-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathMetaSTAARlite_worker_Gene_Centric_ncRNA_Long_Masks.r
84 lines (69 loc) · 2.93 KB
/
MetaSTAARlite_worker_Gene_Centric_ncRNA_Long_Masks.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
rm(list=ls())
gc()
## load required packages
library(gdsfmt)
library(SeqArray)
library(SeqVarTools)
library(STAAR)
library(STAARpipeline)
library(MetaSTAAR)
library(MetaSTAARlite)
###########################################################
# User Input
###########################################################
## aGDS directory
agds_dir <- get(load("/path_to_the_file/agds_dir.Rdata"))
## Null model
obj_nullmodel <- get(load("/path_to_the_file/obj_nullmodel.Rdata"))
## QC_label
QC_label <- "annotation/filter"
## variant_type
variant_type <- "SNV"
## Annotation_dir
Annotation_dir <- "annotation/info/FunctionalAnnotation"
## Annotation channel
Annotation_name_catalog <- get(load("/path_to_the_file/Annotation_name_catalog.Rdata"))
# Or equivalently
# Annotation_name_catalog <- read.csv("/path_to_the_file/Annotation_name_catalog.csv")
## Use_annotation_weights
Use_annotation_weights <- TRUE
## Annotation name
Annotation_name <- c("CADD","LINSIGHT","FATHMM.XF","aPC.EpigeneticActive","aPC.EpigeneticRepressed","aPC.EpigeneticTranscription",
"aPC.Conservation","aPC.LocalDiversity","aPC.Mappability","aPC.TF","aPC.Protein")
## output path
output_path <- "/path_to_the_output_file/"
## output file name
output_file_name <- "JHS_ncRNA"
###########################################################
# Main Function
###########################################################
## analyze large ncRNA masks
arrayid <- c(117,218,220,220,221,156,219)
sub_seq_id <- c(53,19,208,274,311,41,103)
region_spec <- data.frame(arrayid,sub_seq_id)
gene_num_in_array <- 100
group.num.allchr <- ceiling(table(ncRNA_gene[,1])/gene_num_in_array)
sum(group.num.allchr)
ncRNA_sumstat <- list()
ncRNA_cov <- list()
for(kk in 1:dim(region_spec)[1])
{
arrayid <- region_spec$arrayid[kk]
sub_seq_id <- region_spec$sub_seq_id[kk]
chr <- which.max(arrayid <= cumsum(group.num.allchr))
ncRNA_gene_chr <- ncRNA_gene[ncRNA_gene[,1]==chr,]
## aGDS file
agds.path <- agds_dir[chr]
genofile <- seqOpen(agds.path)
gene_name <- ncRNA_gene_chr[sub_seq_id,2]
results_temp <- ncRNA_MetaSTAARlite_worker(chr=chr,gene_name=gene_name,genofile=genofile,obj_nullmodel=obj_nullmodel,
cov_maf_cutoff=0.05,signif.digits=NULL,
QC_label=QC_label,check_qc_label=TRUE,variant_type=variant_type,
Annotation_dir=Annotation_dir,Annotation_name_catalog=Annotation_name_catalog,
Use_annotation_weights=Use_annotation_weights,Annotation_name=Annotation_name)
ncRNA_sumstat[[gene_name]] <- results_temp$summary_stat
ncRNA_cov[[gene_name]] <- results_temp$GTSinvG_rare
seqClose(genofile)
}
save(ncRNA_sumstat,file=paste0(output_path,output_file_name,"_sumstat_",223,".Rdata"),compress = "xz")
save(ncRNA_cov,file=paste0(output_path,output_file_name,"_cov_",223,".Rdata"),compress = "xz")