Last updated: 2023-02-21
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Knit directory: DO_Opioid/
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Untracked: sra-tools_v2.10.7.sif
Unstaged changes:
Modified: _workflowr.yml
Modified: analysis/Plot_DO_Fentanyl_Cohort2_mapping.Rmd
Modified: analysis/Plot_DO_Fentanyl_combining2Cohort_mapping.Rmd
Modified: analysis/Plot_DO_fentanyl.Rmd
Modified: analysis/marker_violin.Rmd
Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
These are the previous versions of the repository in which changes were made to the R Markdown (analysis/Plot_DO_morphine_secondbatch.Rmd
) and HTML (docs/Plot_DO_morphine_secondbatch.html
) files. If you’ve configured a remote Git repository (see ?wflow_git_remote
), click on the hyperlinks in the table below to view the files as they were in that past version.
File | Version | Author | Date | Message |
---|---|---|---|---|
Rmd | cc3ae27 | xhyuo | 2023-02-21 | update with sex specific morphine plot |
html | 8fe8543 | xhyuo | 2023-02-20 | Build site. |
Rmd | b46775c | xhyuo | 2023-02-20 | update with sex specific morphine |
html | 9e4e3be | xhyuo | 2021-08-24 | Build site. |
Rmd | 8b6594f | xhyuo | 2021-08-24 | add snp/gene plot |
html | c191146 | xhyuo | 2020-06-16 | Build site. |
Rmd | 45c4bc8 | xhyuo | 2020-06-16 | Plot_DO_morphine_secondbatch |
html | 5cbc78e | xhyuo | 2020-06-01 | Build site. |
Rmd | 60e46d6 | xhyuo | 2020-06-01 | Plot_DO_morphine_secondbatch |
html | b830cde | xhyuo | 2020-06-01 | Build site. |
Rmd | 8ecb9e6 | xhyuo | 2020-06-01 | Plot_DO_morphine_secondbatch |
Last update: 2023-02-21
library(ggplot2)
library(gridExtra)
library(GGally)
library(parallel)
library(qtl2)
library(parallel)
library(survival)
library(regress)
library(abind)
library(openxlsx)
rz.transform <- function(y) {
rankY=rank(y, ties.method="average", na.last="keep")
rzT=qnorm(rankY/(length(na.exclude(rankY))+1))
return(rzT)
}
load("code/do.colors.RData")
# Read phenotype data -----------------------------------------------------
second_set <- read.xlsx(xlsxFile = "data/MasterMorphine Second Set DO.xlsx",
sheet = 1)
colnames(second_set)[2] <- "Sex"
colnames(second_set)[6] <- "Status24"
#character
second_set[,c("ID", "Sex", "GROUP", "Status24")] <- lapply(second_set[, c("ID", "Sex", "GROUP", "Status24")], as.character)
second_set$Status_bin <- ifelse(second_set$Status24 == "ALIVE", 1, 0)
rownames(second_set) <- second_set$ID
#remove outlier
second_set <- second_set[second_set$ID != "empty",]
#remove negative survival time subjects
second_set <- second_set[!(!is.na(second_set$Survival.Time) & second_set$Survival.Time < 0),]
second_set$Survival.Time[!is.na(second_set$Survival.Time) & second_set$Survival.Time > 15] <- NA
second_set$Recovery.Time[!is.na(second_set$Recovery.Time) & second_set$Recovery.Time > 24] <- NA
second_set$Min.depression[!is.na(second_set$Min.depression) & second_set$Min.depression > 1] <- NA
#do
do.morphine <- get(load("output/second_set_gm.RData"))
do.pheno <- merge(second_set, do.morphine$covar, by.x = "row.names", by.y = "row.names", all.x = TRUE)
#first batch
do.pheno1 <- read.csv("data/pheno_qtl2.csv")
colnames(do.pheno1)[1] <- "ID"
do.pheno1$Survival.Time <- as.numeric(do.pheno1$Survival.Time)
do.pheno1$Recovery.Time <- as.numeric(do.pheno1$Recovery.Time)
do.pheno1$Min.depression <- as.numeric(do.pheno1$Min.depression)
do.pheno1$ngen <- "29"
#boxplot
#survival time
surv <- do.pheno[,c(2,8,15)]
#surv <- rbind(surv, do.pheno1[,c(1,2,5)])
surv <- surv[complete.cases(surv), ]
surv$ngen <- factor(surv$ngen, levels = as.character(c(30:34)))
p1 <- ggplot(surv, aes(x=ngen, y=Survival.Time, group = ngen, fill = ngen, alpha = 0.9)) +
geom_boxplot(show.legend = F , outlier.size = 1.5, notchwidth = 0.85) +
geom_jitter(color="black", size=0.8, alpha=0.9) +
scale_fill_brewer(palette="Blues") +
ylab("Survival Time") +
xlab("Generation") +
labs(fill = "") +
theme(legend.position = "none",
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank(),
axis.line = element_line(colour = "black"),
text = element_text(size=16),
axis.title=element_text(size=16)) +
guides(shape = guide_legend(override.aes = list(size = 12)))
p1
reco <- do.pheno[,c(2,9,15)]
#reco <- rbind(reco, do.pheno1[,c(1,3,5)])
reco <- reco[complete.cases(reco), ]
reco$ngen <- factor(reco$ngen, levels = as.character(c(30:35)))
p2 <- ggplot(reco, aes(x=ngen, y=Recovery.Time, group = ngen, fill = ngen, alpha = 0.9)) +
geom_boxplot(show.legend = F , outlier.size = 1.5, notchwidth = 0.85) +
geom_jitter(color="black", size=0.8, alpha=0.9) +
scale_fill_brewer(palette="Blues") +
ylab("Recovery Time") +
xlab("Generation") +
labs(fill = "") +
theme(legend.position = "none",
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank(),
axis.line = element_line(colour = "black"),
text = element_text(size=16),
axis.title=element_text(size=16)) +
guides(shape = guide_legend(override.aes = list(size = 12)))
p2
dep <- do.pheno[,c(2,10,15)]
#dep <- rbind(dep, do.pheno1[,c(1,4,5)])
dep <- dep[complete.cases(dep), ]
dep$ngen <- factor(dep$ngen, levels = as.character(c(30:35)))
p3 <- ggplot(dep, aes(x=ngen, y=Min.depression, group = ngen, fill = ngen, alpha = 0.9)) +
geom_boxplot(show.legend = F , outlier.size = 1.5, notchwidth = 0.85) +
geom_jitter(color="black", size=0.8, alpha=0.9) +
scale_fill_brewer(palette="Blues") +
ylab("Min depression") +
xlab("Generation") +
labs(fill = "") +
theme(legend.position = "none",
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank(),
axis.line = element_line(colour = "black"),
text = element_text(size=16),
axis.title=element_text(size=16)) +
guides(shape = guide_legend(override.aes = list(size = 12)))
p3
#histogram
a <- ggplot(data=do.pheno, aes(do.pheno$Survival.Time)) +
geom_histogram() +
ylab("Number of DO mice") + xlab("Survival Time (h)")
b <- ggplot(data=do.pheno, aes(do.pheno$Recovery.Time)) +
geom_histogram() +
ylab("Number of DO mice") + xlab("Recovery Time (h)")
c <- ggplot(data=do.pheno, aes(do.pheno$Min.depression)) +
geom_histogram() +
ylab("Number of DO mice") + xlab("Respiratory Depression (% of baseline)")
grid.arrange(a,b,c)
# Warning: Use of `do.pheno$Survival.Time` is discouraged. Use `Survival.Time`
# instead.
# Warning: Removed 211 rows containing non-finite values (stat_bin).
# Warning: Use of `do.pheno$Recovery.Time` is discouraged. Use `Recovery.Time`
# instead.
# Warning: Removed 166 rows containing non-finite values (stat_bin).
# Warning: Use of `do.pheno$Min.depression` is discouraged. Use `Min.depression`
# instead.
# Warning: Removed 17 rows containing non-finite values (stat_bin).
Plot by using its output qtl.morphine.out.second_set.RData
load("output/qtl.morphine.out.second_set.RData")
#pmap and gmap
chr.names <- c("1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17","18","19", "X")
gmap <- list()
pmap <- list()
for (chr in chr.names){
gmap[[chr]] <- do.morphine$gmap[[chr]]
pmap[[chr]] <- do.morphine$pmap[[chr]]
}
attr(gmap, "is_x_chr") <- structure(c(rep(FALSE,19),TRUE), names=1:20)
attr(pmap, "is_x_chr") <- structure(c(rep(FALSE,19),TRUE), names=1:20)
#genome-wide plot
for(i in names(qtl.morphine.out)){
par(mar=c(5.1, 4.1, 1.1, 1.1))
ymx <- maxlod(qtl.morphine.out[[i]]) # overall maximum LOD score
plot(qtl.morphine.out[[i]], map=pmap, lodcolumn=1, col="slateblue", ylim=c(0, 10))
abline(h=summary(qtl.morphine.operm[[i]], alpha=c(0.10, 0.05, 0.01))[[1]], col="red")
abline(h=summary(qtl.morphine.operm[[i]], alpha=c(0.10, 0.05, 0.01))[[2]], col="red")
abline(h=summary(qtl.morphine.operm[[i]], alpha=c(0.10, 0.05, 0.01))[[3]], col="red")
title(main = paste0("DO_morphine_",i))
}
#save genome-wide plot
for(i in names(qtl.morphine.out)){
png(file = paste0("output/DO_morphine_secondbatch_", i, ".png"), width = 16, height =8, res=300, units = "in")
par(mar=c(5.1, 4.1, 1.1, 1.1))
ymx <- maxlod(qtl.morphine.out[[i]]) # overall maximum LOD score
plot(qtl.morphine.out[[i]], map=pmap, lodcolumn=1, col="slateblue", ylim=c(0, 10))
abline(h=summary(qtl.morphine.operm[[i]], alpha=c(0.10, 0.05, 0.01))[[1]], col="red")
abline(h=summary(qtl.morphine.operm[[i]], alpha=c(0.10, 0.05, 0.01))[[2]], col="red")
abline(h=summary(qtl.morphine.operm[[i]], alpha=c(0.10, 0.05, 0.01))[[3]], col="red")
title(main = paste0("DO_morphine_",i))
dev.off()
}
#peaks coeff plot
for(i in names(qtl.morphine.out)){
print(i)
peaks <- find_peaks(qtl.morphine.out[[i]], map=pmap, threshold=6, drop=1.5)
print(peaks)
for(p in 1:dim(peaks)[1]) {
print(p)
chr <-peaks[p,3]
#coeff plot
par(mar=c(4.1, 4.1, 0.6, 0.6))
plot_coefCC(coef_c1[[i]][[p]], pmap[chr], scan1_output=qtl.morphine.out[[i]], bgcolor="gray95", legend=NULL)
plot_coefCC(coef_c2[[i]][[p]], pmap[chr], scan1_output=qtl.morphine.out[[i]], bgcolor="gray95", legend=NULL)
plot(out_snps[[i]][[p]]$lod, out_snps[[i]][[p]]$snpinfo, drop_hilit=1.5, genes=out_genes[[i]][[p]])
}
}
# [1] "Survival.Time"
# lodindex lodcolumn chr pos lod ci_lo ci_hi
# 1 1 pheno1 2 72.08345 6.672136 71.80655 72.11478
# 2 1 pheno1 3 98.06064 7.005262 97.69551 159.92550
# 3 1 pheno1 6 94.86810 8.427626 93.64635 95.01090
# [1] 1
# [1] 2
# [1] 3
# [1] "Recovery.Time"
# lodindex lodcolumn chr pos lod ci_lo ci_hi
# 1 1 pheno1 1 59.35852 6.107005 59.07336 194.5045
# 2 1 pheno1 4 156.04818 6.519153 114.73873 156.1199
# 3 1 pheno1 8 117.07865 6.973714 115.52733 117.7515
# [1] 1
# [1] 2
# [1] 3
Version | Author | Date |
---|---|---|
9e4e3be | xhyuo | 2021-08-24 |
Version | Author | Date |
---|---|---|
9e4e3be | xhyuo | 2021-08-24 |
# [1] "Min.depression"
# lodindex lodcolumn chr pos lod ci_lo ci_hi
# 1 1 pheno1 6 93.69909 6.677445 93.60388 94.87509
# [1] 1
Version | Author | Date |
---|---|---|
9e4e3be | xhyuo | 2021-08-24 |
Version | Author | Date |
---|---|---|
9e4e3be | xhyuo | 2021-08-24 |
Version | Author | Date |
---|---|---|
9e4e3be | xhyuo | 2021-08-24 |
# [1] "Status_bin"
# lodindex lodcolumn chr pos lod ci_lo ci_hi
# 1 1 pheno1 9 68.12998 6.087016 43.84234 123.7027
# [1] 1
Version | Author | Date |
---|---|---|
9e4e3be | xhyuo | 2021-08-24 |
Version | Author | Date |
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9e4e3be | xhyuo | 2021-08-24 |
Version | Author | Date |
---|---|---|
9e4e3be | xhyuo | 2021-08-24 |
#save peaks coeff plot
for(i in names(qtl.morphine.out)){
print(i)
peaks <- find_peaks(qtl.morphine.out[[i]], map=pmap, threshold=6, drop=1.5)
fname <- paste("output/DO_morphine_secondbatch_",i,"_coefplot.pdf",sep="")
pdf(file = fname, width = 16, height =8)
for(p in 1:dim(peaks)[1]) {
print(p)
chr <-peaks[p,3]
#coeff plot
par(mar=c(4.1, 4.1, 0.6, 0.6))
plot_coefCC(coef_c1[[i]][[p]], pmap[chr], scan1_output=qtl.morphine.out[[i]], bgcolor="gray95", legend=NULL)
plot(out_snps[[i]][[p]]$lod, out_snps[[i]][[p]]$snpinfo, drop_hilit=1.5, genes=out_genes[[i]][[p]])
}
dev.off()
}
# [1] "Survival.Time"
# [1] 1
# [1] 2
# [1] 3
# [1] "Recovery.Time"
# [1] 1
# [1] 2
# [1] 3
# [1] "Min.depression"
# [1] 1
# [1] "Status_bin"
# [1] 1
#save peaks coeff blup plot
for(i in names(qtl.morphine.out)){
print(i)
peaks <- find_peaks(qtl.morphine.out[[i]], map=pmap, threshold=6, drop=1.5)
fname <- paste("output/DO_morphine_secondbatch_",i,"_coefplot_blup.pdf",sep="")
pdf(file = fname, width = 16, height =8)
for(p in 1:dim(peaks)[1]) {
print(p)
chr <-peaks[p,3]
#coeff plot
par(mar=c(4.1, 4.1, 0.6, 0.6))
plot_coefCC(coef_c2[[i]][[p]], pmap[chr], scan1_output=qtl.morphine.out[[i]], bgcolor="gray95", legend=NULL)
plot(out_snps[[i]][[p]]$lod, out_snps[[i]][[p]]$snpinfo, drop_hilit=1.5, genes=out_genes[[i]][[p]])
}
dev.off()
}
# [1] "Survival.Time"
# [1] 1
# [1] 2
# [1] 3
# [1] "Recovery.Time"
# [1] 1
# [1] 2
# [1] 3
# [1] "Min.depression"
# [1] 1
# [1] "Status_bin"
# [1] 1
Plot by using its output qtl.morphine.69k.out.second_set.RData
load("output/qtl.morphine.69k.out.second_set.RData")
#pmap and gmap
load("data/69k_grid_pgmap.RData")
#genome-wide plot
for(i in names(qtl.morphine.out)){
par(mar=c(5.1, 4.1, 1.1, 1.1))
ymx <- maxlod(qtl.morphine.out[[i]]) # overall maximum LOD score
plot(qtl.morphine.out[[i]], map=pmap, lodcolumn=1, col="slateblue", ylim=c(0, 10))
abline(h=summary(qtl.morphine.operm[[i]], alpha=c(0.10, 0.05, 0.01))[[1]], col="red")
abline(h=summary(qtl.morphine.operm[[i]], alpha=c(0.10, 0.05, 0.01))[[2]], col="red")
abline(h=summary(qtl.morphine.operm[[i]], alpha=c(0.10, 0.05, 0.01))[[3]], col="red")
title(main = paste0("DO_morphine_",i))
}
#save genome-wide plot
for(i in names(qtl.morphine.out)){
png(file = paste0("output/DO_morphine_secondbatch_69k_", i, ".png"), width = 16, height =8, res=300, units = "in")
par(mar=c(5.1, 4.1, 1.1, 1.1))
ymx <- maxlod(qtl.morphine.out[[i]]) # overall maximum LOD score
plot(qtl.morphine.out[[i]], map=pmap, lodcolumn=1, col="slateblue", ylim=c(0, 10))
abline(h=summary(qtl.morphine.operm[[i]], alpha=c(0.10, 0.05, 0.01))[[1]], col="red")
abline(h=summary(qtl.morphine.operm[[i]], alpha=c(0.10, 0.05, 0.01))[[2]], col="red")
abline(h=summary(qtl.morphine.operm[[i]], alpha=c(0.10, 0.05, 0.01))[[3]], col="red")
title(main = paste0("DO_morphine_",i))
dev.off()
}
#peaks coeff plot
for(i in names(qtl.morphine.out)){
print(i)
peaks <- find_peaks(qtl.morphine.out[[i]], map=pmap, threshold=6, drop=1.5)
print(peaks)
for(p in 1:dim(peaks)[1]) {
print(p)
chr <-peaks[p,3]
#coeff plot
par(mar=c(4.1, 4.1, 0.6, 0.6))
plot_coefCC(coef_c1[[i]][[p]], pmap[chr], scan1_output=qtl.morphine.out[[i]], bgcolor="gray95", legend=NULL)
plot_coefCC(coef_c2[[i]][[p]], pmap[chr], scan1_output=qtl.morphine.out[[i]], bgcolor="gray95", legend=NULL)
plot(out_snps[[i]][[p]]$lod, out_snps[[i]][[p]]$snpinfo, drop_hilit=1.5, genes=out_genes[[i]][[p]])
}
}
# [1] "Survival.Time"
# lodindex lodcolumn chr pos lod ci_lo ci_hi
# 1 1 pheno1 3 98.04809 7.056873 97.51576 160.01710
# 2 1 pheno1 6 94.88068 8.514711 93.61447 95.01174
# [1] 1
# [1] 2
# [1] "Recovery.Time"
# lodindex lodcolumn chr pos lod ci_lo ci_hi
# 1 1 pheno1 1 59.37548 6.120300 59.01588 62.32984
# 2 1 pheno1 4 155.99563 6.203463 114.75702 156.13631
# 3 1 pheno1 8 117.09888 6.925422 115.52682 117.86788
# [1] 1
# [1] 2
# [1] 3
# [1] "Min.depression"
# lodindex lodcolumn chr pos lod ci_lo ci_hi
# 1 1 pheno1 6 94.17733 6.736136 93.600320 94.87681
# 2 1 pheno1 12 12.26505 6.147825 9.396249 16.88098
# 3 1 pheno1 19 44.14928 6.171079 20.756178 55.72002
# 4 1 pheno1 X 163.26639 7.254464 162.637334 164.13916
# [1] 1
# [1] 2
Version | Author | Date |
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9e4e3be | xhyuo | 2021-08-24 |
# [1] 3
Version | Author | Date |
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9e4e3be | xhyuo | 2021-08-24 |
Version | Author | Date |
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9e4e3be | xhyuo | 2021-08-24 |
Version | Author | Date |
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9e4e3be | xhyuo | 2021-08-24 |
# [1] 4
Version | Author | Date |
---|---|---|
9e4e3be | xhyuo | 2021-08-24 |
Version | Author | Date |
---|---|---|
9e4e3be | xhyuo | 2021-08-24 |
Version | Author | Date |
---|---|---|
9e4e3be | xhyuo | 2021-08-24 |
# [1] "Status_bin"
# lodindex lodcolumn chr pos lod ci_lo ci_hi
# 1 1 pheno1 9 68.16325 6.081293 43.77453 123.6993
# [1] 1
Version | Author | Date |
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9e4e3be | xhyuo | 2021-08-24 |
Version | Author | Date |
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9e4e3be | xhyuo | 2021-08-24 |
Version | Author | Date |
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9e4e3be | xhyuo | 2021-08-24 |
#save peaks coeff plot
for(i in names(qtl.morphine.out)){
print(i)
peaks <- find_peaks(qtl.morphine.out[[i]], map=pmap, threshold=6, drop=1.5)
fname <- paste("output/DO_morphine_secondbatch_69k_",i,"_coefplot.pdf",sep="")
pdf(file = fname, width = 16, height =8)
for(p in 1:dim(peaks)[1]) {
print(p)
chr <-peaks[p,3]
#coeff plot
par(mar=c(4.1, 4.1, 0.6, 0.6))
plot_coefCC(coef_c1[[i]][[p]], pmap[chr], scan1_output=qtl.morphine.out[[i]], bgcolor="gray95", legend=NULL)
plot(out_snps[[i]][[p]]$lod, out_snps[[i]][[p]]$snpinfo, drop_hilit=1.5, genes=out_genes[[i]][[p]])
}
dev.off()
}
# [1] "Survival.Time"
# [1] 1
# [1] 2
# [1] "Recovery.Time"
# [1] 1
# [1] 2
# [1] 3
# [1] "Min.depression"
# [1] 1
# [1] 2
# [1] 3
# [1] 4
# [1] "Status_bin"
# [1] 1
#save peaks coeff blup plot
for(i in names(qtl.morphine.out)){
print(i)
peaks <- find_peaks(qtl.morphine.out[[i]], map=pmap, threshold=6, drop=1.5)
fname <- paste("output/DO_morphine_secondbatch_69k_",i,"_coefplot_blup.pdf",sep="")
pdf(file = fname, width = 16, height =8)
for(p in 1:dim(peaks)[1]) {
print(p)
chr <-peaks[p,3]
#coeff plot
par(mar=c(4.1, 4.1, 0.6, 0.6))
plot_coefCC(coef_c2[[i]][[p]], pmap[chr], scan1_output=qtl.morphine.out[[i]], bgcolor="gray95", legend=NULL)
plot(out_snps[[i]][[p]]$lod, out_snps[[i]][[p]]$snpinfo, drop_hilit=1.5, genes=out_genes[[i]][[p]])
}
dev.off()
}
# [1] "Survival.Time"
# [1] 1
# [1] 2
# [1] "Recovery.Time"
# [1] 1
# [1] 2
# [1] 3
# [1] "Min.depression"
# [1] 1
# [1] 2
# [1] 3
# [1] 4
# [1] "Status_bin"
# [1] 1
load("output/qtl.morphine.out.second_set.male.RData")
#pmap and gmap
chr.names <- c("1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17","18","19", "X")
gmap <- list()
pmap <- list()
for (chr in chr.names){
gmap[[chr]] <- do.morphine$gmap[[chr]]
pmap[[chr]] <- do.morphine$pmap[[chr]]
}
attr(gmap, "is_x_chr") <- structure(c(rep(FALSE,19),TRUE), names=1:20)
attr(pmap, "is_x_chr") <- structure(c(rep(FALSE,19),TRUE), names=1:20)
#genome-wide plot
for(i in names(qtl.morphine.out)){
par(mar=c(5.1, 4.1, 1.1, 1.1))
ymx <- maxlod(qtl.morphine.out[[i]]) # overall maximum LOD score
plot(qtl.morphine.out[[i]], map=pmap, lodcolumn=1, col="slateblue", ylim=c(0, max(sapply(qtl.morphine.out, maxlod)) +2))
abline(h=summary(qtl.morphine.operm[[i]], alpha=c(0.10, 0.05, 0.01))[[1]], col="red")
abline(h=summary(qtl.morphine.operm[[i]], alpha=c(0.10, 0.05, 0.01))[[2]], col="red")
abline(h=summary(qtl.morphine.operm[[i]], alpha=c(0.10, 0.05, 0.01))[[3]], col="red")
title(main = paste0("DO_morphine_",i))
}
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
#peaks coeff plot
for(i in names(qtl.morphine.out)){
print(i)
peaks <- find_peaks(qtl.morphine.out[[i]], map=pmap, threshold=6, drop=1.5)
print(peaks)
for(p in 1:dim(peaks)[1]) {
print(p)
chr <-peaks[p,3]
#coeff plot
par(mar=c(4.1, 4.1, 0.6, 0.6))
plot_coefCC(coef_c1[[i]][[p]], pmap[chr], scan1_output=qtl.morphine.out[[i]], bgcolor="gray95", legend=NULL)
plot_coefCC(coef_c2[[i]][[p]], pmap[chr], scan1_output=qtl.morphine.out[[i]], bgcolor="gray95", legend=NULL)
plot(out_snps[[i]][[p]]$lod, out_snps[[i]][[p]]$snpinfo, drop_hilit=1.5, genes=out_genes[[i]][[p]])
}
}
# [1] "Survival.Time"
# lodindex lodcolumn chr pos lod ci_lo ci_hi
# 1 1 pheno1 1 120.12762 6.572499 40.49547 191.33153
# 2 1 pheno1 3 125.94945 6.714517 107.22292 127.25264
# 3 1 pheno1 6 93.28072 6.085423 92.70653 139.26401
# 4 1 pheno1 10 77.27719 6.883233 55.59002 78.16454
# 5 1 pheno1 11 94.11858 7.028132 93.89976 94.27434
# 6 1 pheno1 18 84.44421 7.071786 61.47853 85.27749
# 7 1 pheno1 19 11.86392 6.344164 11.74479 17.03980
# [1] 1
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] 2
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] 3
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] 4
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] 5
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] 6
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] 7
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] "Recovery.Time"
# lodindex lodcolumn chr pos lod ci_lo ci_hi
# 1 1 pheno1 2 45.6708 6.041384 43.98518 167.0778
# [1] 1
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] "Min.depression"
# lodindex lodcolumn chr pos lod ci_lo ci_hi
# 1 1 pheno1 9 122.9964 7.582778 122.2267 124.0099
# [1] 1
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] "Status_bin"
# lodindex lodcolumn chr pos lod ci_lo ci_hi
# 1 1 pheno1 5 148.11200 6.160116 147.986160 148.43807
# 2 1 pheno1 8 37.41968 6.546587 37.029877 37.85219
# 3 1 pheno1 10 108.33120 6.527988 108.088576 108.51289
# 4 1 pheno1 12 80.14229 6.091948 9.247594 103.28398
# 5 1 pheno1 15 88.17969 8.118696 87.323190 88.41707
# [1] 1
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] 2
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] 3
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] 4
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] 5
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
load("output/qtl.morphine.out.second_set.female.RData")
#pmap and gmap
chr.names <- c("1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17","18","19", "X")
gmap <- list()
pmap <- list()
for (chr in chr.names){
gmap[[chr]] <- do.morphine$gmap[[chr]]
pmap[[chr]] <- do.morphine$pmap[[chr]]
}
attr(gmap, "is_x_chr") <- structure(c(rep(FALSE,19),TRUE), names=1:20)
attr(pmap, "is_x_chr") <- structure(c(rep(FALSE,19),TRUE), names=1:20)
#genome-wide plot
for(i in names(qtl.morphine.out)){
par(mar=c(5.1, 4.1, 1.1, 1.1))
ymx <- maxlod(qtl.morphine.out[[i]]) # overall maximum LOD score
plot(qtl.morphine.out[[i]], map=pmap, lodcolumn=1, col="slateblue", ylim=c(0, max(sapply(qtl.morphine.out, maxlod)) +2))
abline(h=summary(qtl.morphine.operm[[i]], alpha=c(0.10, 0.05, 0.01))[[1]], col="red")
abline(h=summary(qtl.morphine.operm[[i]], alpha=c(0.10, 0.05, 0.01))[[2]], col="red")
abline(h=summary(qtl.morphine.operm[[i]], alpha=c(0.10, 0.05, 0.01))[[3]], col="red")
title(main = paste0("DO_morphine_",i))
}
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
#peaks coeff plot
for(i in names(qtl.morphine.out)){
print(i)
peaks <- find_peaks(qtl.morphine.out[[i]], map=pmap, threshold=6, drop=1.5)
print(peaks)
for(p in 1:dim(peaks)[1]) {
print(p)
chr <-peaks[p,3]
#coeff plot
par(mar=c(4.1, 4.1, 0.6, 0.6))
plot_coefCC(coef_c1[[i]][[p]], pmap[chr], scan1_output=qtl.morphine.out[[i]], bgcolor="gray95", legend=NULL)
plot_coefCC(coef_c2[[i]][[p]], pmap[chr], scan1_output=qtl.morphine.out[[i]], bgcolor="gray95", legend=NULL)
plot(out_snps[[i]][[p]]$lod, out_snps[[i]][[p]]$snpinfo, drop_hilit=1.5, genes=out_genes[[i]][[p]])
}
}
# [1] "Survival.Time"
# lodindex lodcolumn chr pos lod ci_lo ci_hi
# 1 1 pheno1 2 70.95263 6.278855 57.899382 173.54300
# 2 1 pheno1 3 97.98775 6.445479 35.675687 130.29440
# 3 1 pheno1 4 30.34673 6.677948 28.777007 30.81005
# 4 1 pheno1 8 115.44116 7.553628 115.137119 115.98481
# 5 1 pheno1 15 29.67993 6.173329 7.017907 47.72534
# 6 1 pheno1 19 37.85897 6.861602 37.488231 38.17204
# [1] 1
Version | Author | Date |
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8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
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8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
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8fe8543 | xhyuo | 2023-02-20 |
# [1] 2
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] 3
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] 4
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] 5
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] 6
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] "Recovery.Time"
# lodindex lodcolumn chr pos lod ci_lo ci_hi
# 1 1 pheno1 3 123.593760 6.464420 117.457785 123.638818
# 2 1 pheno1 4 156.048178 6.417408 114.723317 156.119928
# 3 1 pheno1 5 92.743909 6.654942 37.152061 95.838678
# 4 1 pheno1 10 5.988497 7.279613 5.445056 8.819529
# 5 1 pheno1 13 60.185807 6.793807 59.610678 63.542749
# [1] 1
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] 2
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] 3
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] 4
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] 5
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] "Min.depression"
# lodindex lodcolumn chr pos lod ci_lo ci_hi
# 1 1 pheno1 6 93.69909 6.430461 93.60934 94.86810
# 2 1 pheno1 19 43.49508 8.046388 43.20074 44.03063
# 3 1 pheno1 X 163.31238 7.736391 160.41596 164.23444
# [1] 1
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] 2
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] 3
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] "Status_bin"
# lodindex lodcolumn chr pos lod ci_lo ci_hi
# 1 1 pheno1 3 53.017859 6.760367 52.833289 53.290619
# 2 1 pheno1 6 4.124793 6.678702 3.200188 5.832646
# 3 1 pheno1 9 68.129978 6.719334 67.169326 68.687010
# 4 1 pheno1 12 4.923560 7.088994 3.804905 5.324666
# [1] 1
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
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8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] 2
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] 3
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
# [1] 4
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
---|---|---|
8fe8543 | xhyuo | 2023-02-20 |
Version | Author | Date |
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8fe8543 | xhyuo | 2023-02-20 |
sessionInfo()
# R version 4.0.3 (2020-10-10)
# Platform: x86_64-pc-linux-gnu (64-bit)
# Running under: Ubuntu 20.04.2 LTS
#
# Matrix products: default
# BLAS/LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.8.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=C
# [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] parallel stats graphics grDevices utils datasets methods
# [8] base
#
# other attached packages:
# [1] openxlsx_4.2.3 abind_1.4-5 regress_1.3-21 survival_3.2-7
# [5] qtl2_0.24 GGally_2.1.0 gridExtra_2.3 ggplot2_3.3.3
# [9] workflowr_1.6.2
#
# loaded via a namespace (and not attached):
# [1] tidyselect_1.1.0 xfun_0.21 purrr_0.3.4 lattice_0.20-41
# [5] splines_4.0.3 colorspace_2.0-0 vctrs_0.3.6 generics_0.1.0
# [9] htmltools_0.5.1.1 yaml_2.2.1 blob_1.2.1 rlang_1.0.2
# [13] later_1.1.0.1 pillar_1.4.7 glue_1.4.2 withr_2.4.1
# [17] DBI_1.1.1 bit64_4.0.5 RColorBrewer_1.1-2 lifecycle_1.0.0
# [21] plyr_1.8.6 stringr_1.4.0 munsell_0.5.0 gtable_0.3.0
# [25] zip_2.1.1 evaluate_0.14 memoise_2.0.0 labeling_0.4.2
# [29] knitr_1.31 fastmap_1.1.0 httpuv_1.5.5 highr_0.8
# [33] Rcpp_1.0.6 promises_1.2.0.1 scales_1.1.1 cachem_1.0.4
# [37] farver_2.0.3 fs_1.5.0 bit_4.0.4 digest_0.6.27
# [41] stringi_1.5.3 dplyr_1.0.4 grid_4.0.3 rprojroot_2.0.2
# [45] cli_2.3.0 tools_4.0.3 magrittr_2.0.1 tibble_3.0.6
# [49] RSQLite_2.2.3 crayon_1.4.1 whisker_0.4 pkgconfig_2.0.3
# [53] Matrix_1.3-2 ellipsis_0.3.1 data.table_1.13.6 assertthat_0.2.1
# [57] rmarkdown_2.6 reshape_0.8.8 R6_2.5.0 git2r_0.28.0
# [61] compiler_4.0.3
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