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grlloydgrlloyd
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improve testing for fold change
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‎tests/testthat/test-foldchange.R

Lines changed: 98 additions & 61 deletions
Original file line numberDiff line numberDiff line change
@@ -1,64 +1,101 @@
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# fold_change
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test_that('fold_change',{
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set.seed('57475')
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# data
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D = iris_DatasetExperiment()
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# two groups
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F = filter_smeta(mode='exclude',levels='setosa',factor_name='Species')
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F = model_apply(F,D)
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D = predicted(F)
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# add column for paired data
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D$sample_meta$sample_id=c(1:50,1:50)
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D$data[1:50,2] = NA
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D$data[1:25,3] = NA
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# unpaired
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FF = fold_change(factor_name='Species',method="geometric",control_group='versicolor')
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FF = model_apply(FF,D)
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m=exp(mean(log(D$data[D$sample_meta$Species=='virginica',1]))) / exp(mean(log((D$data[D$sample_meta$Species=='versicolor',1]))))
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expect_equal(FF$fold_change[1,1],m,tolerance=0.00001)
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expect_true(is.na(FF$fold_change[2,1]))
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m=exp(mean(log(na.exclude(D$data[D$sample_meta$Species=='virginica',3])))) / exp(mean(log(na.exclude(D$data[D$sample_meta$Species=='versicolor',3]))))
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expect_equal(FF$fold_change[3,1],m,tolerance=0.00001)
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FF$method = 'median'
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FF = model_apply(FF,D)
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m = median(D$data[D$sample_meta$Species=='virginica',1]) / median(D$data[D$sample_meta$Species=='versicolor',1])
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expect_equal(FF$fold_change[1,1],m,tolerance=0.00001)
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expect_true(is.na(FF$fold_change[2,1]))
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m = median(D$data[D$sample_meta$Species=='virginica',3],na.rm = TRUE) / median(D$data[D$sample_meta$Species=='versicolor',3],na.rm = TRUE)
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expect_equal(FF$fold_change[3,1],m,tolerance=0.00001)
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FF$method = 'mean'
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FF = model_apply(FF,D)
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m = mean(D$data[D$sample_meta$Species=='virginica',1]) / mean(D$data[D$sample_meta$Species=='versicolor',1])
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expect_equal(FF$fold_change[1,1],m,tolerance=0.00001)
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expect_true(is.na(FF$fold_change[2,1]))
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m = mean(D$data[D$sample_meta$Species=='virginica',3],na.rm=TRUE) / mean(D$data[D$sample_meta$Species=='versicolor',3],na.rm=TRUE)
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expect_equal(FF$fold_change[3,1],m,tolerance=0.00001)
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# paired
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FF = fold_change(factor_name='Species',method="geometric",paired=TRUE,sample_name = 'sample_id')
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FF = model_apply(FF,D)
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m=exp(mean(log(D$data[D$sample_meta$Species=='virginica',1])-log(D$data[D$sample_meta$Species=='versicolor',1])))
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expect_equal(FF$fold_change[1,1],m,tolerance=0.00001)
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expect_true(is.na(FF$fold_change[2,1]))
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FF$method = 'median'
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FF = model_apply(FF,D)
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m = median(D$data[D$sample_meta$Species=='virginica',1] / D$data[D$sample_meta$Species=='versicolor',1])
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expect_equal(FF$fold_change[1,1],m,tolerance=0.00001)
55-
expect_true(is.na(FF$fold_change[2,1]))
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FF$method = 'mean'
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FF = model_apply(FF,D)
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m = mean(D$data[D$sample_meta$Species=='virginica',1] / D$data[D$sample_meta$Species=='versicolor',1])
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expect_equal(FF$fold_change[1,1],m,tolerance=0.00001)
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expect_true(is.na(FF$fold_change[2,1]))
621

632

3+
test_that('fold_change unpaired',{
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set.seed('57475')
5+
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# data
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D = iris_DatasetExperiment()
8+
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# add some missing values
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D$data[1:50,2] = NA
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D$data[1:25,3] = NA
12+
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# unpaired
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FF = fold_change(factor_name='Species',method="geometric",control_group='versicolor')
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FF = model_apply(FF,D)
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# check some fold changes
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m=exp(mean(log(na.exclude(D$data[D$sample_meta$Species=='virginica',1])))) / exp(mean(log(na.exclude(D$data[D$sample_meta$Species=='versicolor',1]))))
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expect_equal(FF$fold_change$`virginica/versicolor`[1],m,tolerance=0.00001)
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m=exp(mean(log(na.exclude(D$data[D$sample_meta$Species=='setosa',4])))) / exp(mean(log(na.exclude(D$data[D$sample_meta$Species=='versicolor',4]))))
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expect_equal(FF$fold_change$`setosa/versicolor`[4],m,tolerance=0.00001)
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m=exp(mean(log(na.exclude(D$data[D$sample_meta$Species=='virginica',3])))) / exp(mean(log(na.exclude(D$data[D$sample_meta$Species=='setosa',3]))))
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expect_equal(FF$fold_change$`virginica/setosa`[3],m,tolerance=0.00001)
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# check some NA
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expect_true(is.na(FF$fold_change$`virginica/setosa`[2]))
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expect_true(is.na(FF$fold_change$`setosa/versicolor`[2]))
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FF$method = 'median'
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FF = model_apply(FF,D)
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# check some fold changes
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m = median(D$data[D$sample_meta$Species=='virginica',1],na.rm = TRUE) / median(D$data[D$sample_meta$Species=='versicolor',1],na.rm = TRUE)
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expect_equal(FF$fold_change$`virginica/versicolor`[1],m,tolerance=0.00001)
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36+
m = median(D$data[D$sample_meta$Species=='setosa',4],na.rm = TRUE) / median(D$data[D$sample_meta$Species=='versicolor',4],na.rm = TRUE)
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expect_equal(FF$fold_change$`setosa/versicolor`[4],m,tolerance=0.00001)
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m = median(D$data[D$sample_meta$Species=='virginica',3],na.rm = TRUE) / median(D$data[D$sample_meta$Species=='setosa',3],na.rm = TRUE)
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expect_equal(FF$fold_change$`virginica/setosa`[3],m,tolerance=0.00001)
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# check some NA
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expect_true(is.na(FF$fold_change$`virginica/setosa`[2]))
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expect_true(is.na(FF$fold_change$`setosa/versicolor`[2]))
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FF$method = 'mean'
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FF = model_apply(FF,D)
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m = mean(D$data[D$sample_meta$Species=='virginica',1],na.rm = TRUE) / mean(D$data[D$sample_meta$Species=='versicolor',1],na.rm = TRUE)
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expect_equal(FF$fold_change$`virginica/versicolor`[1],m,tolerance=0.00001)
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51+
m = mean(D$data[D$sample_meta$Species=='setosa',4],na.rm = TRUE) / mean(D$data[D$sample_meta$Species=='versicolor',4],na.rm = TRUE)
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expect_equal(FF$fold_change$`setosa/versicolor`[4],m,tolerance=0.00001)
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54+
m = mean(D$data[D$sample_meta$Species=='virginica',3],na.rm = TRUE) / mean(D$data[D$sample_meta$Species=='setosa',3],na.rm = TRUE)
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expect_equal(FF$fold_change$`virginica/setosa`[3],m,tolerance=0.00001)
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57+
# check some NA
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expect_true(is.na(FF$fold_change$`virginica/setosa`[2]))
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expect_true(is.na(FF$fold_change$`setosa/versicolor`[2]))
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61+
6462
})
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64+
test_that('fold_change paired',{
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set.seed('57475')
66+
67+
# data
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D = iris_DatasetExperiment()
69+
70+
# two groups
71+
F = filter_smeta(mode='exclude',levels='setosa',factor_name='Species')
72+
F = model_apply(F,D)
73+
74+
D = predicted(F)
75+
76+
# add column for paired data
77+
D$sample_meta$sample_id=c(1:50,1:50)
78+
D$data[1:50,2] = NA
79+
D$data[1:25,3] = NA
80+
81+
# paired
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FF = fold_change(factor_name='Species',method="geometric",paired=TRUE,sample_name = 'sample_id',control_group = 'versicolor')
83+
FF = model_apply(FF,D)
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m=exp(mean(log(D$data[D$sample_meta$Species=='virginica',1])-log(D$data[D$sample_meta$Species=='versicolor',1])))
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expect_equal(FF$fold_change[1,1],m,tolerance=0.00001)
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expect_true(is.na(FF$fold_change[2,1]))
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88+
FF$method = 'median'
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FF = model_apply(FF,D)
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m = median(D$data[D$sample_meta$Species=='virginica',1] / D$data[D$sample_meta$Species=='versicolor',1])
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expect_equal(FF$fold_change[1,1],m,tolerance=0.00001)
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expect_true(is.na(FF$fold_change[2,1]))
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FF$method = 'mean'
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FF = model_apply(FF,D)
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m = mean(D$data[D$sample_meta$Species=='virginica',1] / D$data[D$sample_meta$Species=='versicolor',1])
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expect_equal(FF$fold_change[1,1],m,tolerance=0.00001)
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expect_true(is.na(FF$fold_change[2,1]))
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})

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