-
Notifications
You must be signed in to change notification settings - Fork 0
/
cummerbund.R
388 lines (376 loc) · 14.6 KB
/
cummerbund.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
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
rm(list=ls())
library(cummeRbund)
#-------------------------------
#read cufflinks files
#-------------------------------
setwd("/home/suresh/rnaseq/MeOH_R3G_cuffdiffout")
getwd()
cuff<-readCufflinks(gtfFile="../MeOH_R3G_cuffcompare_out/cuffcompare.combined.gtf", genome="hg19", rebuild=T)
#------------------------------
#Information about data
#-------------------------------
runInfo(cuff)
replicates(cuff)
sample.names<-samples(genes(cuff))
###############All genes/isoforms/TSS/CDS operations#########################
#-----------------------------
#Calculate fpkm density distribution for genes for each group
#-----------------------------
g.dens<-csDensity(genes(cuff))
#-----------------------------
#Calculate fpkm density distribution for genes in each replicate in each group
#-----------------------------
r.g.dens<-csDensity(genes(cuff),replicates=T)
#-----------------------------
#Extract annotations for genes in cuff class
#-----------------------------
annot.g.c<-annotation(genes(cuff))
head(annot.g.c)
#-----------------------------
#Extract FPKM values for genes in cuff class
#-----------------------------
fpkm.g<-fpkm(genes(cuff))
head(gene.fpkm)
#-----------------------------
#Extract FPKM values for isoforms in cuff class
#-----------------------------
fpkm.iso<-fpkm(isoforms(cuff))
head(fpkm.iso)
#-----------------------------
#Extract replicate FPKM values for genes in cuff class
#-----------------------------
r.gene.repFpkm<-repFpkm(genes(cuff))
head(gene.repFpkm)
#-----------------------------
#Extract gene counts in cuff class
#-----------------------------
gene.counts<-count(genes(cuff))
head(gene.counts)
#-----------------------------
# Extract differntially regulated genes in cuff class
#-----------------------------
gene.diff<-diffData(genes(cuff))
head(gene.diff)
#--------------------------------------------------
# Extract features available for genes in cuff class db
#--------------------------------------------------
gene.featurenames<-featureNames(genes(cuff))
head(gene.featurenames)
#--------------------------------------------------
# Extract gene fpkm and store it as a matrix for all groups
#--------------------------------------------------
gene.matrix<-fpkmMatrix(genes(cuff))
head(gene.matrix)
#--------------------------------------------------
# Extract gene fpkm and store it as a matrix for all replicates in groups
#--------------------------------------------------
gene.rep.matrix<-repFpkmMatrix(genes(cuff))
head(gene.rep.matrix)
#--------------------------------------------------
# Extract normalized counts for genes and store as a matrix for all groups
#--------------------------------------------------
gene.count.matrix<-countMatrix(genes(cuff))
head(gene.count.matrix)
###############Plots and images##########################
#--------------------------------------------------
# Calculate heatmap distance for all the genes
#--------------------------------------------------
DistHeat<-csDistHeat(genes(cuff))
print(DistHeat)
#--------------------------------------------------
# Calculate heatmap distance for all the genes for all replicates
#--------------------------------------------------
RepDistHeat<-csDistHeat(genes(cuff),replicates=T)
print(RepDistHeat)
#--------------------------------------------------
# Plot component 1 and 2 in PCA plot for the genes
#--------------------------------------------------
genes.PCA<-PCAplot(genes(cuff),"PC1","PC2")
print(genes.PCA)
#--------------------------------------------------
# Plot component 1 and 2 in PCA plot for the genes for all the replicates
#--------------------------------------------------
genes.PCA.rep<-PCAplot(genes(cuff),"PC1","PC2",replicates=T)
print(genes.PCA.rep)
#--------------------------------------------------
# MDS Plot for the genes
#--------------------------------------------------
genes.MDS<-MDSplot(genes(cuff),2)
print(genes.MDS)
#--------------------------------------------------
# MDS Plot for the genes for all replicates
#--------------------------------------------------
genes.MDS.rep<-MDSplot(genes(cuff),replicates=T)
print(genes.MDS.rep)
# Dispersion plot
disp.plot<-dispersionPlot(genes(cuff))
png("../cummerbund/dispersionplot.png")
disp.plot
dev.off()
# Squared coefficient of variance plots for genes
genes.scv<-fpkmSCVPlot(genes(cuff))
png("../cummerbund/genescv.png")
genes.scv
dev.off()
# Squared coefficient of variance plots for isoforms
isoforms.scv<-fpkmSCVPlot(isoforms(cuff))
png("../cummerbund/isoformscv.png")
isoforms.scv
dev.off()
# Plot FPKM densities for genes for each sample group
png("../cummerbund/genedensity.png")
g.dens
dev.off()
# Plot FPKM densities for genes in each replicate
png("../cummerbund/genedensity_replicates.png")
r.g.dens
dev.off()
#-------------------------------------
#Box plots for data distribution per group
#------------------------------------
b<-csBoxplot(genes(cuff))
png("../cummerbund/boxplot.png")
b
dev.off()
#-------------------------------------
#Box plots for data distribution in all replicates
#------------------------------------
brep<-csBoxplot(genes(cuff),replicates=T)
png("../cummerbund/boxplot_rep.png")
brep
dev.off()
#------------------------------------
#All groups against all Scatter plot for genes
#------------------------------------
s<-csScatterMatrix(genes(cuff))
print(s)
png("../cummerbund/gene_scatterplotplot.png")
s
dev.off()
#------------------------------------
# Two groups against each other Scatter plot for genes
#------------------------------------
s<-csScatter(genes(cuff),"MeOH","R3G",smooth=T)
s
png("../cummerbund/gene_scatterplotplot1.png")
s
dev.off()
#------------------------------------
# Dendrogram plot for each group
#------------------------------------
dend<-csDendro(genes(cuff))
plot(dend)
#------------------------------------
# Dendrogram plot for all the replicates
#------------------------------------
dend.rep<-csDendro(genes(cuff),replicates=T)
plot(dend.rep)
#------------------------------------
# Fold change (M) Vs Foldchange (A) plots for two groups
#------------------------------------
m<-MAplot(genes(cuff),"MeOH","R3G")
m
#------------------------------------
# Fold change (M) Vs counts (A) plots for two groups
#------------------------------------
mCount<-MAplot(genes(cuff),"MeOH","R3G",useCount=T)
mCount
#------------------------------------
# Fold change (M) Vs Pvalue (volcano) plots for all groups against all
#------------------------------------
v<-csVolcanoMatrix(genes(cuff))
v
#------------------------------------
# Fold change (M) Vs Pvalue (volcano) plots for two groups
#------------------------------------
v<-csVolcano(genes(cuff),"MeOH","R3G")
v
###############Filtered genes/isoforms/TSS/CDS operations#########################
#--------------------------------------------------
# Extract significantly expressed genes
#--------------------------------------------------
SigTable<-getSigTable(cuff,alpha=0.01,level='genes')
head(SigTable,20)
#--------------------------------------------------
# Plot significant genes with 5% FDR across all groups
#--------------------------------------------------
SigMat<-sigMatrix(cuff,level='genes',alpha=0.05)
print(SigMat)
#--------------------------------------------------
# Extract significant gene IDs with 5% FDR across all groups
#--------------------------------------------------
SigGeneIds<-getSig(cuff,alpha=0.05,level='genes')
head(SigGeneIds)
length(SigGeneIds)
#--------------------------------------------------
# Extract significant genes using IDs with 5% FDR across all groups
#--------------------------------------------------
SigGenes<-getGenes(cuff,SigGeneIds)
SigGenes
#--------------------------------------------------
# Extract significant isoform IDs with 5% FDR between two groups
#--------------------------------------------------
MeOH_vs_R3G.sigIsoformIds<-getSig(cuff,x='MeOH',y='R3G',alpha=0.05,level='isoforms')
head(MeOH_vs_R3G.sigIsoformIds)
length(MeOH_vs_R3G.sigIsoformIds)
###############Selected genes/isoforms/TSS/CDS operations#########################
#--------------------------------------------------
# Extract first 20 genes with 5% FDR between two groups
#--------------------------------------------------
head(SigGeneIds,20)
myGeneIds<-head(SigGeneIds,20)
myGeneIds
myGenes<-getGenes(cuff,myGeneIds)
myGenes
#--------------------------------------------------
# Extract genes between two conditions
#--------------------------------------------------
myGeneset.pluri<-getGenes(cuff,myGeneIds,sampleIdList=c("MeOH","R3G"))
myGeneset.pluri
#--------------------------------------------------
# Extract gene FPKM values for first 20 genes with 5% FDR between two groups
#--------------------------------------------------
#FPKM values for genes in gene set
head(fpkm(myGenes))
#--------------------------------------------------
# Extract isoform FPKM values for first 20 genes with 5% FDR between two groups
#--------------------------------------------------
head(fpkm(isoforms(myGenes)))
#--------------------------------------------------
# Extract TSS FPKM values for first 20 genes with 5% FDR between two groups for all replicates
#--------------------------------------------------
head(repFpkm(TSS(myGenes)))
#--------------------------------------------------
# Heatmap for gene FPKMs for two groups
#--------------------------------------------------
h<-csHeatmap(myGenes,cluster='both')+theme_bw()
h
#--------------------------------------------------
# Heatmap for gene FPKMs for all replicates within groups
#--------------------------------------------------
h.rep<-csHeatmap(myGenes,cluster='none',replicates=T)+theme_bw()
h.rep
#--------------------------------------------------
# Bar plot for selected differentially expressed genes
#--------------------------------------------------
b<-expressionBarplot(myGenes)
b
#--------------------------------------------------
# Scatter plot for selected differentially expressed genes
#--------------------------------------------------
s<-csScatter(myGenes,"MeOH","R3G",smooth=T)
s
#--------------------------------------------------
# Volcano plot for selected differentially expressed genes
#--------------------------------------------------
v<-csVolcano(myGenes,"MeOH","R3G")
v
#--------------------------------------------------
# Heatmap for isoforms from selected differentially expressed genes
#--------------------------------------------------
ih<-csHeatmap(isoforms(myGenes),cluster='both',labRow=F)
ih
#--------------------------------------------------
# Heatmap for TSS from selected differentially expressed genes
#--------------------------------------------------
th<-csHeatmap(TSS(myGenes),cluster='both',labRow=F)
th
#--------------------------------------------------
# Dendrogram plot for selected differentially expressed genes
#--------------------------------------------------
den<-csDendro(myGenes)
plot(den)
#--------------------------------------------------
# Calcualte partitions using K-means clustering for selected genes
#--------------------------------------------------
ic<-csCluster(myGenes,k=4)
head(ic$cluster)
#--------------------------------------------------
# Plot partitions using K-means clustering for selected genes
#--------------------------------------------------
icp<-csClusterPlot(ic)
icp
#--------------------------------------------------
# Calcualte condition specificity for selected genes
#--------------------------------------------------
myGenes.spec<-csSpecificity(myGenes)
head(myGenes.spec)
###############Single gene/isoform/TSS/CDS operations#########################
#--------------------------------------------------
# Extract information for a single gene
#--------------------------------------------------
myGeneId<-"KLRD1"
myGene<-getGene(cuff,myGeneId)
#--------------------------------------------------
# View available information for a stored single gene information
#--------------------------------------------------
View(features(myGene))
head(features(myGene))
#--------------------------------------------------
# View first few FPKM values for selected gene and isoforms within that gene
#--------------------------------------------------
head(fpkm(myGene))
head(fpkm(isoforms(myGene)))
#--------------------------------------------------
# Plot expression for the selected gene
#--------------------------------------------------
gl<-expressionPlot(myGene)
gl
#--------------------------------------------------
# Plot expression for the selected gene in all replicates
#--------------------------------------------------
gl.rep<-expressionPlot(myGene,replicates=TRUE)
gl.rep
#--------------------------------------------------
# Plot expression for isoforms within selected gene in all replicates
#--------------------------------------------------
gl.iso.rep<-expressionPlot(isoforms(myGene),replicates=T)
gl.iso.rep
#--------------------------------------------------
# Plot expression for isoforms within selected gene in all replicates
#--------------------------------------------------
gl.cds.rep<-expressionPlot(CDS(myGene),replicates=T)
gl.cds.rep
#--------------------------------------------------
# Expression barplot for selected gene
#--------------------------------------------------
gb<-expressionBarplot(myGene)
gb
#--------------------------------------------------
# Expression barplot for selected gene in all replicates
#--------------------------------------------------
gb.rep<-expressionBarplot(myGene,replicates=T)
gb.rep
#--------------------------------------------------
# Expression barplot for isoforms within selected gene in all replicates
#--------------------------------------------------
igb<-expressionBarplot(isoforms(myGene),replicates=T)
igb
#--------------------------------------------------
# Piechart for isoforms in selected gene
#--------------------------------------------------
gp<-csPie(myGene,level="isoforms")
gp
#---------------------------------------
#Extract similarly expressed genes that are similar to user defined gene
#---------------------------------------
mySimilar<-findSimilar(cuff,"ALKBH2",n=20)
mySimilar.expression<-expressionPlot(mySimilar,logMode=T,showErrorbars=F)
print(mySimilar.expression)
#---------------------------------------
#Extract similarly expressed genes that are similar to user defined profile
#---------------------------------------
myProfile<-c(500,0,400)
mySimilar2<-findSimilar(cuff,myProfile,n=10)
mySimilar2.expression<-expressionPlot(mySimilar2,logMode=T,showErrorbars=F)
print(mySimilar2.expression)
#------------------
# Disconnect cuff database that is been in use (only at the end)
#------------------
end<-dbDisconnect(cuff@DB)
dbConnect(cuff@DB)
#--------------------------------
# Print loaded packages and their versions used in this analysis
#---------------------------------
sessionInfo()
save.image("cummerbund.Rdata")