-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathRcodes_EwS6pMSAT_Figures.R
332 lines (290 loc) · 13.8 KB
/
Rcodes_EwS6pMSAT_Figures.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
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
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
library(dplyr)
library("data.table")
library(stringr)
library(ggplot2)
library(tidyverse)
library("htmlwidgets")
#################
# Figures #
#################
ggplot(cohort.pattern.count, aes(x = hap, y = Freq, fill = color, group = rank))+
geom_bar(stat = "identity") +
ggtitle ("Microsatellites")+
xlab("microsatellite") +
ylab("microsatellite Pattern") +
geom_text(position = position_stack(vjust=0.5), aes(label = Freq), size=4) +
scale_fill_manual(values = c("AGAA" = "#ccebc5",
"GAAG" = "#fddaec",
"GAG_" = "#b3cde3" ,
"GAGG" = "#fbb4ae" ,
"GGA_" = "#fed9a6" ,
"GGAA" = "#fff2ae" ,
"GGAG" = "#decbe4" ,
"GGGA" = "#cccccc")) +
scale_y_continuous(expand = expansion(mult = c(0,0.1))) +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))
############### Flipped ###############
## Setting levles
cohort.pattern.count.v2 <- cohort.pattern.count
cohort.pattern.count.v2$hap <- factor(cohort.pattern.count.v2$hap, levels = unique(rev(as.character(cohort.pattern.count.v2$hap))))
cohort.pattern.count.v2$rank <- factor(cohort.pattern.count.v2$rank, levels = unique(rev(as.character(cohort.pattern.count.v2$rank))))
ggplot(cohort.pattern.count.v3, aes(x = hap, y = Freq, fill = color, group = rank))+
geom_bar(stat = "identity") +
# ggtitle ("Microsatellites")+
xlab("Microsatellite") +
ylab("Microsatellite Allele Length (bp)") +
geom_text(position = position_stack(vjust=0.5), aes(label = Freq/4), size=4) +
scale_fill_manual(values = c("AGAA" = "#ccebc5",
"GAAG" = "#fddaec",
"GAG_" = "#b3cde3" ,
"GAGG" = "#fbb4ae" ,
"GGA_" = "#fed9a6" ,
"GGAA" = "#fff2ae" ,
"GGAG" = "#decbe4" ,
"GGGA" = "#cccccc")) +
scale_y_continuous(expand = expansion(mult = c(0,0.1))) +
#theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1)) +
coord_flip() +
theme_bw() +
theme(panel.grid.minor = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.major = element_blank())
dev.off()
# **************************** #
# Motif Expansion Label #
# **************************** #
ggplot(cohort.pattern.count.v4, aes(x = hap, y = Freq, fill = expansion, group = rank))+
geom_bar(stat = "identity") +
xlab("Microsatellite") +
ylab("Microsatellite Allele Length (bp)") +
# geom_text(position = position_stack(vjust=0.5), aes(label = Freq), size=2) +
scale_fill_manual(values = c("GGAA expansion 1" = "#fff2b3",
"GGAA expansion 2" = "#ffee99",
"GGAA expansion 3" = "#ffea80" ,
"GGAA expansion 4" = "#ffe14d" ,
"AGAA expansion 1" = "#def2d9" ,
"AGAA expansion 2" = "#ccebc5" ,
"AGAA expansion 3" = "#9bd88d" ,
"GGGA expansion 1" = "#cccccc",
"GGGA expansion 2" = "#cccccc",
"other motifs" = "#fbb4ae")) +
scale_y_continuous(expand = expansion(mult = c(0,0.1))) +
#theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1)) +
coord_flip() +
theme_bw() +
theme(panel.grid.minor = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.major = element_blank())
dev.off()
# ************************ #
# Grouped Bar Plot #
# ************************ #
input.stackedplot6 <- mSat.information.v3 %>%
select(mSat_order, sequence, ews_allele, control_allele, mSat_length) %>%
arrange(desc(mSat_length)) %>%
select(mSat_order, ews_allele, control_allele)
dat.m3 <- melt(input.stackedplot6, id.vars = "mSat_order")
dat.m3$mSat_order = factor(dat.m3$mSat_order, input.order)
dat.m3$variable = factor(dat.m3$variable, c("control_allele", "ews_allele"))
ggplot(dat.m3, aes(fill=variable, y=value, x=mSat_order)) +
geom_bar(position="dodge", stat="identity", alpha = 1.0) +
scale_fill_brewer(palette="Paired") +
scale_y_continuous(expand = expansion(mult = c(0.01,0.01)), limits = c(0,100)) +
theme_bw() +
theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5),
panel.grid.minor = element_blank(), panel.grid.major.x = element_blank() ) +
# ggtitle ("Frequency of EwS case and control")+
xlab("Microsatellite") +
ylab("Allele Count")
# ************************************************** #
# Length of microsatellite with the odds of EWS #
# ************************************************** #
### Using geom_point (better) -USE THIS
df <- mSat.information.v3 %>% select(mSat_length, ews_prop, ews_allele, mSat_status, total_allele, GGAAcounts, GGAA_block34)
View(df)
df$ews_percent <- df$ews_prop*100
df$ews_allele_percent <- (df$ews_allele/542)*100
sum(df$total_allele)
df$total_allele_percent <- (df$total_allele/770)*100
df$odds <- (df$ews_allele)/(df$total_allele-df$ews_allele)
### To add a trend line
require(stats)
reg <-lm(ews_percent ~ mSat_length, data = df)
reg
#reg2 <-lrm(ews_percent ~ mSat_length, data = df)
coeff=coefficients(reg)
# Equation of the line :
eq = paste0("y = ", round(coeff[2],1), "*x + ", round(coeff[1],1))
### Plotting
ggplot(df, aes(mSat_length, ews_percent, size = ews_allele_percent*5)) +
geom_point(alpha = 0.5) +
theme_bw() +
theme(panel.grid.major.x = element_blank()) +
xlab("Length of Microsatellie (bp)") +
ylab("Percetage of EwS in Allele") +
labs(size = "Frequency of Allele")
# scale_color_gradient(low="#4eb3d3", high="#081d58")
# *********************************** #
# mSat only in case and control #
# *********************************** #
msat.control <- setdiff(overall.control$mSat_order, overall.case$mSat_order)
msat.case <- setdiff(overall.case$mSat_order, overall.control$mSat_order)
##### CASE
View(cohort.pattern.count.v2)
cohort.pattern.count.v2$hap <- gsub("mSat", "Allele ", cohort.pattern.count.v2$hap)
msat.case <- gsub("mSat", "Allele ", msat.case)
msat.case
cohort.pattern.count.v2$hap <- factor(cohort.pattern.count.v2$hap, levels = unique(rev(as.character(cohort.pattern.count.v4$hap))))
cohort.pattern.count.v2$rank <- factor(cohort.pattern.count.v2$rank, levels = unique(rev(as.character(cohort.pattern.count.v4$rank))))
EWS.only.pattern.count <- cohort.pattern.count.v2 %>% filter(hap %in% msat.case)
ggplot(EWS.only.pattern.count, aes(x = `hap_Allele_w/o space`, y = Freq, fill = color, group = rank))+
geom_bar(stat = "identity") +
ggtitle ("Microsatellite alleles found only in EwS cases")+
xlab("Microsatellite") +
ylab("Microsatellite Length") +
geom_text(position = position_stack(vjust=0.5), aes(label = Freq), size=4) +
scale_fill_manual(values = c("AGAA" = "#ccebc5",
"GAAG" = "#fddaec",
"GAG_" = "#b3cde3" ,
"GAGG" = "#fbb4ae" ,
"GGA_" = "#fed9a6" ,
"GGAA" = "#fff2ae" ,
"GGAG" = "#decbe4" ,
"GGGA" = "#cccccc")) +
scale_y_continuous(limits = c(0, 160), expand = expansion(mult = c(0,0.1))) +
theme_bw()+
coord_flip() +
theme(panel.grid.minor = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.major = element_blank())
##### CONTROL
msat.control <- gsub("mSat", "Allele ", msat.control)
control.only.pattern.count <- cohort.pattern.count.v2 %>% filter(hap %in% msat.control)
View(control.only.pattern.count)
ggplot(control.only.pattern.count, aes(x = `hap_Allele_w/o space`, y = Freq, fill = color, group = rank))+
geom_bar(stat = "identity") +
ggtitle ("Microsatellite alleles found only in controls")+
xlab("Microsatellite") +
ylab("Microsatellite Length") +
geom_text(position = position_stack(vjust=0.5), aes(label = Freq), size=4) +
scale_fill_manual(values = c("AGAA" = "#ccebc5",
"GAAG" = "#fddaec",
"GAG_" = "#b3cde3" ,
"GAGG" = "#fbb4ae" ,
"GGA_" = "#fed9a6" ,
"GGAA" = "#fff2ae" ,
"GGAG" = "#decbe4" ,
"GGGA" = "#cccccc")) +
scale_y_continuous(limits = c(0, 160), expand = expansion(mult = c(0,0.1))) +
theme_bw()+
coord_flip() +
theme(panel.grid.minor = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.major = element_blank())
# *********************************** #
# Gviz - Visualize genomic data #
# *********************************** #
library(Gviz)
library(GenomicRanges)
grtrack <- GeneRegionTrack(hg19.ncbiRefSeq.chr6.v6, genome = test.gen,
chromosome = chr, name = "Gene Model",
transcriptAnnotation = "symbol",
background.panel = "#FFFEDB",
background.title = "darkblue")
### Adding DNA bases
library(BSgenome.Hsapiens.UCSC.hg19)
strack <- SequenceTrack(Hsapiens, chromosome = chr)
plotTracks(list(test.itrack, gtrack, grtrack, strack), from = 4000000, to = 9000000, cex = 0.8)
final.fig <- plotTracks(list(test.itrack, gtrack, grtrack, strack, dTrack), from = 6300000, to = 7500000, cex = 0.8, type = "histogram")
# ******************************************************* #
# Suuplemetary Figure: Each motif count in each mSat #
# ******************************************************* #
View(mSat.information.v3)
# ***************#
# GGAA count #
# ***************#
### only GGAA counts
input.stackedplot.GGAA <- mSat.information.v3 %>%
select(mSat_order, mSat_length, GGAAcounts) %>%
arrange(desc(mSat_length)) %>%
select(!mSat_length)
input.stackedplot.GGAA$mSat_order <- gsub("mSat", "Allele ", input.stackedplot.GGAA$mSat_order)
input.order <- gsub("mSat", "Allele ", input.order)
input.stackedplot.GGAA$mSat_order = factor(input.stackedplot.GGAA$mSat_order, input.order)
View(input.stackedplot.GGAA)
ggplot(input.stackedplot.GGAA, aes(y=GGAAcounts, x=reorder(mSat_order, desc(mSat_order)))) +
geom_bar(stat="identity", alpha = 1.0) +
scale_y_continuous(expand = expansion(mult = c(0.01,0.01)), limits = c(0,35)) +
theme_bw() +
theme(panel.grid.minor = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.major = element_blank()) +
coord_flip() +
xlab("Microsatellite") +
ylab("Number of GGAA motif")
### only AGAA counts
input.stackedplot.AGAA <- mSat.information.v3 %>%
select(mSat_order, AGAAcounts)
input.stackedplot.AGAA$mSat_order <- gsub("mSat", "Allele ", input.stackedplot.AGAA$mSat_order)
input.stackedplot.AGAA$mSat_order = factor(input.stackedplot.AGAA$mSat_order, input.order)
View(input.stackedplot.AGAA)
ggplot(input.stackedplot.AGAA, aes(y=AGAAcounts, x=reorder(mSat_order, desc(mSat_order)))) +
geom_bar(stat="identity", alpha = 1.0) +
scale_y_continuous(expand = expansion(mult = c(0.01,0.01)), limits = c(0,35)) +
theme_bw() +
theme(panel.grid.minor = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.major = element_blank()) +
coord_flip() +
xlab("Microsatellite") +
ylab("Number of AGAA motif")
### only GGGA counts
input.stackedplot.GGGA <- mSat.information.v3 %>%
select(mSat_order, GGGAcounts)
input.stackedplot.GGGA$mSat_order <- gsub("mSat", "Allele ", input.stackedplot.GGGA$mSat_order)
input.stackedplot.GGGA$mSat_order = factor(input.stackedplot.GGGA$mSat_order, input.order)
View(input.stackedplot.GGGA)
ggplot(input.stackedplot.GGGA, aes(y=GGGAcounts, x=reorder(mSat_order, desc(mSat_order)))) +
geom_bar(stat="identity", alpha = 1.0) +
scale_y_continuous(expand = expansion(mult = c(0.01,0.01)), limits = c(0,35)) +
theme_bw() +
theme(panel.grid.minor = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.major = element_blank()) +
coord_flip() +
xlab("Microsatellite") +
ylab("Number of GGGA motif")
######################################################
# Supp Fig# - 3 SNPs haplotype and GGAA count #
######################################################
### Counts with GGAA freq
df.aligned.patternCounts.v9$rep_pattern <- gsub("_", "", df.aligned.patternCounts.v9$pattern1)
ggplot(df.aligned.patternCounts.v9, aes(x=rep_pattern, y=freq_GGAA)) +
geom_violin(trim = FALSE) +
geom_jitter(position=position_jitter(0.05), alpha = 0.7, aes(colour = Disease.Group)) +
scale_color_manual(values=c("#ff6666", "#00CC99")) +
xlab("Haplotype") +
ylab("GGAA motif count") +
labs(color = "EwS status") +
ylim(5,40) +
theme_bw() +
theme(panel.grid.minor = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.major = element_blank())
df.aligned.patternCounts.v10$rep_pattern <- factor(df.aligned.patternCounts.v9$rep_pattern,
levels = c("ATT", "ATC", "AGT", "GTT", "GTC", "GGC", "GGT"))
ggplot(df.aligned.patternCounts.v10, aes(x=rep_pattern, y=freq_GGAA)) +
geom_violin(trim = FALSE) +
geom_jitter(position=position_jitter(0.05), alpha = 0.7, aes(colour = Disease.Group)) +
scale_color_manual(values=c("#ff6666", "#00CC99")) +
xlab("Haplotype") +
ylab("GGAA motif count") +
labs(color = "EwS status") +
ylim(5,40) +
theme_bw() +
theme(panel.grid.minor = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.major = element_blank())
############################################################################
# Please contact Olivia Lee (olivia.lee@nih.gov) if you have any questions about the codes and details.
############################################################################