-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathRSEM_pipeline.R
258 lines (215 loc) · 12 KB
/
RSEM_pipeline.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
#!/usr/bin/env Rscript
suppressPackageStartupMessages(library("optparse"))
suppressPackageStartupMessages(library(affy))
suppressPackageStartupMessages(library(SummarizedExperiment))
suppressPackageStartupMessages(library(GenomicFeatures))
suppressPackageStartupMessages(library("biomaRt"))
option_list <- list(
make_option(c("-a", "--genesresultsfile"), type="character", help="genesresultsfile"),
make_option(c("-b", "--isoformsresultsfile"), type="character", help="isoformfile"),
make_option(c("-c", "--demographicfile"), type="character", help="demographicsfile"),
make_option(c("-d", "--inputfile"), type="character", help="inputfile"),
make_option(c("-e", "--fastqfile"), type="character", help="fastqfile"),
make_option(c("-f", "--picardmarkeddupfile"), type="character", help="picardmarkeddupfile"),
make_option(c("-g", "--rseqcbamstatfile"), type="character", help="rseqcbamstatfile"),
make_option(c("-z", "--multiqcgeneralstatfile"), type="character", help="genstatfile"),
make_option(c("-i", "--multiqcinferexpfile"), type="character", help="multiqcinferexpfile"),
make_option(c("-x", "--rseqcjunctionannfile"), type="character", help="rseqcjunctionannfile"),
make_option(c("-k", "--rseqcreaddistfile"), type="character", help="rseqcreaddistfile"),
make_option(c("-n", "--gtffile"), type="character", help="GTFfile")
)
opt <- parse_args(OptionParser(option_list=option_list))
genefile <- opt$genesresultsfile
trfile <- opt$isoformsresultsfile
pfile1 <- opt$demographicfile
pfile2 <- opt$inputfile
pfile3 <- opt$fastqfile
pfile4 <- opt$picardmarkeddupfile
pfile5 <- opt$rseqcbamstatfile
pfile6 <- opt$multiqcgeneralstatfile
pfile7 <- opt$multiqcinferexpfile
pfile8 <- opt$rseqcjunctionannfile
pfile9 <- opt$rseqcreaddistfile
pfile10<- opt$gtffile
##Reading in Phenotype Data Files
#Demographics
file1 = read.table(pfile1, header=TRUE, stringsAsFactors=FALSE, quote="",row.names = 1)
phenofile = as.data.frame(t(file1))
#Input file
file2 = read.table(pfile2, header=TRUE, stringsAsFactors=FALSE, quote="",row.names = "SAMPLE_ID")
phenofile = cbind(phenofile,file2)
#FASTQ
file3 = read.table(pfile3, header=TRUE,sep = "\t", stringsAsFactors=FALSE, quote="",row.names = 1)
a<- 0
matrix <- c()
while(a <nrow(file3)){
a = a+2
x <- file3[a-1,]
colnames(x) <- paste("FASTQ_R1",colnames(x),sep="_")
y <- file3[a,]
colnames(y) <- paste("FASTQ_R2",colnames(y),sep="_")
filex <- cbind(x,y)
matrix <- rbind(matrix,filex)
}
phenofile <- cbind(phenofile,matrix)
#Picard Marked Duplicates
file4 = read.table(pfile4,header=TRUE, stringsAsFactors=FALSE, quote="",row.names = 1)
colnames(file4) <- paste("picard_marked_duplicates",colnames(file4),sep="_")
phenofile = cbind(phenofile,file4)
#RSeqC BamStat
file5 = read.table(pfile5,header=TRUE, stringsAsFactors=FALSE, quote="", row.names = 1)
colnames(file5) <- paste("RSeqC_BamStat",colnames(file5),sep="_")
phenofile = cbind(phenofile,file5)
#MultiQC, General Stats
file6 = read.table(pfile6, header=TRUE, stringsAsFactors=FALSE, quote="",row.names = 1)
colnames(file6) <- paste("QC_Gen_stats",colnames(file6),sep="_")
phenofile = cbind(phenofile,file6)
#MultiQC, InferredExperiment
file7 = read.table(pfile7, header=TRUE, stringsAsFactors=FALSE, quote="", row.names = 1)
rownames(file7) <- gsub(".inferred_experiment","",row.names(file7))
colnames(file7) <- paste("infer_experiment", colnames(file7), sep="_")
phenofile = cbind(phenofile,file7)
#RSeqC Junction Annotation
file8 = read.table(pfile8, header=TRUE, stringsAsFactors=FALSE, quote="", row.names = 1)
rownames(file8) <- gsub(".junction_annotation","",row.names(file8))
colnames(file8) <- paste("junction_annotation", colnames(file8), sep="_")
phenofile = cbind(phenofile,file8)
#RSeqC Read Distribution
file9 = read.table(pfile9, header=TRUE, stringsAsFactors=FALSE, quote="", row.names = 1)
rownames(file9) <- gsub(".read_distribution","",row.names(file9))
colnames(file9) <- paste("read_distribution", colnames(file9), sep="_")
phenofile = cbind(phenofile,file9)
##Reading in assay data
#gene data
files = scan(genefile, what="")
posterior_mean_count = c()
title.matrix = c()
fpkm = c()
exp_count = c()
tpm = c()
posterior_stdev_count = c()
pme_tpm = c()
pme_fpkm = c()
tpm_lowerbound = c()
tpm_upperbound = c()
tpm_coeff_quartile_variation = c()
fpkm_ci_lowerbound = c()
fpkm_ci_upperbound = c()
fpkm_coefficient_quartile_variation = c()
for(i in files) {
temp = read.table(i, sep="\t", header=TRUE, stringsAsFactors=FALSE, quote="")
posterior_mean_count = cbind(posterior_mean_count, temp$posterior_mean_count)
fpkm = cbind(fpkm, temp$FPKM)
exp_count = cbind(exp_count, temp$expected_count)
tpm = cbind(tpm, temp$TPM)
posterior_stdev_count = cbind(posterior_stdev_count, temp$posterior_standard_deviation_of_count)
pme_tpm = cbind(pme_tpm, temp$pme_TPM)
pme_fpkm = cbind(pme_fpkm, temp$pme_FPKM)
tpm_lowerbound = cbind(tpm_lowerbound, temp$TPM_ci_lower_bound)
tpm_upperbound = cbind(tpm_upperbound, temp$TPM_ci_upper_bound)
tpm_coeff_quartile_variation = cbind(tpm_coeff_quartile_variation, temp$TPM_coefficient_of_quartile_variation)
fpkm_ci_lowerbound = cbind(fpkm_ci_lowerbound, temp$FPKM_ci_lower_bound)
fpkm_ci_upperbound = cbind(fpkm_ci_upperbound, temp$FPKM_ci_upper_bound)
fpkm_coefficient_quartile_variation = cbind(fpkm_coefficient_quartile_variation, temp$FPKM_coefficient_of_quartile_variation)
title = basename(i)
title <- gsub(".genes.results","",title)
title.matrix = cbind(title.matrix, title)
}
name.matrix <- temp$gene_id
naming <- function(name,title,matrix,phenofile){
colnames(matrix) <- as.character(title)
rownames(matrix) <- as.character(name)
return(matrix)
}
#Naming the rows/matrices
posterior_mean_count <- naming(name.matrix,title.matrix,posterior_mean_count,phenofile)
fpkm <- naming(name.matrix,title.matrix,fpkm,phenofile)
exp_count <- naming(name.matrix,title.matrix,exp_count,phenofile)
tpm <- naming(name.matrix,title.matrix,tpm,phenofile)
posterior_stdev_count <- naming(name.matrix,title.matrix,posterior_stdev_count,phenofile)
pme_tpm <- naming(name.matrix,title.matrix,pme_tpm,phenofile)
pme_fpkm <- naming(name.matrix,title.matrix,pme_fpkm,phenofile)
tpm_lowerbound <- naming(name.matrix,title.matrix,tpm_lowerbound,phenofile)
tpm_upperbound <- naming(name.matrix,title.matrix,tpm_upperbound,phenofile)
tpm_coeff_quartile_variation <- naming(name.matrix,title.matrix,tpm_coeff_quartile_variation,phenofile)
fpkm_ci_lowerbound <- naming(name.matrix,title.matrix,fpkm_ci_lowerbound,phenofile)
fpkm_ci_upperbound <- naming(name.matrix,title.matrix,fpkm_ci_upperbound,phenofile)
fpkm_coefficient_quartile_variation <- naming(name.matrix,title.matrix,fpkm_coefficient_quartile_variation,phenofile)
#trancsript data
trfiles = scan(trfile, what="")
titletr.matrix = c()
posterior_mean_count_tr = c()
fpkm_tr = c()
exp_count_tr = c()
tpm_tr = c()
posterior_stdev_count_tr = c()
pme_tpm_tr = c()
pme_fpkm_tr = c()
tpm_lowerbound_tr = c()
tpm_upperbound_tr = c()
tpm_coeff_quartile_variation_tr = c()
fpkm_ci_lowerbound_tr = c()
fpkm_ci_upperbound_tr = c()
fpkm_coefficient_quartile_variation_tr = c()
isopct_tr = c()
isopct_pmetpm_tr = c()
#Creating assaydata for transcripts
for(i in trfiles) {
temp = read.table(i, sep="\t", header=TRUE, stringsAsFactors=FALSE, quote="")
posterior_mean_count_tr = cbind(posterior_mean_count_tr, temp$posterior_mean_count)
fpkm_tr =cbind(fpkm_tr,temp$FPKM)
exp_count_tr = cbind(exp_count_tr, temp$expected_count)
tpm_tr = cbind(tpm_tr, temp$TPM)
isopct_tr = cbind(isopct_tr, temp$IsoPct)
posterior_stdev_count_tr = cbind(posterior_stdev_count_tr, temp$posterior_standard_deviation_of_count)
pme_tpm_tr = cbind(pme_tpm_tr, temp$pme_TPM)
pme_fpkm_tr = cbind(pme_fpkm_tr, temp$pme_FPKM)
isopct_pmetpm_tr = cbind(isopct_pmetpm_tr, temp$IsoPct_from_pme_TPM)
tpm_lowerbound_tr = cbind(tpm_lowerbound_tr, temp$TPM_ci_lower_bound)
tpm_upperbound_tr = cbind(tpm_upperbound_tr, temp$TPM_ci_upper_bound)
tpm_coeff_quartile_variation_tr = cbind(tpm_coeff_quartile_variation_tr, temp$TPM_coefficient_of_quartile_variation)
fpkm_ci_lowerbound_tr = cbind(fpkm_ci_lowerbound_tr, temp$FPKM_ci_lower_bound)
fpkm_ci_upperbound_tr = cbind(fpkm_ci_upperbound_tr, temp$FPKM_ci_upper_bound)
fpkm_coefficient_quartile_variation_tr = cbind(fpkm_coefficient_quartile_variation_tr,temp$FPKM_coefficient_of_quartile_variation)
title = basename(i)
title <- gsub(".isoforms.results","",title)
titletr.matrix = cbind(titletr.matrix, title)
}
nametr.matrix <- temp$transcript_id
#Naming the rows/columns
posterior_mean_count_tr <- naming(nametr.matrix,titletr.matrix,posterior_mean_count_tr,phenofile)
fpkm_tr <- naming(nametr.matrix,titletr.matrix,fpkm_tr,phenofile)
exp_count_tr <- naming(nametr.matrix,titletr.matrix,exp_count_tr,phenofile)
tpm_tr <- naming(nametr.matrix,titletr.matrix,tpm_tr,phenofile)
posterior_stdev_count_tr <- naming(nametr.matrix,titletr.matrix,posterior_stdev_count_tr,phenofile)
pme_tpm_tr <- naming(nametr.matrix,titletr.matrix,pme_tpm_tr,phenofile)
pme_fpkm_tr <- naming(nametr.matrix,titletr.matrix,pme_fpkm_tr,phenofile)
tpm_lowerbound_tr <- naming(nametr.matrix,titletr.matrix,tpm_lowerbound_tr,phenofile)
tpm_upperbound_tr <- naming(nametr.matrix,titletr.matrix,tpm_upperbound_tr,phenofile)
tpm_coeff_quartile_variation_tr <- naming(nametr.matrix,titletr.matrix,tpm_coeff_quartile_variation_tr,phenofile)
fpkm_ci_lowerbound_tr <- naming(nametr.matrix,titletr.matrix,fpkm_ci_lowerbound_tr,phenofile)
fpkm_ci_upperbound_tr <- naming(nametr.matrix,titletr.matrix,fpkm_ci_upperbound_tr,phenofile)
fpkm_coefficient_quartile_variation_tr <- naming(nametr.matrix,titletr.matrix,fpkm_coefficient_quartile_variation_tr,phenofile)
isopct_tr <- naming(nametr.matrix,titletr.matrix,isopct_tr,phenofile)
isopct_pmetpm_tr <- naming(nametr.matrix,titletr.matrix,isopct_pmetpm_tr,phenofile)
##Adding in rowRanges data
txdb = makeTxDbFromGFF(pfile10)
genedata = genes(txdb)
trdata = transcripts(txdb)
##Adding in rowData data from Biomart
mart = useEnsembl(biomart="ensembl",dataset="hsapiens_gene_ensembl", GRCh=37)
gene.attributes = c("ensembl_gene_id", "hgnc_symbol", "gene_biotype", "description","band", "external_gene_name", "external_gene_source", "transcript_count","entrezgene")
gene.info = getBM(gene.attributes, mart = mart)
transcript.attributes = c("ensembl_transcript_id", "ensembl_gene_id", "hgnc_symbol", "gene_biotype", "transcript_biotype", "description","band", "external_gene_name", "external_gene_source", "external_transcript_name", "external_transcript_source_name", "entrezgene")
transcript.info = getBM(transcript.attributes, mart = mart)
g = gene.info[gene.info[,1]%in%row.names(posterior_mean_count),]
df <- aggregate(g[2:9],g[1],unique)
mcols(genedata) <- c(mcols(genedata),df[2:9])
t = transcript.info[transcript.info[,1]%in%row.names(posterior_mean_count_tr),]
dft <- aggregate(t[2:12],t[1],unique)
mcols(trdata) <- c(mcols(trdata),dft[2:12])
##Creation of SummarizedExperiment object
se <- SummarizedExperiment(assays = list(posterior_mean_count=posterior_mean_count,fpkm=fpkm,exp_count=exp_count,tpm=tpm,posterior_stdev_count=posterior_stdev_count,pme_tpm=pme_tpm,pme_fpkm=pme_fpkm,tpm_lowerbound=tpm_lowerbound,tpm_upperbound=tpm_upperbound,tpm_coeff_quartile_variation=tpm_coeff_quartile_variation,fpkm_ci_lowerbound=fpkm_ci_lowerbound,fpkm_ci_upperbound=fpkm_ci_upperbound,fpkm_coefficient_quartile_variation=fpkm_coefficient_quartile_variation), colData=phenofile,rowRanges = genedata)
set <- SummarizedExperiment(assays = list(posterior_mean_count_tr=posterior_mean_count_tr,fpkm_tr=fpkm_tr,exp_count_tr=exp_count_tr,tpm_tr=tpm_tr,posterior_stdev_count_tr=posterior_stdev_count_tr,pme_tpm_tr=pme_tpm_tr,pme_fpkm_tr=pme_fpkm_tr,tpm_lowerbound_tr=tpm_lowerbound_tr,tpm_upperbound_tr=tpm_upperbound_tr,tpm_coeff_quartile_variation_tr=tpm_coeff_quartile_variation_tr,fpkm_ci_lowerbound_tr=fpkm_ci_lowerbound_tr,fpkm_ci_upperbound_tr=fpkm_ci_upperbound_tr,fpkm_coefficient_quartile_variation_tr=fpkm_coefficient_quartile_variation_tr,isopct_tr=isopct_tr,isopct_pmetpm_tr=isopct_pmetpm_tr), colData=phenofile,rowRanges = trdata)
saveRDS(se,"RSEM_gene.rds")
saveRDS(set,"RSEM_transcript.rds")