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merge_elai.R
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merge_elai.R
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#!/usr/bin/env Rscript
mylib <- "~/R/x86_64-pc-linux-gnu-library/4.0"
.libPaths(mylib)
library(LEA)
suppressPackageStartupMessages(library(Rsamtools))
library(tidyverse)
library(viridis)
library(Rcpp)
library(data.table)
args <- commandArgs(trailingOnly = TRUE)
chr_nb <- args[1]
outdir <- "/shared/projects/elai_most/data/snakelai_out_all/elai3runs_45VN_merged"
dir.create(outdir, showWarnings = FALSE)
elai_outdir <- "/shared/projects/elai_most/data/snakelai_out_all/elai_average"
source_dir <- "/shared/projects/elai_most/data/snakelai_out_all/source"
# function
sourceCpp("/shared/projects/vietcaf/scripts/snakelai/script/elai2GR.cpp")
plot_elai <- function(snakedir, chrom, groups, plot_path = NULL) {
snp <- c("all", "even")
all_dosage <- do.call(rbind, lapply(snp, function(s) {
result_data <- file.path(snakedir, chrom, s, "c5_mg20", "local_dosage.csv")
print(result_data)
all_dosage <- fread(result_data)
all_dosage1 <- data.frame(all_dosage, snp = s)
return(all_dosage1)
}))
print("done1")
all_dosage$ancestry <- factor(all_dosage$ancestry)
print("done2")
levels(all_dosage$ancestry) <- groups
print("done3")
all_dosage$ancestry <- factor(all_dosage$ancestry, levels = c("ER", "OB", "C", "AG", "D"))
print("done4")
if (!is.null(plot_path)) {
cat(plot_path)
# tiff(file = plot_path,
# width = 20, height = 12, units = "in", res = 800)
p <- ggplot(all_dosage) +
facet_grid(rows = vars(individual)) +
# geom_point(aes(x = pos, y = dosage, color = ancestry), size = 1.5, shape = 16, alpha = .5) +
geom_line(aes(x = pos, y = dosage, color = ancestry, linetype = snp, alpha = snp)) +
scale_linetype_manual(values=c("dashed", "solid")) +
# scale_color_viridis_d(end = 0.9) +
scale_color_manual(values = group_col) +
scale_alpha_manual(values = c(.8, 1)) +
xlab(paste("Position on chromosome", unique(all_dosage$chr))) +
ylab("Ancestral dosage") +
theme_minimal() +
theme(axis.text.x = element_blank(),
axis.title.y = element_text(size = 12),
axis.title.x = element_blank(),
legend.text = element_text(size = 12),
legend.title = element_text(size = 12),
legend.key.size = unit(5, "mm"),
axis.ticks.y = element_line(size = .1),
axis.text.y = element_text(size = 8),
panel.spacing = unit(2, "mm"),
strip.text.x = element_text(angle = 90, size = 10, hjust = 1))
ggsave(filename = plot_path, plot = p, width = 10, height = 6, dpi = 1000)
# dev.off()
}
return(invisible(all_dosage))
}
rounding <- function(x) {
n <- sapply(x, function(i) {
if (i < 0.1) {
i <- 0
} else if (i > 0.4 && i < .6) {
i <- 0.5
} else if (i > 0.9) {
i <- 1
} else {
i <- NA
}
}, USE.NAMES = F, simplify = T)
return(n)
}
elai_GR <- function(all_dosage, gap = 1e6){
# rounding admixture
all_dosage <- all_dosage %>%
mutate(dosage = rounding(dosage)) %>%
arrange(snp, pos)
com_dosage <- reshape2::dcast(all_dosage, ... ~ snp,
value.var = "dosage")
# remove ambiguous positions
com_dosage <- na.omit(com_dosage)
# for each individual and each ancestry,
# retain positions that have equal admixture
fin_dosage <- com_dosage %>%
group_by(individual, ancestry) %>%
arrange(pos) %>%
rowwise() %>%
filter(all == even)
elai_GR_list <- dosage2GR(fin_dosage = fin_dosage, gap_length = gap)
return(elai_GR_list)
}
# list of individuals
vcf_file <- list.files(source_dir, "CC1.8.Chr07.recode.vcf", recursive = T, full.names = T)
vcf_header <- scanBcfHeader(vcf_file)
ind_names <- vcf_header[[1]]@listData$Sample
info_file <- "/shared/projects/elai_most/data/snakelai_out_all/config/sequence_info_final.tsv"
ind_info <- read.delim(info_file)
ind_names <- sapply(ind_names, function(i)
ifelse(any(grepl(i, ind_info$Label)),
grep(i, ind_info$Label, value = T),
i),
USE.NAMES = F)
# get elai results
chrom <- paste0("CC1.8.Chr", chr_nb)
chr_snmf <- load.snmfProject(file.path(source_dir, chrom, "snmf/chr.snmfProject"))
chr_bestrun <- which.min(cross.entropy(chr_snmf))
chr_prop <- Q(chr_snmf, run = chr_bestrun)
rownames(chr_prop) <- ind_names
chr_groups <- chr_prop %>%
as.data.frame() %>%
rownames_to_column("id") %>%
filter(!grepl("S.+", id)) %>%
mutate(prior = gsub(".+_", "", id)) %>%
mutate(prior = case_when(prior %in% c("O", "B") ~ "OB",
prior %in% c("E", "R") ~ "ER",
prior %in% c("A", "G") ~ "AG",
TRUE ~ prior)) %>%
pivot_longer(cols = V1:V5, names_to = "ancestry", values_to = "proportion") %>%
group_by(ancestry) %>%
arrange(desc(proportion), .by_group = T) %>%
slice_head(n = 3) %>% slice_tail(n = 1) %>% pull(prior) # n=2 for chr08, n=3 for chr11, n=1 for others
print(chrom)
print(chr_groups)
chr_dose <- plot_elai(snakedir = elai_outdir, chrom = chrom, groups = chr_groups)
chr_GR <- elai_GR(chr_dose)
saveRDS(chr_GR, file = file.path(outdir, paste0("chrom_", chr_nb, ".RDS")))