1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
|
# This tests the correctGroupSummary function.
# library(testthat); library(scuttle); source("test-correct-summary.R")
library(scuttle)
test_that("correctGroupSummary works correctly in raw mode", {
# No batches.
y <- matrix(rnorm(1000), ncol=100)
group <- rep(1:10, each=10)
block <- rep('all', ncol(y))
averaged <- correctGroupSummary(y, group, block)
ref <- sumCountsAcrossCells(y, group, average=TRUE)
expect_equal(averaged, assay(ref))
averaged <- correctGroupSummary(y, group, block=NULL) # same with NULL.
expect_equal(averaged, assay(ref))
# Perfectly balanced.
y <- matrix(rnorm(1000), ncol=100)
group <- rep(1:10, each=10)
block <- rep(1:10, 10)
averaged <- correctGroupSummary(y, group, block)
ref <- sumCountsAcrossCells(y, group, average=TRUE)
ref <- assay(ref)
ref2 <- ref - rowMeans(ref)
averaged2 <- averaged - rowMeans(averaged)
expect_equal(ref2, averaged2)
# Effectively ignores batches with only one cluster.
y <- matrix(rnorm(210), ncol=21)
group <- c(1:10, 1:10, 1)
block <- rep(1:3, c(10, 10, 1))
averaged <- correctGroupSummary(y, group, block)
averaged2 <- correctGroupSummary(y[,-21], group[-21], block[-21])
expect_equal(averaged, averaged2)
# Handles batch-specific clusters.
y <- matrix(rnorm(220), ncol=22)
group <- c(1:10, 1:10, c(1,11))
block <- rep(1:3, c(10, 10, 2))
averaged <- correctGroupSummary(y, group, block)
expect_identical(sum(!colAnyNAs(averaged)), 11L)
})
test_that("correctGroupSummary works with weights", {
y <- matrix(rnorm(1000), ncol=100)
group <- rep(1:10, each=10)
block <- rep(1:10, 10)
w <- sample(2, ncol(y), replace=TRUE)
out <- correctGroupSummary(y, group, block, weights=w)
expander <- rep(seq_along(w), w)
ref <- correctGroupSummary(y[,expander], group[expander], block[expander])
expect_equal(out, ref)
})
test_that("correctGroupSummary handles subsetting", {
y <- matrix(rnorm(1000), ncol=100)
group <- factor(rep(1:10, each=10))
block <- rep(1:10, 10)
# Subset.row gives the same results.
sub <- sample(nrow(y), 10)
ref <- correctGroupSummary(y, group, block, subset.row=sub)
out <- correctGroupSummary(y[sub,,drop=FALSE], group, block)
expect_identical(ref, out)
# Handles the special one-gene case.
ref <- correctGroupSummary(y, group, block)
out <- correctGroupSummary(y[1,,drop=FALSE], group, block)
expect_identical(ref[1,,drop=FALSE], out)
w <- runif(100)
ref <- correctGroupSummary(y, group, block, weights=w)
out <- correctGroupSummary(y[1,,drop=FALSE], group, block, weights=w)
expect_identical(ref[1,,drop=FALSE], out)
})
test_that("correctGroupSummary respects factor ordering", {
y <- matrix(rnorm(1000), ncol=100)
group <- factor(rep(1:10, each=10), 10:1)
block <- rep(1:10, 10)
out <- correctGroupSummary(y, group, block)
expect_identical(colnames(out), as.character(10:1))
ref <- correctGroupSummary(y, as.character(group), block)
expect_equal(out, ref[,colnames(out)])
})
test_that("correctGroupSummary works correctly in log mode", {
# Actually has an effect.
y <- matrix(rexp(1000), ncol=100)
group <- rep(1:10, each=10)
block <- rep('all', ncol(y))
averaged1 <- correctGroupSummary(y, group, block)
averaged2 <- correctGroupSummary(y, group, block, transform="log")
expect_false(identical(averaged1, averaged2))
# Survives a round trip with correct untransformation.
y <- matrix(rexp(1000), ncol=10)
group <- 1:10
block <- rep('all', ncol(y))
averaged <- correctGroupSummary(y, group, block, transform="log")
expect_equivalent(averaged, y)
# Handles zeroes.
y <- matrix(0, ncol=100, nrow=10)
group <- rep(1:10, each=10)
block <- rep('all', ncol(y))
averaged <- correctGroupSummary(y, group, block, transform="log")
expect_true(all(averaged==0))
})
test_that("correctGroupSummary works correctly in logit mode", {
# Actually has an effect.
y <- matrix(runif(1000), ncol=100)
group <- rep(1:10, each=10)
block <- rep('all', ncol(y))
averaged1 <- correctGroupSummary(y, group, block)
averaged2 <- correctGroupSummary(y, group, block, transform="log")
averaged3 <- correctGroupSummary(y, group, block, transform="logit")
expect_false(identical(averaged1, averaged3))
expect_false(identical(averaged2, averaged3))
# Survives a round trip with correct untransformation.
y <- matrix(runif(1000), ncol=10)
group <- 1:10
block <- rep('all', ncol(y))
averaged <- correctGroupSummary(y, group, block, transform="logit")
expect_equivalent(averaged, y)
# Handles boundaries.
y <- matrix(0, ncol=100, nrow=10)
group <- rep(1:10, each=10)
block <- rep('all', ncol(y))
averaged <- correctGroupSummary(y, group, block, transform="logit")
expect_true(all(abs(averaged) < 1e-10))
y <- matrix(1, ncol=100, nrow=10)
averaged <- correctGroupSummary(y, group, block, transform="logit")
expect_true(all(averaged==1))
})
|
