1",
"PT02_CD34_BM_3", "PT02_CD34_BM_1",
"PT02_CD34_BM_3", "PT02_CD34_BM_1",
"PT02_Whole_BM_6", "PT02_Whole_BM_1",
"PT02_Whole_BM_6", "PT02_Whole_BM_1",
"PT02_Whole_BM_6", "PT02_Whole_BM_1",
"PT02_Whole_BM_6", "PT02_Whole_BM_1",
"PT02_Whole_BM_6", "PT02_Whole_BM_1",
"PT02_Whole_BM_6", "PT02_Whole_BM_1"
) |> paste0("-1"),
g1_SubjectID = c(
"PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02"
),
g1_CellMarker = c(
"CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "CD34", "CD34",
"Whole", "Whole", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole"
),
g1_Tissue = c(
"BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM"
),
g1_TimePoint = c(
3, 1, 3, 1, 3, 1, 3, 1, 3, 1, 3, 1,
6, 1, 6, 1, 6, 1, 6, 1, 6, 1, 6, 1
),
g2 = c(
"PT02_CD14_PB_03", "PT02_CD14_PB_03",
"PT02_CD13_PB_03", "PT02_CD13_PB_03",
"PT02_CD13_PB_01", "PT02_CD13_PB_01",
"PT02_CD15_PB_01", "PT02_CD15_PB_01",
"PT02_CD15_PB_06", "PT02_CD15_PB_06",
"PT02_CD14_PB_02", "PT02_CD14_PB_02",
"PT02_CD14_PB_03", "PT02_CD14_PB_03",
"PT02_CD13_PB_03", "PT02_CD13_PB_03",
"PT02_CD13_PB_01", "PT02_CD13_PB_01",
"PT02_CD15_PB_01", "PT02_CD15_PB_01",
"PT02_CD15_PB_06", "PT02_CD15_PB_06",
"PT02_CD14_PB_02", "PT02_CD14_PB_02"
) |> paste0("-2"),
g2_SubjectID = c(
"PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02"
),
g2_CellMarker = c(
"CD14", "CD14", "CD13", "CD13",
"CD13", "CD13", "CD15", "CD15",
"CD15", "CD15", "CD14", "CD14",
"CD14", "CD14", "CD13", "CD13",
"CD13", "CD13", "CD15", "CD15",
"CD15", "CD15", "CD14", "CD14"
),
g2_Tissue = c(
"PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB"
),
g2_TimePoint = c(
3, 3, 3, 3, 1, 1, 1, 1, 6, 6, 2, 2,
3, 3, 3, 3, 1, 1, 1, 1, 6, 6, 2, 2
),
chr = c(
NA, NA, "1", NA, NA, "2", NA, NA,
NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, 1, 1, NA, NA,
NA
),
integration_locus = c(
NA, NA, 43524, NA, NA, 76835,
NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, 56832,
12345, NA, NA, NA
),
strand = c(
NA, NA, "+", NA, NA, "-", NA,
NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA,
"-", "+", NA, NA, NA
),
sharing_perc = c(
0, 0, 100, 0, 0, 100, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 100,
100, 0, 0, 0
)
) |>
dplyr::arrange(.data$g1, .data$g2)
)
expected_res2 <- tibble::tibble(
g1 = c(
"PT01_CD34_BM_1", "PT01_CD34_BM_2", "PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2", "PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2", "PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2", "PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2", "PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2", "PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2", "PT01_Whole_BM_1",
"PT01_Whole_BM_2", "PT01_Whole_BM_1", "PT01_Whole_BM_2",
"PT01_Whole_BM_1", "PT01_Whole_BM_2", "PT01_Whole_BM_1",
"PT01_Whole_BM_2", "PT01_Whole_BM_1", "PT01_Whole_BM_2",
"PT01_Whole_BM_1", "PT01_Whole_BM_2", "PT01_Whole_BM_1",
"PT01_Whole_BM_2", "PT01_Whole_BM_1", "PT01_Whole_BM_2",
"PT01_Whole_BM_1", "PT01_Whole_BM_2", "PT01_Whole_BM_1",
"PT01_Whole_BM_2", "PT01_Whole_BM_1", "PT01_Whole_BM_2",
"PT01_Whole_BM_1", "PT01_Whole_BM_2", "PT01_Whole_BM_1",
"PT01_Whole_BM_2", "PT02_CD34_BM_3", "PT02_CD34_BM_1",
"PT02_CD34_BM_3", "PT02_CD34_BM_1", "PT02_CD34_BM_3",
"PT02_CD34_BM_1", "PT02_CD34_BM_3", "PT02_CD34_BM_1",
"PT02_CD34_BM_3", "PT02_CD34_BM_1", "PT02_CD34_BM_3",
"PT02_CD34_BM_1", "PT02_CD34_BM_3", "PT02_CD34_BM_1",
"PT02_CD34_BM_3", "PT02_CD34_BM_1", "PT02_CD34_BM_3",
"PT02_CD34_BM_1", "PT02_CD34_BM_3", "PT02_CD34_BM_1",
"PT02_CD34_BM_3", "PT02_CD34_BM_1", "PT02_CD34_BM_3",
"PT02_CD34_BM_1", "PT02_CD34_BM_3", "PT02_CD34_BM_1",
"PT02_Whole_BM_6", "PT02_Whole_BM_1", "PT02_Whole_BM_6",
"PT02_Whole_BM_1", "PT02_Whole_BM_6", "PT02_Whole_BM_1",
"PT02_Whole_BM_6", "PT02_Whole_BM_1", "PT02_Whole_BM_6",
"PT02_Whole_BM_1", "PT02_Whole_BM_6", "PT02_Whole_BM_1",
"PT02_Whole_BM_6", "PT02_Whole_BM_1", "PT02_Whole_BM_6",
"PT02_Whole_BM_1", "PT02_Whole_BM_6", "PT02_Whole_BM_1",
"PT02_Whole_BM_6", "PT02_Whole_BM_1", "PT02_Whole_BM_6",
"PT02_Whole_BM_1", "PT02_Whole_BM_6", "PT02_Whole_BM_1",
"PT02_Whole_BM_6", "PT02_Whole_BM_1"
) |> paste0("-1"),
g1_SubjectID = c(
"PT01", "PT01", "PT01", "PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02", "PT02", "PT02"
),
g1_CellMarker = c(
"CD34", "CD34", "CD34", "CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "CD34", "CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "CD34", "CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "CD34", "CD34", "CD34", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole", "Whole", "Whole",
"CD34", "CD34", "CD34", "CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "CD34", "CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "CD34", "CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "CD34", "CD34", "CD34", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole", "Whole", "Whole"
),
g1_Tissue = c(
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM"
),
g1_TimePoint = c(
1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,
2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2,
1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 3, 1, 3, 1, 3,
1, 3, 1, 3, 1, 3, 1, 3, 1, 3, 1, 3, 1, 3, 1, 3, 1, 3, 1,
3, 1, 6, 1, 6, 1, 6, 1, 6, 1, 6, 1, 6, 1, 6, 1, 6, 1, 6,
1, 6, 1, 6, 1, 6, 1, 6, 1
),
g2 = c(
"PT02_CD14_PB_03", "PT02_CD14_PB_03", "PT02_CD13_PB_03",
"PT02_CD13_PB_03", "PT01_CD15_PB_01", "PT01_CD15_PB_01",
"PT01_CD14_PB_06", "PT01_CD14_PB_06", "PT01_CD14_PB_01",
"PT01_CD14_PB_01", "PT02_CD13_PB_01", "PT02_CD13_PB_01",
"PT01_CD14_PB_02", "PT01_CD14_PB_02", "PT01_CD13_PB_08",
"PT01_CD13_PB_08", "PT01_CD14_PB_03", "PT01_CD14_PB_03",
"PT02_CD15_PB_01", "PT02_CD15_PB_01", "PT02_CD15_PB_06",
"PT02_CD15_PB_06", "PT01_CD13_PB_01", "PT01_CD13_PB_01",
"PT02_CD14_PB_02", "PT02_CD14_PB_02", "PT02_CD14_PB_03",
"PT02_CD14_PB_03", "PT02_CD13_PB_03", "PT02_CD13_PB_03",
"PT01_CD15_PB_01", "PT01_CD15_PB_01", "PT01_CD14_PB_06",
"PT01_CD14_PB_06", "PT01_CD14_PB_01", "PT01_CD14_PB_01",
"PT02_CD13_PB_01", "PT02_CD13_PB_01", "PT01_CD14_PB_02",
"PT01_CD14_PB_02", "PT01_CD13_PB_08", "PT01_CD13_PB_08",
"PT01_CD14_PB_03", "PT01_CD14_PB_03", "PT02_CD15_PB_01",
"PT02_CD15_PB_01", "PT02_CD15_PB_06", "PT02_CD15_PB_06",
"PT01_CD13_PB_01", "PT01_CD13_PB_01", "PT02_CD14_PB_02",
"PT02_CD14_PB_02", "PT02_CD14_PB_03", "PT02_CD14_PB_03",
"PT02_CD13_PB_03", "PT02_CD13_PB_03", "PT01_CD15_PB_01",
"PT01_CD15_PB_01", "PT01_CD14_PB_06", "PT01_CD14_PB_06",
"PT01_CD14_PB_01", "PT01_CD14_PB_01", "PT02_CD13_PB_01",
"PT02_CD13_PB_01", "PT01_CD14_PB_02", "PT01_CD14_PB_02",
"PT01_CD13_PB_08", "PT01_CD13_PB_08", "PT01_CD14_PB_03",
"PT01_CD14_PB_03", "PT02_CD15_PB_01", "PT02_CD15_PB_01",
"PT02_CD15_PB_06", "PT02_CD15_PB_06", "PT01_CD13_PB_01",
"PT01_CD13_PB_01", "PT02_CD14_PB_02", "PT02_CD14_PB_02",
"PT02_CD14_PB_03", "PT02_CD14_PB_03", "PT02_CD13_PB_03",
"PT02_CD13_PB_03", "PT01_CD15_PB_01", "PT01_CD15_PB_01",
"PT01_CD14_PB_06", "PT01_CD14_PB_06", "PT01_CD14_PB_01",
"PT01_CD14_PB_01", "PT02_CD13_PB_01", "PT02_CD13_PB_01",
"PT01_CD14_PB_02", "PT01_CD14_PB_02", "PT01_CD13_PB_08",
"PT01_CD13_PB_08", "PT01_CD14_PB_03", "PT01_CD14_PB_03",
"PT02_CD15_PB_01", "PT02_CD15_PB_01", "PT02_CD15_PB_06",
"PT02_CD15_PB_06", "PT01_CD13_PB_01", "PT01_CD13_PB_01",
"PT02_CD14_PB_02", "PT02_CD14_PB_02"
) |> paste0("-2"),
g2_SubjectID = c(
"PT02", "PT02", "PT02", "PT02", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT02", "PT02", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01", "PT02", "PT02", "PT02",
"PT02", "PT01", "PT01", "PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT01", "PT01", "PT01", "PT01", "PT01",
"PT01", "PT02", "PT02", "PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT02", "PT02", "PT02", "PT02", "PT01",
"PT01", "PT02", "PT02", "PT02", "PT02", "PT02", "PT02",
"PT01", "PT01", "PT01", "PT01", "PT01", "PT01", "PT02",
"PT02", "PT01", "PT01", "PT01", "PT01", "PT01", "PT01",
"PT02", "PT02", "PT02", "PT02", "PT01", "PT01", "PT02",
"PT02", "PT02", "PT02", "PT02", "PT02", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01", "PT02", "PT02", "PT01",
"PT01", "PT01", "PT01", "PT01", "PT01", "PT02", "PT02",
"PT02", "PT02", "PT01", "PT01", "PT02", "PT02"
),
g2_CellMarker = c(
"CD14", "CD14", "CD13", "CD13", "CD15", "CD15", "CD14",
"CD14", "CD14", "CD14", "CD13", "CD13", "CD14", "CD14",
"CD13", "CD13", "CD14", "CD14", "CD15", "CD15", "CD15",
"CD15", "CD13", "CD13", "CD14", "CD14", "CD14", "CD14",
"CD13", "CD13", "CD15", "CD15", "CD14", "CD14", "CD14",
"CD14", "CD13", "CD13", "CD14", "CD14", "CD13", "CD13",
"CD14", "CD14", "CD15", "CD15", "CD15", "CD15", "CD13",
"CD13", "CD14", "CD14", "CD14", "CD14", "CD13", "CD13",
"CD15", "CD15", "CD14", "CD14", "CD14", "CD14", "CD13",
"CD13", "CD14", "CD14", "CD13", "CD13", "CD14", "CD14",
"CD15", "CD15", "CD15", "CD15", "CD13", "CD13", "CD14",
"CD14", "CD14", "CD14", "CD13", "CD13", "CD15", "CD15",
"CD14", "CD14", "CD14", "CD14", "CD13", "CD13", "CD14",
"CD14", "CD13", "CD13", "CD14", "CD14", "CD15", "CD15",
"CD15", "CD15", "CD13", "CD13", "CD14", "CD14"
),
g2_Tissue = c(
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB"
),
g2_TimePoint = c(
3, 3, 3, 3, 1, 1, 6, 6, 1, 1, 1, 1, 2, 2, 8, 8, 3, 3, 1,
1, 6, 6, 1, 1, 2, 2, 3, 3, 3, 3, 1, 1, 6, 6, 1, 1, 1, 1,
2, 2, 8, 8, 3, 3, 1, 1, 6, 6, 1, 1, 2, 2, 3, 3, 3, 3, 1,
1, 6, 6, 1, 1, 1, 1, 2, 2, 8, 8, 3, 3, 1, 1, 6, 6, 1, 1,
2, 2, 3, 3, 3, 3, 1, 1, 6, 6, 1, 1, 1, 1, 2, 2, 8, 8, 3,
3, 1, 1, 6, 6, 1, 1, 2, 2
),
chr = c(
NA, NA, NA, NA, "1", NA, "1", NA, "2", NA, NA, NA, NA, "3", NA,
"3", "1", NA, NA, NA, "1", NA, NA, NA, NA, "3", NA, NA, NA, NA,
"1", NA, "1", NA, "2", NA, NA, NA, NA, "3", NA, "3", "1", NA, NA,
NA, "1", NA, NA, NA, NA, "3", NA, NA, "1", NA, NA, NA, NA, NA, NA,
NA, NA, "2", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, "1", NA, "1", NA, NA, NA, NA, NA, NA, NA, NA,
NA, "1", NA, NA, "1", "1", NA, NA, NA, NA, NA
),
integration_locus = c(
NA, NA, NA, NA, 12345, NA, 12345, NA, 54321, NA, NA,
NA, NA, 62135, NA, 62135, 12345, NA, NA, NA, 12345,
NA, NA, NA, NA, 62135, NA, NA, NA, NA, 12345, NA,
12345, NA, 54321, NA, NA, NA, NA, 62135, NA, 62135,
12345, NA, NA, NA, 12345, NA, NA, NA, NA, 62135, NA,
NA, 43524, NA, NA, NA, NA, NA, NA, NA, NA, 76835, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, 12345, NA, 12345, NA, NA, NA, NA, NA,
NA, NA, NA, NA, 12345, NA, NA, 56832, 12345, NA, NA,
NA, NA, NA
),
strand = c(
NA, NA, NA, NA, "+", NA, "+", NA, "-", NA, NA, NA, NA, "+", NA,
"+", "+", NA, NA, NA, "+", NA, NA, NA, NA, "+", NA, NA, NA, NA,
"+", NA, "+", NA, "-", NA, NA, NA, NA, "+", NA, "+", "+", NA,
NA, NA, "+", NA, NA, NA, NA, "+", NA, NA, "+", NA, NA, NA, NA,
NA, NA, NA, NA, "-", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, "+", NA, "+", NA, NA, NA, NA, NA, NA,
NA, NA, NA, "+", NA, NA, "-", "+", NA, NA, NA, NA, NA
),
sharing_perc = c(
0, 0, 0, 0, 50, 0, 50, 0, 100, 0, 0, 0, 0, 100, 0, 50,
100, 0, 0, 0, 100, 0, 0, 0, 0, 100, 0, 0, 0, 0, 50, 0, 50,
0, 100, 0, 0, 0, 0, 100, 0, 50, 100, 0, 0, 0, 100, 0, 0,
0, 0, 100, 0, 0, 100, 0, 0, 0, 0, 0, 0, 0, 0, 100, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 50, 0, 50,
0, 0, 0, 0, 0, 0, 0, 0, 0, 100, 0, 0, 100, 100, 0, 0, 0,
0, 0
)
) |> dplyr::arrange(.data$g1, .data$g2)
test_that("iss_source produces expected output - per patient", {
withr::local_options(list(
ISAnalytics.parallel_processing = FALSE
))
res <- iss_source(test_df2, test_df3) |>
purrr::map(~ dplyr::arrange(.x, .data$g1, .data$g2))
expect_equal(res, expected_res1)
})
test_that("iss_source produces expected output - NO per patient", {
withr::local_options(list(
ISAnalytics.parallel_processing = FALSE
))
res <- iss_source(test_df2, test_df3, by_subject = FALSE) |>
dplyr::arrange(.data$g1, .data$g2)
expect_equal(res, expected_res2)
})
#------------------------------------------------------------------------------#
# Test gene_frequency_fisher
#------------------------------------------------------------------------------#
test_that("gene_frequency_fisher produces expected output", {
withr::local_options(list(ISAnalytics.verbose = TRUE))
test_cis <- readRDS(fs::path(testdata_path, "test_cis_for_fisher.Rds"))
## -- Testing intersection
fisher_df <- gene_frequency_fisher(test_cis[[1]], test_cis[[2]],
min_is_per_gene = 1,
gene_set_method = "intersection"
)
common_genes <- intersect(test_cis$PT001$GeneName, test_cis$PT002$GeneName)
expect_true(all(fisher_df$GeneName %in% common_genes) &
all(common_genes %in% fisher_df$GeneName))
## -- Testing union
fisher_df <- gene_frequency_fisher(test_cis[[1]], test_cis[[2]],
min_is_per_gene = 1,
gene_set_method = "union",
remove_unbalanced_0 = FALSE
)
union_genes <- union(test_cis$PT001$GeneName, test_cis$PT002$GeneName)
expect_true(all(fisher_df$GeneName %in% union_genes) &
all(union_genes %in% fisher_df$GeneName))
## -- Testing default filtering
expect_message(
{
fisher_df <- gene_frequency_fisher(test_cis[[1]], test_cis[[2]],
min_is_per_gene = 3,
gene_set_method = "intersection"
)
},
class = "empty_df_gene_freq"
)
expect_null(fisher_df)
fisher_df <- gene_frequency_fisher(test_cis[[1]], test_cis[[2]],
min_is_per_gene = 3,
gene_set_method = "union"
)
expect_true(nrow(fisher_df) == 2)
})
#------------------------------------------------------------------------------#
# Test top_targeted_genes
#------------------------------------------------------------------------------#
test_that("top_targeted_genes produces expected output", {
annot_ex <- minimal_agg_example |>
dplyr::mutate(
GeneName = c(
"GENE1", "GENE1", "GENE1", "GENE2", "GENE2", "GENE3", "GENE4",
"GENE4", "GENE4"
),
GeneStrand = c("+", "+", "+", "-", "-", "-", "+", "+", "+"),
.after = "strand"
)
# --- top genes overall
top_5 <- top_targeted_genes(annot_ex, n = 5, key = NULL)
expected <- tibble::tibble(
GeneName = c("GENE1", "GENE2", "GENE1", "GENE3", "GENE4"),
GeneStrand = c("+", "-", "+", "-", "+"),
chr = c("2", "5", "1", "3", "10"),
n_IS = c(2, 2, 1, 1, 1)
)
expect_equal(top_5, expected)
top_5 <- top_targeted_genes(annot_ex,
n = 5, key = NULL,
consider_chr = FALSE
)
expected <- tibble::tibble(
GeneName = c("GENE1", "GENE4", "GENE2", "GENE3"),
GeneStrand = c("+", "+", "-", "-"),
n_IS = c(3, 3, 2, 1)
)
expect_equal(top_5, expected)
top_5 <- top_targeted_genes(annot_ex,
n = 5, key = NULL,
consider_chr = FALSE,
consider_gene_strand = FALSE
)
expected <- tibble::tibble(
GeneName = c("GENE1", "GENE4", "GENE2", "GENE3"),
n_IS = c(3, 3, 2, 1)
)
expect_equal(top_5, expected)
# --- top genes per group
top_5 <- top_targeted_genes(annot_ex,
n = 5,
key = c("SubjectID", "CellMarker")
)
expected <- tibble::tibble(
SubjectID = c("S1", "S1", "S1", "S2", "S2", "S2", "S2"),
CellMarker = c("CM1", "CM1", "CM1", "CM2", "CM2", "CM2", "CM2"),
GeneName = c(
"GENE1", "GENE2", "GENE1", "GENE3", "GENE4", "GENE4",
"GENE4"
),
GeneStrand = c("+", "-", "+", "-", "+", "+", "+"),
chr = c("2", "5", "1", "3", "3", "10", "11"),
n_IS = c(2, 2, 1, 1, 1, 1, 1)
)
top_5 <- top_targeted_genes(annot_ex,
n = 5,
key = c("SubjectID", "CellMarker"),
consider_chr = FALSE
)
expected <- tibble::tibble(
SubjectID = c("S1", "S1", "S2", "S2"),
CellMarker = c("CM1", "CM1", "CM2", "CM2"),
GeneName = c("GENE1", "GENE2", "GENE4", "GENE3"),
GeneStrand = c("+", "-", "+", "-"),
n_IS = c(3, 2, 3, 1)
)
})
calabrialab/ISAnalytics documentation built on Nov. 2, 2023, 8:57 p.m.
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#------------------------------------------------------------------------------#
# Global vars
#------------------------------------------------------------------------------#
withr::local_options(
ISAnalytics.verbose = FALSE,
ISAnalytics.reports = FALSE
)
minimal_agg_example <- tibble::tibble(
chr = c("1", "2", "2", "5", "5", "3", "3", "10", "11"),
integration_locus = c(
14505,
1005,
15513,
4561,
10167,
5247,
10951,
23403,
25611
),
strand = c(
"+", "-", "+", "+", "-", "-",
"+", "-", "-"
),
SubjectID = c(
rep_len("S1", 5),
rep_len("S2", 4)
),
CellMarker = c(
rep_len("CM1", 5),
rep_len("CM2", 4)
),
Tissue = c(
rep_len("T1", 5),
rep_len("T2", 4)
),
TimePoint = c(
rep_len("0001", 3),
"0010", "0015",
rep_len("0001", 2),
rep_len("0020", 2)
),
Value_sum = c(
50, 80, 650, 46, 79, 633,
875, 99, 123
)
)
#------------------------------------------------------------------------------#
# Test sample_statistics
#------------------------------------------------------------------------------#
test_that("sample_statistics works as expected with default functions", {
val_cols <- c("seqCount", "fragmentEstimate")
stats <- sample_statistics(
x = integration_matrices,
metadata = association_file,
value_columns = val_cols
)
fun_names <- names(default_stats())
fun_names <- fun_names[fun_names != "describe"]
desc_fun_names <- paste("describe", c(
"vars", "n", "mean", "sd",
"median", "trimmed", "mad",
"min", "max", "range", "skew",
"kurtosis", "se"
), sep = "_")
fun_names <- c(fun_names, desc_fun_names)
expected_name_cols <- unlist(purrr::map(
val_cols,
~ paste(.x, fun_names, sep = "_")
))
expect_true(all(c(expected_name_cols, "nIS") %in% colnames(stats$x)))
expect_true(all(c(expected_name_cols, "nIS") %in% colnames(stats$metadata)))
})
#------------------------------------------------------------------------------#
# Test top_integrations
#------------------------------------------------------------------------------#
test_that("top_integrations works as expected", {
example <- tibble::tribble(
~chr, ~integration_locus, ~strand, ~SubjectID, ~Tissue, ~abundance,
"1", 34254, "+", "S1", "T1", 0.27,
"1", 56423, "+", "S1", "T1", 0.02,
"2", 85834, "-", "S1", "T1", 0.12,
"5", 12334, "-", "S1", "T1", 0.05,
"6", 64721, "+", "S1", "T1", 0.16,
"1", 96473, "-", "S1", "T1", 0.29,
"7", 31434, "+", "S1", "T1", 0.09,
"1", 34254, "+", "S2", "T1", 0.56,
"X", 31246, "+", "S2", "T1", 0.01,
"8", 12354, "-", "S2", "T1", 0.08,
"9", 13468, "+", "S2", "T1", 0.15,
"5", 86534, "-", "S2", "T1", 0.19,
"1", 74567, "+", "S2", "T1", 0.01
)
top_3 <- top_integrations(example,
n = 3,
columns = "abundance"
)
expected_top_3 <- tibble::tribble(
~chr, ~integration_locus, ~strand, ~abundance, ~SubjectID, ~Tissue,
"1", 34254, "+", 0.56, "S2", "T1",
"1", 96473, "-", 0.29, "S1", "T1",
"1", 34254, "+", 0.27, "S1", "T1"
)
expect_equal(top_3, expected_top_3)
top_3 <- top_integrations(example,
n = 3,
columns = "abundance",
key = c("SubjectID", "Tissue")
)
expected_top_3 <- tibble::tribble(
~SubjectID, ~Tissue, ~chr, ~integration_locus, ~strand, ~abundance,
"S1", "T1", "1", 96473, "-", 0.29,
"S1", "T1", "1", 34254, "+", 0.27,
"S1", "T1", "6", 64721, "+", 0.16,
"S2", "T1", "1", 34254, "+", 0.56,
"S2", "T1", "5", 86534, "-", 0.19,
"S2", "T1", "9", 13468, "+", 0.15,
)
expect_equal(top_3, expected_top_3)
})
#------------------------------------------------------------------------------#
# Test cumulative_is
#------------------------------------------------------------------------------#
test_that("cumulative_is produces correct output", {
c_is <- cumulative_is(minimal_agg_example,
expand = FALSE,
keep_og_is = TRUE
)
expect_true(nrow(c_is$coordinates) == 5)
expect_true(all(c("is", "cumulative_is") %in% colnames(c_is$coordinates)))
expect_equal(c_is$counts$is_n_cumulative, c(3, 4, 5, 2, 4))
c_is <- cumulative_is(minimal_agg_example,
keep_og_is = FALSE,
expand = FALSE
)
expect_true(nrow(c_is$coordinates) == 5)
expect_true(all(c("cumulative_is") %in% colnames(c_is$coordinates)))
expect_equal(c_is$counts$is_n_cumulative, c(3, 4, 5, 2, 4))
c_is <- cumulative_is(minimal_agg_example,
keep_og_is = FALSE,
expand = TRUE
)
expect_true(all(mandatory_IS_vars() %in% colnames(c_is$coordinates)))
})
test_that("cumulative_is works as expected with tp 0", {
all_zeros <- minimal_agg_example |>
dplyr::mutate(TimePoint = "0000")
expect_message(
{
c_is <- cumulative_is(all_zeros)
},
class = "only_zero_tps"
)
expect_null(c_is)
some_zeros <- minimal_agg_example
some_zeros[c(1, 2, 3), ]$TimePoint <- "0000"
c_is <- cumulative_is(some_zeros, expand = FALSE)
expect_true(c_is$counts[1, ]$TimePoint == 10 &
c_is$counts[1, ]$is_n_cumulative == 1)
})
#------------------------------------------------------------------------------#
# Test .assign_iss_by_tp
#------------------------------------------------------------------------------#
test_that(".assign_iss_by_tp assigns iss correctly", {
test_df <- tibble::tribble(
~chr, ~integration_locus, ~strand, ~CellMarker, ~Tissue, ~TimePoint,
"1", 12345, "+", "CD34", "BM", "03",
"1", 12345, "+", "CD34", "BM", "01",
"1", 12345, "+", "CD34", "BM", "06",
"2", 54321, "-", "CD34", "BM", "01",
"3", 62135, "+", "CD34", "BM", "02",
"3", 62135, "+", "CD34", "BM", "08"
)
expected_assign <- tibble::tribble(
~chr, ~integration_locus, ~strand, ~CellMarker, ~Tissue, ~TimePoint,
"1", 12345, "+", "CD34", "BM", 1,
"2", 54321, "-", "CD34", "BM", 1,
"3", 62135, "+", "CD34", "BM", 2
)
re_assigned <- .assign_iss_by_tp(
df = test_df,
timepoint_column = "TimePoint"
)
expect_equal(re_assigned, expected_assign)
})
#------------------------------------------------------------------------------#
# Test iss_source
#------------------------------------------------------------------------------#
test_df2 <- tibble::tibble(
chr = c(
"1", "1", "1", "1", "2", "2", "3", "3",
"1", "1", "1", "1", "1", "2", "3", "3"
),
integration_locus = c(
12345, 43524, 12345, 12345, 54321,
76835, 62135, 62135, 12345, 12345,
56832, 12345, 12345, 54321, 62135,
62135
),
strand = c(
"+", "+", "+", "+", "-", "-", "+", "+", "+",
"+", "-", "+", "+", "-", "+", "+"
),
SubjectID = c(
"PT01", "PT02", "PT01", "PT01", "PT01",
"PT02", "PT01", "PT01", "PT01", "PT01",
"PT02", "PT01", "PT02", "PT01", "PT01",
"PT01"
),
CellMarker = c(
"CD34", "CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "CD34", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole", "Whole",
"Whole"
),
Tissue = c(
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM"
),
TimePoint = c(
"03", "03", "01", "06", "01", "01", "02",
"08", "03", "01", "01", "06", "06", "01",
"02", "08"
)
)
test_df3 <- tibble::tibble(
chr = c(
"1", "1", "1", "1", "2", "2", "3", "3", "1",
"1", "1", "1", "1", "2", "3", "3"
),
integration_locus = c(
56252, 43524, 12345, 86435, 54321,
76835, 62135, 432245, 12345, 534587,
56832, 12345, 12345, 578635, 62135,
62135
),
strand = c(
"+", "+", "+", "+", "-", "-", "+", "+", "+",
"+", "-", "+", "+", "-", "+", "+"
),
SubjectID = c(
"PT02", "PT02", "PT01", "PT01", "PT01",
"PT02", "PT01", "PT01", "PT01", "PT01",
"PT02", "PT01", "PT02", "PT01", "PT02",
"PT01"
),
CellMarker = c(
"CD14", "CD13", "CD15", "CD14", "CD14",
"CD13", "CD14", "CD13", "CD14", "CD15",
"CD15", "CD14", "CD15", "CD13", "CD14",
"CD13"
),
Tissue = c(
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB"
),
TimePoint = c(
"03", "03", "01", "06", "01", "01", "02",
"08", "03", "01", "01", "06", "06", "01",
"02", "08"
)
)
expected_res1 <- list(
PT01 = tibble::tibble(
g1 = c(
"PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_Whole_BM_1", "PT01_Whole_BM_2",
"PT01_Whole_BM_1", "PT01_Whole_BM_2",
"PT01_Whole_BM_1", "PT01_Whole_BM_2",
"PT01_Whole_BM_1", "PT01_Whole_BM_2",
"PT01_Whole_BM_1", "PT01_Whole_BM_2",
"PT01_Whole_BM_1", "PT01_Whole_BM_2",
"PT01_Whole_BM_1", "PT01_Whole_BM_2"
) |> paste0("-1"),
g1_SubjectID = c(
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01"
),
g1_CellMarker = c(
"CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole"
),
g1_Tissue = c(
"BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM"
),
g1_TimePoint = c(
1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2,
1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2,
1, 2, 1, 2
),
g2 = c(
"PT01_CD15_PB_01", "PT01_CD15_PB_01",
"PT01_CD14_PB_06", "PT01_CD14_PB_06",
"PT01_CD14_PB_01", "PT01_CD14_PB_01",
"PT01_CD14_PB_02", "PT01_CD14_PB_02",
"PT01_CD13_PB_08", "PT01_CD13_PB_08",
"PT01_CD14_PB_03", "PT01_CD14_PB_03",
"PT01_CD13_PB_01", "PT01_CD13_PB_01",
"PT01_CD15_PB_01", "PT01_CD15_PB_01",
"PT01_CD14_PB_06", "PT01_CD14_PB_06",
"PT01_CD14_PB_01", "PT01_CD14_PB_01",
"PT01_CD14_PB_02", "PT01_CD14_PB_02",
"PT01_CD13_PB_08", "PT01_CD13_PB_08",
"PT01_CD14_PB_03", "PT01_CD14_PB_03",
"PT01_CD13_PB_01", "PT01_CD13_PB_01"
) |> paste0("-2"),
g2_SubjectID = c(
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01"
),
g2_CellMarker = c(
"CD15", "CD15", "CD14", "CD14",
"CD14", "CD14", "CD14", "CD14",
"CD13", "CD13", "CD14", "CD14",
"CD13", "CD13", "CD15", "CD15",
"CD14", "CD14", "CD14", "CD14",
"CD14", "CD14", "CD13", "CD13",
"CD14", "CD14", "CD13", "CD13"
),
g2_Tissue = c(
"PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB"
),
g2_TimePoint = c(
1, 1, 6, 6, 1, 1, 2, 2, 8, 8, 3, 3,
1, 1, 1, 1, 6, 6, 1, 1, 2, 2, 8, 8,
3, 3, 1, 1
),
chr = c(
"1", NA, "1", NA, "2", NA, NA, "3",
NA, "3", "1", NA, NA, NA, "1", NA,
"1", NA, "2", NA, NA, "3", NA, "3",
"1", NA, NA, NA
),
integration_locus = c(
12345, NA, 12345, NA, 54321,
NA, NA, 62135, NA, 62135, 12345,
NA, NA, NA, 12345, NA, 12345,
NA, 54321, NA, NA, 62135, NA,
62135, 12345, NA, NA, NA
),
strand = c(
"+", NA, "+", NA, "-", NA, NA,
"+", NA, "+", "+", NA, NA, NA,
"+", NA, "+", NA, "-", NA, NA,
"+", NA, "+", "+", NA, NA, NA
),
sharing_perc = c(
50, 0, 50, 0, 100, 0, 0, 100, 0, 50,
100, 0, 0, 0, 50, 0, 50, 0, 100, 0,
0, 100, 0, 50, 100, 0, 0, 0
)
) |>
dplyr::arrange(.data$g1, .data$g2),
PT02 = tibble::tibble(
g1 = c(
"PT02_CD34_BM_3", "PT02_CD34_BM_1",
"PT02_CD34_BM_3", "PT02_CD34_BM_1",
"PT02_CD34_BM_3", "PT02_CD34_BM_1",
"PT02_CD34_BM_3", "PT02_CD34_BM_1",
"PT02_CD34_BM_3", "PT02_CD34_BM_1",
"PT02_CD34_BM_3", "PT02_CD34_BM_1",
"PT02_Whole_BM_6", "PT02_Whole_BM_1",
"PT02_Whole_BM_6", "PT02_Whole_BM_1",
"PT02_Whole_BM_6", "PT02_Whole_BM_1",
"PT02_Whole_BM_6", "PT02_Whole_BM_1",
"PT02_Whole_BM_6", "PT02_Whole_BM_1",
"PT02_Whole_BM_6", "PT02_Whole_BM_1"
) |> paste0("-1"),
g1_SubjectID = c(
"PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02"
),
g1_CellMarker = c(
"CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "CD34", "CD34",
"Whole", "Whole", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole"
),
g1_Tissue = c(
"BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM"
),
g1_TimePoint = c(
3, 1, 3, 1, 3, 1, 3, 1, 3, 1, 3, 1,
6, 1, 6, 1, 6, 1, 6, 1, 6, 1, 6, 1
),
g2 = c(
"PT02_CD14_PB_03", "PT02_CD14_PB_03",
"PT02_CD13_PB_03", "PT02_CD13_PB_03",
"PT02_CD13_PB_01", "PT02_CD13_PB_01",
"PT02_CD15_PB_01", "PT02_CD15_PB_01",
"PT02_CD15_PB_06", "PT02_CD15_PB_06",
"PT02_CD14_PB_02", "PT02_CD14_PB_02",
"PT02_CD14_PB_03", "PT02_CD14_PB_03",
"PT02_CD13_PB_03", "PT02_CD13_PB_03",
"PT02_CD13_PB_01", "PT02_CD13_PB_01",
"PT02_CD15_PB_01", "PT02_CD15_PB_01",
"PT02_CD15_PB_06", "PT02_CD15_PB_06",
"PT02_CD14_PB_02", "PT02_CD14_PB_02"
) |> paste0("-2"),
g2_SubjectID = c(
"PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02"
),
g2_CellMarker = c(
"CD14", "CD14", "CD13", "CD13",
"CD13", "CD13", "CD15", "CD15",
"CD15", "CD15", "CD14", "CD14",
"CD14", "CD14", "CD13", "CD13",
"CD13", "CD13", "CD15", "CD15",
"CD15", "CD15", "CD14", "CD14"
),
g2_Tissue = c(
"PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB"
),
g2_TimePoint = c(
3, 3, 3, 3, 1, 1, 1, 1, 6, 6, 2, 2,
3, 3, 3, 3, 1, 1, 1, 1, 6, 6, 2, 2
),
chr = c(
NA, NA, "1", NA, NA, "2", NA, NA,
NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, 1, 1, NA, NA,
NA
),
integration_locus = c(
NA, NA, 43524, NA, NA, 76835,
NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, 56832,
12345, NA, NA, NA
),
strand = c(
NA, NA, "+", NA, NA, "-", NA,
NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA,
"-", "+", NA, NA, NA
),
sharing_perc = c(
0, 0, 100, 0, 0, 100, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 100,
100, 0, 0, 0
)
) |>
dplyr::arrange(.data$g1, .data$g2)
)
expected_res2 <- tibble::tibble(
g1 = c(
"PT01_CD34_BM_1", "PT01_CD34_BM_2", "PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2", "PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2", "PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2", "PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2", "PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2", "PT01_CD34_BM_1", "PT01_CD34_BM_2",
"PT01_CD34_BM_1", "PT01_CD34_BM_2", "PT01_Whole_BM_1",
"PT01_Whole_BM_2", "PT01_Whole_BM_1", "PT01_Whole_BM_2",
"PT01_Whole_BM_1", "PT01_Whole_BM_2", "PT01_Whole_BM_1",
"PT01_Whole_BM_2", "PT01_Whole_BM_1", "PT01_Whole_BM_2",
"PT01_Whole_BM_1", "PT01_Whole_BM_2", "PT01_Whole_BM_1",
"PT01_Whole_BM_2", "PT01_Whole_BM_1", "PT01_Whole_BM_2",
"PT01_Whole_BM_1", "PT01_Whole_BM_2", "PT01_Whole_BM_1",
"PT01_Whole_BM_2", "PT01_Whole_BM_1", "PT01_Whole_BM_2",
"PT01_Whole_BM_1", "PT01_Whole_BM_2", "PT01_Whole_BM_1",
"PT01_Whole_BM_2", "PT02_CD34_BM_3", "PT02_CD34_BM_1",
"PT02_CD34_BM_3", "PT02_CD34_BM_1", "PT02_CD34_BM_3",
"PT02_CD34_BM_1", "PT02_CD34_BM_3", "PT02_CD34_BM_1",
"PT02_CD34_BM_3", "PT02_CD34_BM_1", "PT02_CD34_BM_3",
"PT02_CD34_BM_1", "PT02_CD34_BM_3", "PT02_CD34_BM_1",
"PT02_CD34_BM_3", "PT02_CD34_BM_1", "PT02_CD34_BM_3",
"PT02_CD34_BM_1", "PT02_CD34_BM_3", "PT02_CD34_BM_1",
"PT02_CD34_BM_3", "PT02_CD34_BM_1", "PT02_CD34_BM_3",
"PT02_CD34_BM_1", "PT02_CD34_BM_3", "PT02_CD34_BM_1",
"PT02_Whole_BM_6", "PT02_Whole_BM_1", "PT02_Whole_BM_6",
"PT02_Whole_BM_1", "PT02_Whole_BM_6", "PT02_Whole_BM_1",
"PT02_Whole_BM_6", "PT02_Whole_BM_1", "PT02_Whole_BM_6",
"PT02_Whole_BM_1", "PT02_Whole_BM_6", "PT02_Whole_BM_1",
"PT02_Whole_BM_6", "PT02_Whole_BM_1", "PT02_Whole_BM_6",
"PT02_Whole_BM_1", "PT02_Whole_BM_6", "PT02_Whole_BM_1",
"PT02_Whole_BM_6", "PT02_Whole_BM_1", "PT02_Whole_BM_6",
"PT02_Whole_BM_1", "PT02_Whole_BM_6", "PT02_Whole_BM_1",
"PT02_Whole_BM_6", "PT02_Whole_BM_1"
) |> paste0("-1"),
g1_SubjectID = c(
"PT01", "PT01", "PT01", "PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT02", "PT02", "PT02", "PT02"
),
g1_CellMarker = c(
"CD34", "CD34", "CD34", "CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "CD34", "CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "CD34", "CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "CD34", "CD34", "CD34", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole", "Whole", "Whole",
"CD34", "CD34", "CD34", "CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "CD34", "CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "CD34", "CD34", "CD34", "CD34", "CD34",
"CD34", "CD34", "CD34", "CD34", "CD34", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole", "Whole", "Whole",
"Whole", "Whole", "Whole", "Whole", "Whole", "Whole"
),
g1_Tissue = c(
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM", "BM",
"BM", "BM", "BM", "BM"
),
g1_TimePoint = c(
1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,
2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2,
1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 3, 1, 3, 1, 3,
1, 3, 1, 3, 1, 3, 1, 3, 1, 3, 1, 3, 1, 3, 1, 3, 1, 3, 1,
3, 1, 6, 1, 6, 1, 6, 1, 6, 1, 6, 1, 6, 1, 6, 1, 6, 1, 6,
1, 6, 1, 6, 1, 6, 1, 6, 1
),
g2 = c(
"PT02_CD14_PB_03", "PT02_CD14_PB_03", "PT02_CD13_PB_03",
"PT02_CD13_PB_03", "PT01_CD15_PB_01", "PT01_CD15_PB_01",
"PT01_CD14_PB_06", "PT01_CD14_PB_06", "PT01_CD14_PB_01",
"PT01_CD14_PB_01", "PT02_CD13_PB_01", "PT02_CD13_PB_01",
"PT01_CD14_PB_02", "PT01_CD14_PB_02", "PT01_CD13_PB_08",
"PT01_CD13_PB_08", "PT01_CD14_PB_03", "PT01_CD14_PB_03",
"PT02_CD15_PB_01", "PT02_CD15_PB_01", "PT02_CD15_PB_06",
"PT02_CD15_PB_06", "PT01_CD13_PB_01", "PT01_CD13_PB_01",
"PT02_CD14_PB_02", "PT02_CD14_PB_02", "PT02_CD14_PB_03",
"PT02_CD14_PB_03", "PT02_CD13_PB_03", "PT02_CD13_PB_03",
"PT01_CD15_PB_01", "PT01_CD15_PB_01", "PT01_CD14_PB_06",
"PT01_CD14_PB_06", "PT01_CD14_PB_01", "PT01_CD14_PB_01",
"PT02_CD13_PB_01", "PT02_CD13_PB_01", "PT01_CD14_PB_02",
"PT01_CD14_PB_02", "PT01_CD13_PB_08", "PT01_CD13_PB_08",
"PT01_CD14_PB_03", "PT01_CD14_PB_03", "PT02_CD15_PB_01",
"PT02_CD15_PB_01", "PT02_CD15_PB_06", "PT02_CD15_PB_06",
"PT01_CD13_PB_01", "PT01_CD13_PB_01", "PT02_CD14_PB_02",
"PT02_CD14_PB_02", "PT02_CD14_PB_03", "PT02_CD14_PB_03",
"PT02_CD13_PB_03", "PT02_CD13_PB_03", "PT01_CD15_PB_01",
"PT01_CD15_PB_01", "PT01_CD14_PB_06", "PT01_CD14_PB_06",
"PT01_CD14_PB_01", "PT01_CD14_PB_01", "PT02_CD13_PB_01",
"PT02_CD13_PB_01", "PT01_CD14_PB_02", "PT01_CD14_PB_02",
"PT01_CD13_PB_08", "PT01_CD13_PB_08", "PT01_CD14_PB_03",
"PT01_CD14_PB_03", "PT02_CD15_PB_01", "PT02_CD15_PB_01",
"PT02_CD15_PB_06", "PT02_CD15_PB_06", "PT01_CD13_PB_01",
"PT01_CD13_PB_01", "PT02_CD14_PB_02", "PT02_CD14_PB_02",
"PT02_CD14_PB_03", "PT02_CD14_PB_03", "PT02_CD13_PB_03",
"PT02_CD13_PB_03", "PT01_CD15_PB_01", "PT01_CD15_PB_01",
"PT01_CD14_PB_06", "PT01_CD14_PB_06", "PT01_CD14_PB_01",
"PT01_CD14_PB_01", "PT02_CD13_PB_01", "PT02_CD13_PB_01",
"PT01_CD14_PB_02", "PT01_CD14_PB_02", "PT01_CD13_PB_08",
"PT01_CD13_PB_08", "PT01_CD14_PB_03", "PT01_CD14_PB_03",
"PT02_CD15_PB_01", "PT02_CD15_PB_01", "PT02_CD15_PB_06",
"PT02_CD15_PB_06", "PT01_CD13_PB_01", "PT01_CD13_PB_01",
"PT02_CD14_PB_02", "PT02_CD14_PB_02"
) |> paste0("-2"),
g2_SubjectID = c(
"PT02", "PT02", "PT02", "PT02", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT02", "PT02", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01", "PT02", "PT02", "PT02",
"PT02", "PT01", "PT01", "PT02", "PT02", "PT02", "PT02",
"PT02", "PT02", "PT01", "PT01", "PT01", "PT01", "PT01",
"PT01", "PT02", "PT02", "PT01", "PT01", "PT01", "PT01",
"PT01", "PT01", "PT02", "PT02", "PT02", "PT02", "PT01",
"PT01", "PT02", "PT02", "PT02", "PT02", "PT02", "PT02",
"PT01", "PT01", "PT01", "PT01", "PT01", "PT01", "PT02",
"PT02", "PT01", "PT01", "PT01", "PT01", "PT01", "PT01",
"PT02", "PT02", "PT02", "PT02", "PT01", "PT01", "PT02",
"PT02", "PT02", "PT02", "PT02", "PT02", "PT01", "PT01",
"PT01", "PT01", "PT01", "PT01", "PT02", "PT02", "PT01",
"PT01", "PT01", "PT01", "PT01", "PT01", "PT02", "PT02",
"PT02", "PT02", "PT01", "PT01", "PT02", "PT02"
),
g2_CellMarker = c(
"CD14", "CD14", "CD13", "CD13", "CD15", "CD15", "CD14",
"CD14", "CD14", "CD14", "CD13", "CD13", "CD14", "CD14",
"CD13", "CD13", "CD14", "CD14", "CD15", "CD15", "CD15",
"CD15", "CD13", "CD13", "CD14", "CD14", "CD14", "CD14",
"CD13", "CD13", "CD15", "CD15", "CD14", "CD14", "CD14",
"CD14", "CD13", "CD13", "CD14", "CD14", "CD13", "CD13",
"CD14", "CD14", "CD15", "CD15", "CD15", "CD15", "CD13",
"CD13", "CD14", "CD14", "CD14", "CD14", "CD13", "CD13",
"CD15", "CD15", "CD14", "CD14", "CD14", "CD14", "CD13",
"CD13", "CD14", "CD14", "CD13", "CD13", "CD14", "CD14",
"CD15", "CD15", "CD15", "CD15", "CD13", "CD13", "CD14",
"CD14", "CD14", "CD14", "CD13", "CD13", "CD15", "CD15",
"CD14", "CD14", "CD14", "CD14", "CD13", "CD13", "CD14",
"CD14", "CD13", "CD13", "CD14", "CD14", "CD15", "CD15",
"CD15", "CD15", "CD13", "CD13", "CD14", "CD14"
),
g2_Tissue = c(
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB", "PB",
"PB", "PB", "PB", "PB"
),
g2_TimePoint = c(
3, 3, 3, 3, 1, 1, 6, 6, 1, 1, 1, 1, 2, 2, 8, 8, 3, 3, 1,
1, 6, 6, 1, 1, 2, 2, 3, 3, 3, 3, 1, 1, 6, 6, 1, 1, 1, 1,
2, 2, 8, 8, 3, 3, 1, 1, 6, 6, 1, 1, 2, 2, 3, 3, 3, 3, 1,
1, 6, 6, 1, 1, 1, 1, 2, 2, 8, 8, 3, 3, 1, 1, 6, 6, 1, 1,
2, 2, 3, 3, 3, 3, 1, 1, 6, 6, 1, 1, 1, 1, 2, 2, 8, 8, 3,
3, 1, 1, 6, 6, 1, 1, 2, 2
),
chr = c(
NA, NA, NA, NA, "1", NA, "1", NA, "2", NA, NA, NA, NA, "3", NA,
"3", "1", NA, NA, NA, "1", NA, NA, NA, NA, "3", NA, NA, NA, NA,
"1", NA, "1", NA, "2", NA, NA, NA, NA, "3", NA, "3", "1", NA, NA,
NA, "1", NA, NA, NA, NA, "3", NA, NA, "1", NA, NA, NA, NA, NA, NA,
NA, NA, "2", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, "1", NA, "1", NA, NA, NA, NA, NA, NA, NA, NA,
NA, "1", NA, NA, "1", "1", NA, NA, NA, NA, NA
),
integration_locus = c(
NA, NA, NA, NA, 12345, NA, 12345, NA, 54321, NA, NA,
NA, NA, 62135, NA, 62135, 12345, NA, NA, NA, 12345,
NA, NA, NA, NA, 62135, NA, NA, NA, NA, 12345, NA,
12345, NA, 54321, NA, NA, NA, NA, 62135, NA, 62135,
12345, NA, NA, NA, 12345, NA, NA, NA, NA, 62135, NA,
NA, 43524, NA, NA, NA, NA, NA, NA, NA, NA, 76835, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, 12345, NA, 12345, NA, NA, NA, NA, NA,
NA, NA, NA, NA, 12345, NA, NA, 56832, 12345, NA, NA,
NA, NA, NA
),
strand = c(
NA, NA, NA, NA, "+", NA, "+", NA, "-", NA, NA, NA, NA, "+", NA,
"+", "+", NA, NA, NA, "+", NA, NA, NA, NA, "+", NA, NA, NA, NA,
"+", NA, "+", NA, "-", NA, NA, NA, NA, "+", NA, "+", "+", NA,
NA, NA, "+", NA, NA, NA, NA, "+", NA, NA, "+", NA, NA, NA, NA,
NA, NA, NA, NA, "-", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, "+", NA, "+", NA, NA, NA, NA, NA, NA,
NA, NA, NA, "+", NA, NA, "-", "+", NA, NA, NA, NA, NA
),
sharing_perc = c(
0, 0, 0, 0, 50, 0, 50, 0, 100, 0, 0, 0, 0, 100, 0, 50,
100, 0, 0, 0, 100, 0, 0, 0, 0, 100, 0, 0, 0, 0, 50, 0, 50,
0, 100, 0, 0, 0, 0, 100, 0, 50, 100, 0, 0, 0, 100, 0, 0,
0, 0, 100, 0, 0, 100, 0, 0, 0, 0, 0, 0, 0, 0, 100, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 50, 0, 50,
0, 0, 0, 0, 0, 0, 0, 0, 0, 100, 0, 0, 100, 100, 0, 0, 0,
0, 0
)
) |> dplyr::arrange(.data$g1, .data$g2)
test_that("iss_source produces expected output - per patient", {
withr::local_options(list(
ISAnalytics.parallel_processing = FALSE
))
res <- iss_source(test_df2, test_df3) |>
purrr::map(~ dplyr::arrange(.x, .data$g1, .data$g2))
expect_equal(res, expected_res1)
})
test_that("iss_source produces expected output - NO per patient", {
withr::local_options(list(
ISAnalytics.parallel_processing = FALSE
))
res <- iss_source(test_df2, test_df3, by_subject = FALSE) |>
dplyr::arrange(.data$g1, .data$g2)
expect_equal(res, expected_res2)
})
#------------------------------------------------------------------------------#
# Test gene_frequency_fisher
#------------------------------------------------------------------------------#
test_that("gene_frequency_fisher produces expected output", {
withr::local_options(list(ISAnalytics.verbose = TRUE))
test_cis <- readRDS(fs::path(testdata_path, "test_cis_for_fisher.Rds"))
## -- Testing intersection
fisher_df <- gene_frequency_fisher(test_cis[[1]], test_cis[[2]],
min_is_per_gene = 1,
gene_set_method = "intersection"
)
common_genes <- intersect(test_cis$PT001$GeneName, test_cis$PT002$GeneName)
expect_true(all(fisher_df$GeneName %in% common_genes) &
all(common_genes %in% fisher_df$GeneName))
## -- Testing union
fisher_df <- gene_frequency_fisher(test_cis[[1]], test_cis[[2]],
min_is_per_gene = 1,
gene_set_method = "union",
remove_unbalanced_0 = FALSE
)
union_genes <- union(test_cis$PT001$GeneName, test_cis$PT002$GeneName)
expect_true(all(fisher_df$GeneName %in% union_genes) &
all(union_genes %in% fisher_df$GeneName))
## -- Testing default filtering
expect_message(
{
fisher_df <- gene_frequency_fisher(test_cis[[1]], test_cis[[2]],
min_is_per_gene = 3,
gene_set_method = "intersection"
)
},
class = "empty_df_gene_freq"
)
expect_null(fisher_df)
fisher_df <- gene_frequency_fisher(test_cis[[1]], test_cis[[2]],
min_is_per_gene = 3,
gene_set_method = "union"
)
expect_true(nrow(fisher_df) == 2)
})
#------------------------------------------------------------------------------#
# Test top_targeted_genes
#------------------------------------------------------------------------------#
test_that("top_targeted_genes produces expected output", {
annot_ex <- minimal_agg_example |>
dplyr::mutate(
GeneName = c(
"GENE1", "GENE1", "GENE1", "GENE2", "GENE2", "GENE3", "GENE4",
"GENE4", "GENE4"
),
GeneStrand = c("+", "+", "+", "-", "-", "-", "+", "+", "+"),
.after = "strand"
)
# --- top genes overall
top_5 <- top_targeted_genes(annot_ex, n = 5, key = NULL)
expected <- tibble::tibble(
GeneName = c("GENE1", "GENE2", "GENE1", "GENE3", "GENE4"),
GeneStrand = c("+", "-", "+", "-", "+"),
chr = c("2", "5", "1", "3", "10"),
n_IS = c(2, 2, 1, 1, 1)
)
expect_equal(top_5, expected)
top_5 <- top_targeted_genes(annot_ex,
n = 5, key = NULL,
consider_chr = FALSE
)
expected <- tibble::tibble(
GeneName = c("GENE1", "GENE4", "GENE2", "GENE3"),
GeneStrand = c("+", "+", "-", "-"),
n_IS = c(3, 3, 2, 1)
)
expect_equal(top_5, expected)
top_5 <- top_targeted_genes(annot_ex,
n = 5, key = NULL,
consider_chr = FALSE,
consider_gene_strand = FALSE
)
expected <- tibble::tibble(
GeneName = c("GENE1", "GENE4", "GENE2", "GENE3"),
n_IS = c(3, 3, 2, 1)
)
expect_equal(top_5, expected)
# --- top genes per group
top_5 <- top_targeted_genes(annot_ex,
n = 5,
key = c("SubjectID", "CellMarker")
)
expected <- tibble::tibble(
SubjectID = c("S1", "S1", "S1", "S2", "S2", "S2", "S2"),
CellMarker = c("CM1", "CM1", "CM1", "CM2", "CM2", "CM2", "CM2"),
GeneName = c(
"GENE1", "GENE2", "GENE1", "GENE3", "GENE4", "GENE4",
"GENE4"
),
GeneStrand = c("+", "-", "+", "-", "+", "+", "+"),
chr = c("2", "5", "1", "3", "3", "10", "11"),
n_IS = c(2, 2, 1, 1, 1, 1, 1)
)
top_5 <- top_targeted_genes(annot_ex,
n = 5,
key = c("SubjectID", "CellMarker"),
consider_chr = FALSE
)
expected <- tibble::tibble(
SubjectID = c("S1", "S1", "S2", "S2"),
CellMarker = c("CM1", "CM1", "CM2", "CM2"),
GeneName = c("GENE1", "GENE2", "GENE4", "GENE3"),
GeneStrand = c("+", "-", "+", "-"),
n_IS = c(3, 2, 3, 1)
)
})
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