-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathtesting_Laila_Code.R
106 lines (80 loc) · 3.91 KB
/
testing_Laila_Code.R
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
## testing measurements
setwd("~/Documents/GitHub/Trident/results_organoids/")
setwd("/Volumes/FateTrack_2021/FateTrack_v2/select_data/LailaTests/data_0527_5dil/")
library(ggplot2)
fillist = list.files(path = "./",recursive = T, pattern = "yfp_measurements.csv")
measures_yfp = data.frame()
for (i in fillist){
temp = read.csv(i )
temp$yfpfile = i
measures_yfp = rbind(measures_yfp,temp)
}
measures_yfp$X = 1:nrow(measures_yfp)
measures_yfp = measures_yfp[!(colnames(measures_yfp)%in%(c("label","centroid.0","centroid.1")))]
fillist = list.files(path = "./",recursive = T, pattern = "cy5_measurements.csv")
measures_cy5 = data.frame()
for (i in fillist){
temp = read.csv(i )
temp$cy5file = i
measures_cy5 = rbind(measures_cy5,temp)
}
measures_cy5$X = 1:nrow(measures_cy5)
measures_cy5 = measures_cy5[!(colnames(measures_cy5)%in%(c("label","centroid.0","centroid.1")))]
fillist = list.files(path = "./",recursive = T, pattern = "cy3_measurements.csv")
measures_cy3 = data.frame()
for (i in fillist){
temp = read.csv(i )
temp$cy5file = i
measures_cy3 = rbind(measures_cy3,temp)
}
measures_cy3$X = 1:nrow(measures_cy3)
measures_cy3 = measures_cy3[!(colnames(measures_cy3)%in%(c("label","centroid.0","centroid.1")))]
mergeMeasure = merge(merge(measures_cy5, measures_yfp,by="X"),measures_cy3,by="X")
changeBounds=function(vec,log2_transform = T){
if(log2_transform ){
vec = log2(vec)
}
maxV = max(vec)
minV = min(vec)
slope = 1/(maxV-minV)
yInt = -1*slope*minV
return(slope*vec+yInt)
}
pol = log2(mergeMeasure$yfp_mean_intensity)
plot(changeBounds(mergeMeasure$cy3_mean_intensity,T),changeBounds(mergeMeasure$cy3_mean_intensity,T))
quantile(changeBounds(mergeMeasure$cy3_mean_intensity,T),probs = seq(0,1,1/5))
mergeMeasure$cy5_scale = changeBounds(mergeMeasure$cy5_mean_intensity,T)
mergeMeasure$cy3_scale = changeBounds(mergeMeasure$cy3_mean_intensity,T)
mergeMeasure$yfp_scale = changeBounds(mergeMeasure$yfp_mean_intensity,T)
mergeMeasure$rad = sqrt((mergeMeasure$yfp_scale)**2+(mergeMeasure$cy3_scale)**2+(mergeMeasure$cy5_scale)**2)
q <- quantile(mergeMeasure$rad,probs = seq(0,1,(10)**-1))
mergeMeasure$group <- cut(mergeMeasure$rad, q, include.lowest=TRUE,
labels=1:(length(q)-1))
samplingDensity = round(sqrt(diff(q))/max(sqrt(diff(q)))*75)
samplingNum = table(mergeMeasure$group)
library(dplyr)
superSelect = c()
for (i in 1:10){
tmp = mergeMeasure[mergeMeasure$group == i,]
tmpSize = round(as.numeric(samplingDensity)[i]/100*as.numeric(table(mergeMeasure$group)[i]))
rowSelect = sample(1:nrow(tmp),tmpSize,replace = F)
tmp$trainingInclude = (1:nrow(tmp))%in%rowSelect
superSelect = rbind(superSelect,tmp)
}
ggplot(superSelect[!superSelect$trainingInclude,])+geom_hex(aes(cy3_scale,yfp_scale))+scale_x_continuous(limits = c(0,1.1))+scale_y_continuous(limits = c(0,1.1))+scale_fill_gradient(low = "darkgrey",high = "orange")+theme_dark()
ggplot(superSelect)+geom_hex(aes(cy3_scale,yfp_scale))+scale_x_continuous(limits = c(0,1.1))+scale_y_continuous(limits = c(0,1.1))+scale_color_continuous()+scale_fill_gradient(low = "darkgrey",high = "orange")+theme_dark()
sample(mergeMeasure[mergeMeasure$group == 1,],replace = F,
as.numeric(samplingDensity)[1]/100*as.numeric(table(mergeMeasure$group)[1]))
mergeMeasure$cy3_scale = scale(log2(mergeMeasure$cy3_mean_intensity))
(abs(min(mergeMeasure$cy3_scale)/max(mergeMeasure$cy3_scale))*mergeMeasure$cy3_scale)-1
ggplot(mergeMeasure, aes(log2(cy3_mean_intensity), log2(cy5_mean_intensity)))+
geom_point(alpha = 0.5,col="white")+
#scale_x_log10()+ scale_y_log10()+
theme_dark()
ggplot(mergeMeasure, aes(cy3_scale))+
geom_histogram(alpha = 0.5,col="white",binwidth =.1)
newFile = mergeMeasure[mergeMeasure$cy5file == unique(mergeMeasure$cy5file)[4],]
ggplot(newFile,aes(centroid.1,-centroid.0))+
geom_point(aes(col=cy5_mean_intensity))+
scale_color_gradient(low = "blue",high = "yellow")+
theme_dark()+theme(legend.position = "none")