Last updated: 2019-03-22
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Knit directory: cropseq/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | fba9768 | simingz | 2019-03-15 | cisgene download |
| html | fba9768 | simingz | 2019-03-15 | cisgene download |
| Rmd | 56b0c36 | simingz | 2019-03-15 | cisgene download |
| html | 56b0c36 | simingz | 2019-03-15 | cisgene download |
| Rmd | 955af53 | simingz | 2019-03-15 | cisgene |
| html | 955af53 | simingz | 2019-03-15 | cisgene |
| Rmd | 5b26d50 | simingz | 2019-03-14 | empirical p |
| Rmd | a970cce | simingz | 2019-02-14 | enrichment-fisher |
| html | a970cce | simingz | 2019-02-14 | enrichment-fisher |
| Rmd | 01a5914 | simingz | 2019-02-14 | permutation |
| html | 01a5914 | simingz | 2019-02-14 | permutation |
# SNPfile: "/project2/xinhe/simingz/CROP-seq/scRNA_seq_SNP_list.txt"
module load mysql
mysql --user=genome --host=genome-mysql.cse.ucsc.edu -A -D hg19 -e '
select
K.name2,
K.name,
S.name,
S.avHet,
S.chrom,
S.chromStart,
K.txStart,
K.txEnd
from snp150 as S
left join refGene as K on
(S.chrom=K.chrom and not(K.txEnd+50000<S.chromStart or S.chromEnd+50000<K.txStart))
where
S.name in ("rs7148456","rs12895055","rs7170068","rs520843","rs12716973","rs2192932","rs17200916","rs1198588","rs324017","rs4151680","rs301791","rs324015","rs9882911","rs11633075","rs2027349","rs186132169","rs9661794","rs7936858","rs3861678","rs10933","rs6071578")' > /project2/xinhe/simingz/CROP-seq/cropseq/data/SNP_50000.txtsnpfile <- "/project2/xinhe/simingz/CROP-seq/scRNA_seq_SNP_list.txt"
gRNAsnp <- read.table(snpfile, header=F, stringsAsFactors = F)
colnames(gRNAsnp) <- c("locus_SNP", "locus")cisgene <- read.table("data/SNP_50000.txt", stringsAsFactors = F,sep="\t", header=T)
outdfall <- NULL
for (i in 1:dim(gRNAsnp)[1]){
locsnp <- gRNAsnp[i,"locus_SNP"]
loc <- gRNAsnp[i,"locus"]
loccisgene <- unique(cisgene[cisgene[,3]==locsnp,1])
for (pfile in list.files("data/gRNA_edgeR-QLF/", paste0(loc, "_.*_edgeR-qlf_Neg1_Empricialp.Rd"))){
load(paste0("data/gRNA_edgeR-QLF/",pfile))
gRNA <- strsplit(pfile, split = "_edgeR")[[1]][1]
outdf <- cbind(locsnp, loc, gRNA,loccisgene, resEmpiricalp[loccisgene, c(1,2,9,10)])
colnames(outdf)[c(1,2,4,7,8)] <- c("locus_SNP", "locus", "cisGene", "empiricalP", "empiricalFDR")
outdfall <- rbind(outdfall, outdf)
}
}
rownames(outdfall) <- NULL
outdfall <- outdfall[complete.cases(outdfall),]
outdfall[, 5:8] <- signif(outdfall[,5:8],3)
write.table( outdfall , file= "data/SNP_50000_empiricalP.txt" , row.names=F, col.names=T, sep="\t", quote = F)
DT::datatable(outdfall)cisgene <- read.table("data/SNP_200000.txt", stringsAsFactors = F,sep="\t", header=T)
outdfall <- NULL
for (i in 1:dim(gRNAsnp)[1]){
locsnp <- gRNAsnp[i,"locus_SNP"]
loc <- gRNAsnp[i,"locus"]
loccisgene <- unique(cisgene[cisgene[,3]==locsnp,1])
for (pfile in list.files("data/gRNA_edgeR-QLF/", paste0(loc, "_.*_edgeR-qlf_Neg1_Empricialp.Rd"))){
load(paste0("data/gRNA_edgeR-QLF/",pfile))
gRNA <- strsplit(pfile, split = "_edgeR")[[1]][1]
outdf <- cbind(locsnp, loc, gRNA,loccisgene, resEmpiricalp[loccisgene, c(1,2,9,10)])
colnames(outdf)[c(1,2,4,7,8)] <- c("locus_SNP", "locus", "cisGene", "empiricalP", "empiricalFDR")
outdfall <- rbind(outdfall, outdf)
}
}
rownames(outdfall) <- NULL
outdfall <- outdfall[complete.cases(outdfall),]
outdfall[, 5:8] <- signif(outdfall[,5:8],3)
write.table( outdfall , file= "data/SNP_200000_empiricalP.txt" , row.names=F, col.names=T, sep="\t", quote = F)
DT::datatable(outdfall)cisgene <- read.table("data/SNP_500000.txt", stringsAsFactors = F,sep="\t", header=T)
outdfall <- NULL
for (i in 1:dim(gRNAsnp)[1]){
locsnp <- gRNAsnp[i,"locus_SNP"]
loc <- gRNAsnp[i,"locus"]
loccisgene <- unique(cisgene[cisgene[,3]==locsnp,1])
for (pfile in list.files("data/gRNA_edgeR-QLF/", paste0(loc, "_.*_edgeR-qlf_Neg1_Empricialp.Rd"))){
load(paste0("data/gRNA_edgeR-QLF/",pfile))
gRNA <- strsplit(pfile, split = "_edgeR")[[1]][1]
outdf <- cbind(locsnp, loc, gRNA,loccisgene, resEmpiricalp[loccisgene, c(1,2,9,10)])
colnames(outdf)[c(1,2,4,7,8)] <- c("locus_SNP", "locus", "cisGene", "empiricalP", "empiricalFDR")
outdfall <- rbind(outdfall, outdf)
}
}
rownames(outdfall) <- NULL
outdfall <- outdfall[complete.cases(outdfall),]
outdfall[, 5:8] <- signif(outdfall[,5:8],3)
write.table( outdfall , file= "data/SNP_500000_empiricalP.txt" , row.names=F, col.names=T, sep="\t", quote = F)
DT::datatable(outdfall)
sessionInfo()R version 3.5.1 (2018-07-02)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)
Matrix products: default
BLAS/LAPACK: /software/openblas-0.2.19-el7-x86_64/lib/libopenblas_haswellp-r0.2.19.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] Rcpp_1.0.0 knitr_1.20 whisker_0.3-2 magrittr_1.5
[5] workflowr_1.2.0 xtable_1.8-3 R6_2.3.0 stringr_1.4.0
[9] tools_3.5.1 DT_0.5 git2r_0.23.0 htmltools_0.3.6
[13] crosstalk_1.0.0 yaml_2.2.0 rprojroot_1.3-2 digest_0.6.18
[17] shiny_1.2.0 later_0.7.5 htmlwidgets_1.3 fs_1.2.6
[21] promises_1.0.1 glue_1.3.0 evaluate_0.12 mime_0.6
[25] rmarkdown_1.10 stringi_1.3.1 compiler_3.5.1 backports_1.1.2
[29] jsonlite_1.6 httpuv_1.4.5