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
|
library(tidyverse)
library(ggpubr)
data <- read_csv("../csv/data_per_assay_per_year_per_outcome.csv")
studies_data <- read_csv("../csv/donors_list.csv") %>%
group_by(study_id) %>%
summarise(
count = n()
)
tbl <- data %>%
mutate(
assay_type = factor(assay, labels = (
c(
"MSD",
"Multiplex cytokine",
"Cell Cytometry",
"Multiplex cytokine",
"Phospho cytometry",
"Cell Cytometry",
"Phospho cytometry",
"Complete blood count",
"MSD",
"Cell Cytometry",
"MSD",
"Multiplex cytokine",
"Multiplex cytokine",
"Cell Cytometry"
)
))
)
id_plt <- tbl %>%
group_by(year, assay, outcome) %>%
summarise(
measurements = n(),
study = study
) %>%
ggplot(aes(year, measurements / 1000, color = factor(assay))) +
geom_line() +
geom_point() +
ylim(-1, 10) +
facet_grid(rows = vars(factor(outcome, labels = c("low", "high")))) +
labs(y = "number of features (thousands)") +
scale_color_discrete(name="Assay type") +
theme_pubclean()
type_plt <- tbl %>%
group_by(year, assay_type, outcome) %>%
summarise(
measurements = n(),
study = study
) %>%
ggplot(aes(year, measurements / 1000, color = factor(assay_type))) +
geom_line(show.legend=F) +
geom_point(show.legend=F) +
ylim(-1, 10) +
facet_grid(rows = vars(factor(outcome, labels = c("low", "high")))) +
labs(y = "number of features (thousands)") +
scale_color_discrete(name="Assay type") +
theme_pubclean()
study_plt <- tbl %>%
group_by(year, assay_type) %>%
summarise(
measurements = n(),
study = study
) %>%
ggplot(aes(year, measurements / 1000, color = factor(assay_type))) +
geom_line() +
geom_point() +
ylim(-1, 10) +
facet_grid(rows = vars(factor(study, labels = c(
paste("SLVP015\nn=(", as.numeric(studies_data[studies_data$study_id == 15,][2]), ")"),
paste("SLVP017\nn=(", as.numeric(studies_data[studies_data$study_id == 17,][2]), ")"),
paste("SLVP018\nn=(", as.numeric(studies_data[studies_data$study_id == 18,][2]), ")"),
paste("SLVP021\nn=(", as.numeric(studies_data[studies_data$study_id == 21,][2]), ")"),
paste("SLVP024\nn=(", as.numeric(studies_data[studies_data$study_id == 24,][2]), ")"),
paste("SLVP028\nn=(", as.numeric(studies_data[studies_data$study_id == 28,][2]), ")"),
paste("SLVP029\nn=(", as.numeric(studies_data[studies_data$study_id == 29,][2]), ")"),
paste("SLVP030\nn=(", as.numeric(studies_data[studies_data$study_id == 30,][2]), ")")
)))) +
labs(y = "number of features (thousands)", legend="Assay type") +
scale_color_discrete(name="Assay type") +
theme_pubclean()
top_half <- ggarrange(
id_plt,
type_plt,
ncol=2,
labels = c("A","B")
)
whole <- ggarrange(
top_half,
study_plt,
nrow=2,
labels=c("", "C"),
heights = c(1,2)
)
whole
ggsave("../images/exp_data_numbers.pdf", whole, width = 21, height = 29.7, dpi=300, units = "cm")
|
