R/gwas gene plot 20180802.R
In whweve/wisassoplot2: visualize genome-wide association study with gene annotation and linkage disequiblism
#' @title plot association with LD and annotation at a given gene
#' @description This function plot the association with
#' linkage disequiblism and annotation at the level of a single gene.
#' @author Hongwei Wang <\email{whweve@163.com}>
#' @param transcript the transcript of gene, required.
#' @param gtf the annotation file, required.
#' @param association the association table, required.
#' @param hapmap the genotype file for computing leadsnpLD in the format of hapmap. The file should be the same file used for coumputing association. required.
#' @param hapmap_ld the genotype file for computing trangleLD in the format of hapmap, not required. If hapmap_ld was not provided, hapmap would be used.
#' @param slide_length the sliding window length for computing LD, default -1.
#' @param threadN the number of (CPU) cores used for computing LD, default 1.
#' @param up the upper distance from the start position of gene
#' @param down the down distance from the end position of gene
#' @param threshold the significant level of the assocition, default NULL.
#' @param ldstatistics the statistics used for computing LD, default rsquare, and the optional is dprime.
#' @param leadsnp snp name provided by user
#' @param link2gene link the locis that passed the threshold to the genic structure, default TRUE.
#' @param triangleLD show LD in the format lile triangle, default TRUE.
#' @param link2LD link the locis that passed the threshold to the LD, default TRUE.
#' @param leadsnpLD show LD of the locis when compared with the most significant loci, default TRUE.
#' @param exon_colour the colour of exon, default gray.
#' @param cds_colour the colour of cds, default black.
#' @param utr_colour the colour of utr, default gray.
#' @param intron_colour the colour of intron, default gray.
#' @param colour02 the colour of LD statistics ranged between 0.0 and 0.2, default gray.
#' @param colour04 the colour of LD statistics ranged between 0.2 and 0.4, default cyan.
#' @param colour06 the colour of LD statistics ranged between 0.4 and 0.6, default green.
#' @param colour08 the colour of LD statistics ranged between 0.6 and 0.8, default yellow.
#' @param colour10 the colour of LD statistics ranged between 0.8 and 1.0, default red.
#' @return ggplot2 plot
#' @export
#' @import ggplot2 genetics reshape2
#' @examples
#' data(gtf)
#' data(zmvpp1_association)
#' data(zmvpp1_hapmap)
#' plot_gene('GRMZM2G170927_T01',gtf,association=zmvpp1_association,hapmap=zmvpp1_hapmap,hapmap_ld = zmvpp1_hapmap,threshold=8,up=500,down=600,leadsnpLD = FALSE)
plot_gene <- function(transcript, gtf, association, hapmap, hapmap_ld = NULL, slide_length = -1,
threadN = 1, up = NULL, down = NULL, threshold = NULL, ldstatistics = "rsq",
leadsnp = NULL, link2gene = TRUE, triangleLD = TRUE, link2LD = TRUE, leadsnpLD = TRUE,
exon_colour = "gray", cds_colour = "black", utr_colour = "gray", intron_colour = "gray",
colour02 = "gray", colour04 = "cyan", colour06 = "green", colour08 = "yellow",
colour10 = "red") {
if (sum(grepl(transcript, gtf$V9)) == 0) {
stop("please provide the correct transcript or the gtf file")
} else {
transcript_corrdination <- gtf[grepl(transcript, gtf$V9), ]
chromosome_association <- association[association$Locus == unique(transcript_corrdination$V1),
]
transcript_corrdination <- gtf[grepl(transcript, gtf$V9), ]
transcript_min <- ifelse(is.null(up), min(transcript_corrdination$V4), min(transcript_corrdination$V4) -
up)
transcript_max <- ifelse(is.null(down), max(transcript_corrdination$V5),
max(transcript_corrdination$V5) + down)
transcript_association <- chromosome_association[chromosome_association$Site >=
transcript_min & chromosome_association$Site <= transcript_max, ]
transcript_association <- transcript_association[order(transcript_association$Site),
]
if (dim(transcript_association)[1] == 0) {
stop("no association observed")
} else {
# compute the meta variable
pvalue_range <- pretty(-log10(transcript_association$p))
# adjust the yaxis to fit in the LD plot
fold <- ((transcript_max - transcript_min) * 2/3)/max(pvalue_range)
n_pvalue_range <- length(pvalue_range)
marker_number = dim(transcript_association)[1]
length = (transcript_max - transcript_min)
distance = 0.5 * length/(marker_number - 1)
# transcript start and end
for (struct in c("utr", "cds", "exon")) {
assign(paste0("transcript_structure_", struct), transcript_corrdination[grep(struct,
transcript_corrdination$V3, ignore.case = T), ])
if (dim(get(paste0("transcript_structure_", struct)))[1] > 0) {
assign(paste0("transcript_structure_", struct, "_list"), list(geom_segment(data = get(paste0("transcript_structure_",
struct)), aes(x = V4, xend = V5, y = -max(pvalue_range) * fold/30,
yend = -max(pvalue_range) * fold/30), colour = get(paste0(struct,
"_colour")), size = 4)))
} else {
assign(paste0("transcript_structure_", struct, "_list"), NULL)
}
}
transcript_intron_structure <- list(geom_segment(aes(x = transcript_min,
xend = transcript_max, y = -max(pvalue_range) * fold/30, yend = -max(pvalue_range) *
fold/30), colour = intron_colour, size = 1))
# decide whether to rotate x axis
scale_x <- ifelse(unique(transcript_corrdination$V7) == "-", list(scale_x_reverse(limits = c((transcript_max -
transcript_min)/6 + transcript_max, transcript_min), breaks = seq(transcript_max,
transcript_min, transcript_min - transcript_max))), list(scale_x_continuous(limits = c(transcript_min -
(transcript_max - transcript_min)/6, transcript_max), breaks = seq(transcript_min,
transcript_max, transcript_max - transcript_min))))
# label the yaxis
scale_y_line <- ifelse(unique(transcript_corrdination$V7) == "-", list(geom_segment(aes(x = (transcript_max -
transcript_min)/30 + transcript_max, y = min(pvalue_range), xend = (transcript_max -
transcript_min)/30 + transcript_max, yend = max(pvalue_range) *
fold))), list(geom_segment(aes(x = transcript_min - (transcript_max -
transcript_min)/30, y = min(pvalue_range), xend = transcript_min -
(transcript_max - transcript_min)/30, yend = max(pvalue_range) *
fold))))
scale_y_ticks <- ifelse(unique(transcript_corrdination$V7) == "-", list(geom_segment(aes(x = rep((transcript_max -
transcript_min)/15 + transcript_max, n_pvalue_range), y = pvalue_range *
fold, xend = (transcript_max - transcript_min)/30 + transcript_max,
yend = pvalue_range * fold))), list(geom_segment(aes(x = rep(transcript_min -
(transcript_max - transcript_min)/15, n_pvalue_range), y = pvalue_range *
fold, xend = rep(transcript_min - (transcript_max - transcript_min)/30,
n_pvalue_range), yend = pvalue_range * fold))))
scale_y_text <- ifelse(unique(transcript_corrdination$V7) == "-", list(geom_text(aes(x = rep((transcript_max -
transcript_min)/12 + transcript_max, n_pvalue_range), y = pvalue_range *
fold, label = pvalue_range))), list(geom_text(aes(x = rep(transcript_min -
(transcript_max - transcript_min)/12, n_pvalue_range), y = pvalue_range *
fold, label = pvalue_range))))
# add threshold line
if (is.null(threshold)) {
threshold_line <- list(NULL)
}
if (all(length(threshold) > 0, threshold <= max(pvalue_range))) {
threshold_line <- list(geom_segment(aes(x = transcript_min, xend = transcript_max,
y = threshold * fold, yend = threshold * fold), linetype = "longdash",
colour = "gray"))
}
if (all(length(threshold) > 0, threshold > max(pvalue_range))) {
threshold_line <- list(NULL)
print("no -log10(p) pass the threshold, will not draw threshold line")
}
# compute the LD, leadsnp or triangle
if (any(isTRUE(leadsnpLD), isTRUE(triangleLD)) & is.null(hapmap)) {
print("no hapmap data found, please provide the hapmap")
ld_leadsnp_colour <- list(NULL)
bottom_trianglLD = list(NULL)
}
if (all(!isTRUE(leadsnpLD), !isTRUE(triangleLD), !is.null(hapmap))) {
ld_leadsnp_colour <- list(NULL)
bottom_trianglLD <- list(NULL)
}
# link association and LD for the significant loci link between LD and genic
# structure
if (any(isTRUE(leadsnpLD), isTRUE(triangleLD)) & !is.null(hapmap)) {
names(hapmap) <- sub("#", "", names(hapmap))
gene_snp <- hapmap[hapmap$chrom == unique(transcript_corrdination$V1) &
hapmap$pos >= transcript_min & hapmap$pos <= transcript_max, ]
# gene_snp = hapmap2
names(gene_snp) <- sub("#", "", names(gene_snp))
gene_snp <- gene_snp[!duplicated(gene_snp$rs), ]
# convert the SNP to numeric format
major_allele <- paste0(substr(gene_snp$allele, 1, 1), substr(gene_snp$allele,
1, 1))
minor_allele <- paste0(substr(gene_snp$allele, 3, 3), substr(gene_snp$allele,
3, 3))
heter_left <- paste0(substr(gene_snp$allele, 1, 1), substr(gene_snp$allele,
3, 3))
heter_right <- paste0(substr(gene_snp$allele, 3, 3), substr(gene_snp$allele,
1, 1))
# if allele equal to major allele, 0, else 2
for (j in 12:dim(gene_snp)[2]) {
gene_snp[gene_snp[, j] == major_allele, j] = 2
gene_snp[gene_snp[, j] == minor_allele, j] = 0
gene_snp[gene_snp[, j] == "NN", j] = NA
heter_position_left <- which(isTRUE(gene_snp[, j] == heter_left))
heter_position_right <- which(isTRUE(gene_snp[, j] == heter_right))
if (length(heter_position_left) > 1) {
gene_snp[heter_position_left, j] = 1
}
if (length(heter_position_right) > 1) {
gene_snp[heter_position_right, j] = 1
}
}
gene_snp2 <- gene_snp[, 12:dim(gene_snp)[2]]
gene_snp2 <- as.matrix(sapply(gene_snp2, as.numeric))
snpgdsCreateGeno("test.gds", genmat = gene_snp2, sample.id = names(gene_snp)[12:dim(gene_snp)[2]],
snp.id = gene_snp$rs, snp.position = gene_snp$pos, snp.allele = gene_snp$alleles,
snpfirstdim = TRUE)
genofile <- snpgdsOpen("test.gds")
if (ldstatistics == "rsq") {
aa = snpgdsLDMat(genofile, slide = slide_length, method = "corr",
num.thread = threadN)
}
if (ldstatistics == "dprime") {
aa = snpgdsLDMat(genofile, slide = slide_length, method = "dprime",
num.thread = threadN)
}
snpgdsClose(genofile)
ld = aa$LD
if (ldstatistics == "rsq")
ld <- ld^2
names(ld) <- gene_snp$rs
ld <- melt(ld)
marker_info <- data.frame(index = 1:dim(gene_snp)[1], marker_name = gene_snp$rs)
ld$Var1 <- marker_info$marker[match(ld$Var1, marker_info$index)]
ld$Var2 <- marker_info$marker[match(ld$Var2, marker_info$index)]
if (ldstatistics == "rsq") {
lengend_name = expression(italic(r)^2)
} else if (ldstatistics == "dprime") {
lengend_name = expression(D * {
"'"
})
}
ld <- ld[!is.na(ld$value), ]
ld_reverse <- data.frame(Var1 = ld$Var2, Var2 = ld$Var1, value = ld$value)
ld <- rbind(ld, ld_reverse)
marker_pos <- transcript_association[, c("Marker", "Site")]
ld$Site1 <- marker_pos$Site[match(ld$Var1, marker_pos$Marker)]
ld$Site2 <- marker_pos$Site[match(ld$Var2, marker_pos$Marker)]
# ld <- merge(ld,marker_pos,by.x='Var1',by.y = 'Marker') ld <-
# merge(ld,marker_pos,by.x='Var2',by.y = 'Marker') names(ld) =
# sub('Site.x','Site1',names(ld)) names(ld) = sub('Site.y','Site2',names(ld))
if (isTRUE(leadsnpLD)) {
if (is.null(leadsnp)) {
leadsnp <- as.character(transcript_association[which.min(transcript_association$p),
"Marker"])
}
if (!is.null(leadsnp)) {
leadsnp <- leadsnp
}
ld_leadsnp <- ld[ld$Var1 == leadsnp, ]
ld_leadsnp <- merge(ld_leadsnp, transcript_association, by.x = "Var2",
by.y = "Marker")
ld_leadsnp$R2 <- 0.2 * (ld_leadsnp$value%/%0.2 + as.logical(ld_leadsnp$value%/%0.2))
ld_leadsnp$R2 <- as.character(ld_leadsnp$R2)
ld_leadsnp$R2[ld_leadsnp$R2 == "0"] = "0.2"
ld_leadsnp$R2[ld_leadsnp$R2 == "1.2"] = "1"
if (length(which(ld_leadsnp$Var1 == leadsnp & ld_leadsnp$Var2 ==
leadsnp)) >= 1) {
ld_leadsnp <- ld_leadsnp[!(ld_leadsnp$Var1 == leadsnp & ld_leadsnp$Var2 ==
leadsnp), ]
}
ld_leadsnp_colour <- list(geom_point(data = ld_leadsnp, aes(Site2,
-log10(p) * fold, fill = R2), pch = 21, colour = "black"), scale_fill_manual(values = c(`0.2` = colour02,
`0.4` = colour04, `0.6` = colour06, `0.8` = colour08, `1` = colour10),
labels = c("0-0.2", "0.2-0.4", "0.4-0.6", "0.6-0.8", "0.8-1.0"),
name = lengend_name))
}
if (!isTRUE(leadsnpLD)) {
ld_leadsnp_colour <- list(NULL)
}
if (isTRUE(triangleLD)) {
if (is.null(hapmap_ld)) {
hapmap_ld <- hapmap
}
hapmap_ld <- hapmap_ld[hapmap_ld$chrom == unique(transcript_corrdination$V1) &
hapmap_ld$pos >= transcript_min & hapmap_ld$pos <= transcript_max,
]
marker_number = dim(hapmap_ld)[1]
length = (transcript_max - transcript_min)
distance = 0.5 * length/(marker_number - 1)
names(hapmap_ld) <- sub("#", "", names(hapmap_ld))
gene_snp <- hapmap_ld
names(gene_snp) <- sub("#", "", names(gene_snp))
gene_snp <- gene_snp[!duplicated(gene_snp$rs), ]
# convert the SNP to numeric format
major_allele <- paste0(substr(gene_snp$allele, 1, 1), substr(gene_snp$allele,
1, 1))
minor_allele <- paste0(substr(gene_snp$allele, 3, 3), substr(gene_snp$allele,
3, 3))
heter_left <- paste0(substr(gene_snp$allele, 1, 1), substr(gene_snp$allele,
3, 3))
heter_right <- paste0(substr(gene_snp$allele, 3, 3), substr(gene_snp$allele,
1, 1))
# if allele equal to major allele, 0, else 2
for (j in 12:dim(gene_snp)[2]) {
gene_snp[gene_snp[, j] == major_allele, j] = 2
gene_snp[gene_snp[, j] == minor_allele, j] = 0
gene_snp[gene_snp[, j] == "NN", j] = NA
heter_position_left <- which(isTRUE(gene_snp[, j] == heter_left))
heter_position_right <- which(isTRUE(gene_snp[, j] == heter_right))
if (length(heter_position_left) > 1) {
gene_snp[heter_position_left, j] = 1
}
if (length(heter_position_right) > 1) {
gene_snp[heter_position_right, j] = 1
}
}
gene_snp2 <- gene_snp[, 12:dim(gene_snp)[2]]
gene_snp2 <- as.matrix(sapply(gene_snp2, as.numeric))
snpgdsCreateGeno("test.gds", genmat = gene_snp2, sample.id = names(gene_snp)[12:dim(gene_snp)[2]],
snp.id = gene_snp$rs, snp.position = gene_snp$pos, snp.allele = gene_snp$alleles,
snpfirstdim = TRUE)
genofile <- snpgdsOpen("test.gds")
if (ldstatistics == "rsq") {
aa = snpgdsLDMat(genofile, slide = slide_length, method = "corr",
num.thread = threadN)
}
if (ldstatistics == "dprime") {
aa = snpgdsLDMat(genofile, slide = slide_length, method = "dprime",
num.thread = threadN)
}
snpgdsClose(genofile)
ld = aa$LD
if (ldstatistics == "rsq")
ld <- ld^2
names(ld) <- gene_snp$rs
ld <- melt(ld)
marker_info <- data.frame(index = 1:dim(gene_snp)[1], marker_name = gene_snp$rs)
ld$Var1 <- marker_info$marker[match(ld$Var1, marker_info$index)]
ld$Var2 <- marker_info$marker[match(ld$Var2, marker_info$index)]
if (ldstatistics == "rsq") {
lengend_name = expression(italic(r)^2)
} else if (ldstatistics == "dprime") {
lengend_name = expression(D * {
"'"
})
}
ld <- ld[!is.na(ld$value), ]
ld_reverse <- data.frame(Var1 = ld$Var2, Var2 = ld$Var1, value = ld$value)
ld <- rbind(ld, ld_reverse)
marker_pos <- hapmap_ld[, c("rs", "pos")]
ld$Site1 <- marker_pos$pos[match(ld$Var1, marker_pos$rs)]
ld$Site2 <- marker_pos$pos[match(ld$Var2, marker_pos$rs)]
# ld <- merge(ld,marker_pos,by.x='Var1',by.y = 'rs') ld <-
# merge(ld,marker_pos,by.x='Var2',by.y = 'rs') names(ld) =
# sub('pos.x','Site1',names(ld)) names(ld) = sub('pos.y','Site2',names(ld))
# compute the LD position, the sequence ranged from small to big
marker_pair = NULL
center_x = NULL
center_y = NULL
locib <- rep(1:(marker_number-1),(marker_number-1):1)
locia <- NULL
for (row in 1:(marker_number - 1)) {
locia <- c(locia,seq(1:(marker_number-row)))
}
marker_pair <- paste0(locia,"_",locia+locib)
center_x <- distance*(locia+locia+locib-2)
center_y <- -locib*distance
upper_center_x <- center_x
upper_center_y <- center_y + distance
lower_center_x <- center_x
lower_center_y <- center_y - distance
left_center_x <- center_x - distance
left_center_y <- center_y
right_center_x <- center_x + distance
right_center_y <- center_y
poly_data <- data.frame(group = rep(marker_pair, 4), x = c(upper_center_x,
right_center_x, lower_center_x, left_center_x) + transcript_min,
y = c(upper_center_y, right_center_y, lower_center_y, left_center_y) -
4 * max(pvalue_range) * fold/30, label = rep(c(1, 2, 3, 4),
each = length(upper_center_x)))
poly_data$marker1 <- sub("([0-9]+)_[0-9]+", "\\1", poly_data$group)
poly_data$marker2 <- sub("[0-9]+_([0-9]+)", "\\1", poly_data$group)
# transcript_association <-
# transcript_association[order(transcript_association$Site),]
# transcript_association$marker_number <- 1:dim(transcript_association)[1]
# marker_index <- transcript_association[,c('Marker','marker_number')]
hapmap_ld <- hapmap_ld[order(hapmap_ld$pos), ]
hapmap_ld$marker_number <- 1:dim(hapmap_ld)[1]
marker_index <- hapmap_ld[, c("rs", "marker_number")]
poly_data$Var1 <- marker_index$rs[match(poly_data$marker1, marker_index$marker_number)]
poly_data$Var2 <- marker_index$rs[match(poly_data$marker2, marker_index$marker_number)]
# poly_data <- merge(poly_data,marker_index,by.x='marker1',by.y =
# 'marker_number') poly_data <- merge(poly_data,marker_index,by.x='marker2',by.y
# = 'marker_number') names(poly_data) = sub('rs.x','Var1',names(poly_data))
# names(poly_data) = sub('rs.y','Var2',names(poly_data))
poly_data$value <- ld$value[match(paste0(poly_data$Var1, "/",
poly_data$Var2), paste0(ld$Var1, "/", ld$Var2))]
poly_data$Site1 <- ld$Site1[match(paste0(poly_data$Var1, "/",
poly_data$Var2), paste0(ld$Var1, "/", ld$Var2))]
poly_data$Site2 <- ld$Site2[match(paste0(poly_data$Var1, "/",
poly_data$Var2), paste0(ld$Var1, "/", ld$Var2))]
# poly_data <- merge(poly_data,ld,by.x=c('Var1','Var2'),by.y = c('Var1','Var2'))
poly_data$R2 <- 0.2 * (poly_data$value%/%0.2 + as.logical(poly_data$value%/%0.2))
poly_data$R2 <- as.character(poly_data$R2)
poly_data$R2[poly_data$R2 == "0"] = "0.2"
poly_data$R2[poly_data$R2 == "1.2"] = "1"
poly_data <- poly_data[order(poly_data$group, poly_data$label),
]
if (!isTRUE(leadsnpLD)) {
bottom_trianglLD = list(geom_polygon(data = poly_data, aes(group = group,
x = x, y = y - (transcript_max - transcript_min)/50, fill = R2)),
scale_fill_manual(values = c(`0.2` = colour02, `0.4` = colour04,
`0.6` = colour06, `0.8` = colour08, `1` = colour10), labels = c("0-0.2",
"0.2-0.4", "0.4-0.6", "0.6-0.8", "0.8-1.0"), name = lengend_name))
}
if (isTRUE(leadsnpLD)) {
bottom_trianglLD = list(geom_polygon(data = poly_data, aes(group = group,
x = x, y = y - (transcript_max - transcript_min)/50, fill = R2)))
}
}
if (!isTRUE(triangleLD)) {
bottom_trianglLD <- list(NULL)
}
}
# link line from significant loci to the strucuture
if (!isTRUE(link2gene) & any(!is.null(threshold), is.null(threshold))) {
link_asso_gene <- list(NULL)
}
if (isTRUE(link2gene) & is.null(threshold)) {
print("threshold acquired")
link_asso_gene <- list(NULL)
}
if (isTRUE(link2gene) & !is.null(threshold)) {
link_association_structure <- transcript_association[-log10(transcript_association$p) >=
threshold, ]
link_association_structure <- link_association_structure[!duplicated(link_association_structure$p),
]
if (dim(link_association_structure)[1] == 0) {
print("no -log10(p) pass the threshold, will not draw link")
link_asso_gene <- list(NULL)
threshold_line <- list(NULL)
}
if (dim(link_association_structure)[1] > 0) {
link_association_structure <- transcript_association[-log10(transcript_association$p) >=
threshold, ]
link_association_structure <- link_association_structure[!duplicated(link_association_structure$p),
]
link_number <- dim(link_association_structure)[1]
link_asso_gene <- list(geom_segment(data = link_association_structure,
aes(x = Site, xend = Site, y = rep(-max(pvalue_range) * fold/30,
link_number), yend = -log10(p) * fold), linetype = "longdash",
colour = "red"))
}
}
if (isTRUE(triangleLD) & isTRUE(link2gene) & isTRUE(link2LD)) {
link_association_structure <- transcript_association[-log10(transcript_association$p) >=
threshold, ]
link_association_structure <- link_association_structure[!duplicated(link_association_structure$p),
]
link_number <- dim(link_association_structure)[1]
link_asso_gene <- list(geom_segment(data = link_association_structure,
aes(x = Site, xend = Site, y = rep(-max(pvalue_range) * fold/30,
link_number), yend = -log10(p) * fold), linetype = "longdash",
colour = "red"))
marker_axis_LD_x <- transcript_min + (seq(1:marker_number) - 1) *
2 * distance
marker_axis_genic_x <- hapmap_ld$pos
marker_axis_LD_y <- rep(-4 * max(pvalue_range) * fold/30, marker_number)
marker_axis_genic_y <- rep(-max(pvalue_range) * fold/30, marker_number)
link_ld_data <- data.frame(x = marker_axis_LD_x, xend = marker_axis_genic_x,
y = marker_axis_LD_y, yend = marker_axis_genic_y)
link_ld_data <- link_ld_data[link_ld_data$xend %in% link_association_structure$Site,
]
link_LD_genic_structure <- geom_segment(data = link_ld_data, aes(x = x,
xend = xend, y = y, yend = yend), colour = "red", linetype = "longdash")
} else {
link_LD_genic_structure <- list(NULL)
}
y_axis_text <- ifelse(unique(transcript_corrdination$V7) == "-", list(geom_text(aes(x = transcript_max +
(transcript_max - transcript_min)/6.5, y = mean(pvalue_range) *
fold), label = "atop(-log[10]*italic(P)[observed])", parse = T,
angle = 90)), list(geom_text(aes(x = transcript_min - (transcript_max -
transcript_min)/6.5, y = mean(pvalue_range) * fold), label = "atop(-log[10]*italic(P)[observed])",
parse = T, angle = 90)))
if (isTRUE(triangleLD)) {
xtext <- list(geom_text(aes(x = (transcript_max + transcript_min)/2,
y = min(poly_data$y) - 10 * distance, label = transcript)))
} else {
xtext <- list(geom_text(aes(x = (transcript_max + transcript_min)/2,
y = -(transcript_max - transcript_min)/10, label = transcript)))
}
plot <- ggplot() + geom_point(data = transcript_association, aes(Site,
-log10(p) * fold), colour = "black") + ld_leadsnp_colour + transcript_intron_structure +
transcript_structure_exon_list + transcript_structure_utr_list +
transcript_structure_cds_list + link_asso_gene + link_LD_genic_structure +
scale_x + scale_y_line + scale_y_ticks + scale_y_text + threshold_line +
bottom_trianglLD + y_axis_text + xtext + theme_bw() + theme(legend.key = element_rect(colour = "black"),
axis.title.x = element_blank(), axis.ticks = element_blank(), panel.border = element_blank(),
panel.grid = element_blank(), axis.text = element_blank(), axis.title.y = element_blank(),
text = element_text(size = 15, face = "bold"))
return(plot)
}
}
}
whweve/wisassoplot2 documentation built on May 15, 2019, 9:56 p.m.
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#' @title plot association with LD and annotation at a given gene
#' @description This function plot the association with
#' linkage disequiblism and annotation at the level of a single gene.
#' @author Hongwei Wang <\email{whweve@163.com}>
#' @param transcript the transcript of gene, required.
#' @param gtf the annotation file, required.
#' @param association the association table, required.
#' @param hapmap the genotype file for computing leadsnpLD in the format of hapmap. The file should be the same file used for coumputing association. required.
#' @param hapmap_ld the genotype file for computing trangleLD in the format of hapmap, not required. If hapmap_ld was not provided, hapmap would be used.
#' @param slide_length the sliding window length for computing LD, default -1.
#' @param threadN the number of (CPU) cores used for computing LD, default 1.
#' @param up the upper distance from the start position of gene
#' @param down the down distance from the end position of gene
#' @param threshold the significant level of the assocition, default NULL.
#' @param ldstatistics the statistics used for computing LD, default rsquare, and the optional is dprime.
#' @param leadsnp snp name provided by user
#' @param link2gene link the locis that passed the threshold to the genic structure, default TRUE.
#' @param triangleLD show LD in the format lile triangle, default TRUE.
#' @param link2LD link the locis that passed the threshold to the LD, default TRUE.
#' @param leadsnpLD show LD of the locis when compared with the most significant loci, default TRUE.
#' @param exon_colour the colour of exon, default gray.
#' @param cds_colour the colour of cds, default black.
#' @param utr_colour the colour of utr, default gray.
#' @param intron_colour the colour of intron, default gray.
#' @param colour02 the colour of LD statistics ranged between 0.0 and 0.2, default gray.
#' @param colour04 the colour of LD statistics ranged between 0.2 and 0.4, default cyan.
#' @param colour06 the colour of LD statistics ranged between 0.4 and 0.6, default green.
#' @param colour08 the colour of LD statistics ranged between 0.6 and 0.8, default yellow.
#' @param colour10 the colour of LD statistics ranged between 0.8 and 1.0, default red.
#' @return ggplot2 plot
#' @export
#' @import ggplot2 genetics reshape2
#' @examples
#' data(gtf)
#' data(zmvpp1_association)
#' data(zmvpp1_hapmap)
#' plot_gene('GRMZM2G170927_T01',gtf,association=zmvpp1_association,hapmap=zmvpp1_hapmap,hapmap_ld = zmvpp1_hapmap,threshold=8,up=500,down=600,leadsnpLD = FALSE)
plot_gene <- function(transcript, gtf, association, hapmap, hapmap_ld = NULL, slide_length = -1,
threadN = 1, up = NULL, down = NULL, threshold = NULL, ldstatistics = "rsq",
leadsnp = NULL, link2gene = TRUE, triangleLD = TRUE, link2LD = TRUE, leadsnpLD = TRUE,
exon_colour = "gray", cds_colour = "black", utr_colour = "gray", intron_colour = "gray",
colour02 = "gray", colour04 = "cyan", colour06 = "green", colour08 = "yellow",
colour10 = "red") {
if (sum(grepl(transcript, gtf$V9)) == 0) {
stop("please provide the correct transcript or the gtf file")
} else {
transcript_corrdination <- gtf[grepl(transcript, gtf$V9), ]
chromosome_association <- association[association$Locus == unique(transcript_corrdination$V1),
]
transcript_corrdination <- gtf[grepl(transcript, gtf$V9), ]
transcript_min <- ifelse(is.null(up), min(transcript_corrdination$V4), min(transcript_corrdination$V4) -
up)
transcript_max <- ifelse(is.null(down), max(transcript_corrdination$V5),
max(transcript_corrdination$V5) + down)
transcript_association <- chromosome_association[chromosome_association$Site >=
transcript_min & chromosome_association$Site <= transcript_max, ]
transcript_association <- transcript_association[order(transcript_association$Site),
]
if (dim(transcript_association)[1] == 0) {
stop("no association observed")
} else {
# compute the meta variable
pvalue_range <- pretty(-log10(transcript_association$p))
# adjust the yaxis to fit in the LD plot
fold <- ((transcript_max - transcript_min) * 2/3)/max(pvalue_range)
n_pvalue_range <- length(pvalue_range)
marker_number = dim(transcript_association)[1]
length = (transcript_max - transcript_min)
distance = 0.5 * length/(marker_number - 1)
# transcript start and end
for (struct in c("utr", "cds", "exon")) {
assign(paste0("transcript_structure_", struct), transcript_corrdination[grep(struct,
transcript_corrdination$V3, ignore.case = T), ])
if (dim(get(paste0("transcript_structure_", struct)))[1] > 0) {
assign(paste0("transcript_structure_", struct, "_list"), list(geom_segment(data = get(paste0("transcript_structure_",
struct)), aes(x = V4, xend = V5, y = -max(pvalue_range) * fold/30,
yend = -max(pvalue_range) * fold/30), colour = get(paste0(struct,
"_colour")), size = 4)))
} else {
assign(paste0("transcript_structure_", struct, "_list"), NULL)
}
}
transcript_intron_structure <- list(geom_segment(aes(x = transcript_min,
xend = transcript_max, y = -max(pvalue_range) * fold/30, yend = -max(pvalue_range) *
fold/30), colour = intron_colour, size = 1))
# decide whether to rotate x axis
scale_x <- ifelse(unique(transcript_corrdination$V7) == "-", list(scale_x_reverse(limits = c((transcript_max -
transcript_min)/6 + transcript_max, transcript_min), breaks = seq(transcript_max,
transcript_min, transcript_min - transcript_max))), list(scale_x_continuous(limits = c(transcript_min -
(transcript_max - transcript_min)/6, transcript_max), breaks = seq(transcript_min,
transcript_max, transcript_max - transcript_min))))
# label the yaxis
scale_y_line <- ifelse(unique(transcript_corrdination$V7) == "-", list(geom_segment(aes(x = (transcript_max -
transcript_min)/30 + transcript_max, y = min(pvalue_range), xend = (transcript_max -
transcript_min)/30 + transcript_max, yend = max(pvalue_range) *
fold))), list(geom_segment(aes(x = transcript_min - (transcript_max -
transcript_min)/30, y = min(pvalue_range), xend = transcript_min -
(transcript_max - transcript_min)/30, yend = max(pvalue_range) *
fold))))
scale_y_ticks <- ifelse(unique(transcript_corrdination$V7) == "-", list(geom_segment(aes(x = rep((transcript_max -
transcript_min)/15 + transcript_max, n_pvalue_range), y = pvalue_range *
fold, xend = (transcript_max - transcript_min)/30 + transcript_max,
yend = pvalue_range * fold))), list(geom_segment(aes(x = rep(transcript_min -
(transcript_max - transcript_min)/15, n_pvalue_range), y = pvalue_range *
fold, xend = rep(transcript_min - (transcript_max - transcript_min)/30,
n_pvalue_range), yend = pvalue_range * fold))))
scale_y_text <- ifelse(unique(transcript_corrdination$V7) == "-", list(geom_text(aes(x = rep((transcript_max -
transcript_min)/12 + transcript_max, n_pvalue_range), y = pvalue_range *
fold, label = pvalue_range))), list(geom_text(aes(x = rep(transcript_min -
(transcript_max - transcript_min)/12, n_pvalue_range), y = pvalue_range *
fold, label = pvalue_range))))
# add threshold line
if (is.null(threshold)) {
threshold_line <- list(NULL)
}
if (all(length(threshold) > 0, threshold <= max(pvalue_range))) {
threshold_line <- list(geom_segment(aes(x = transcript_min, xend = transcript_max,
y = threshold * fold, yend = threshold * fold), linetype = "longdash",
colour = "gray"))
}
if (all(length(threshold) > 0, threshold > max(pvalue_range))) {
threshold_line <- list(NULL)
print("no -log10(p) pass the threshold, will not draw threshold line")
}
# compute the LD, leadsnp or triangle
if (any(isTRUE(leadsnpLD), isTRUE(triangleLD)) & is.null(hapmap)) {
print("no hapmap data found, please provide the hapmap")
ld_leadsnp_colour <- list(NULL)
bottom_trianglLD = list(NULL)
}
if (all(!isTRUE(leadsnpLD), !isTRUE(triangleLD), !is.null(hapmap))) {
ld_leadsnp_colour <- list(NULL)
bottom_trianglLD <- list(NULL)
}
# link association and LD for the significant loci link between LD and genic
# structure
if (any(isTRUE(leadsnpLD), isTRUE(triangleLD)) & !is.null(hapmap)) {
names(hapmap) <- sub("#", "", names(hapmap))
gene_snp <- hapmap[hapmap$chrom == unique(transcript_corrdination$V1) &
hapmap$pos >= transcript_min & hapmap$pos <= transcript_max, ]
# gene_snp = hapmap2
names(gene_snp) <- sub("#", "", names(gene_snp))
gene_snp <- gene_snp[!duplicated(gene_snp$rs), ]
# convert the SNP to numeric format
major_allele <- paste0(substr(gene_snp$allele, 1, 1), substr(gene_snp$allele,
1, 1))
minor_allele <- paste0(substr(gene_snp$allele, 3, 3), substr(gene_snp$allele,
3, 3))
heter_left <- paste0(substr(gene_snp$allele, 1, 1), substr(gene_snp$allele,
3, 3))
heter_right <- paste0(substr(gene_snp$allele, 3, 3), substr(gene_snp$allele,
1, 1))
# if allele equal to major allele, 0, else 2
for (j in 12:dim(gene_snp)[2]) {
gene_snp[gene_snp[, j] == major_allele, j] = 2
gene_snp[gene_snp[, j] == minor_allele, j] = 0
gene_snp[gene_snp[, j] == "NN", j] = NA
heter_position_left <- which(isTRUE(gene_snp[, j] == heter_left))
heter_position_right <- which(isTRUE(gene_snp[, j] == heter_right))
if (length(heter_position_left) > 1) {
gene_snp[heter_position_left, j] = 1
}
if (length(heter_position_right) > 1) {
gene_snp[heter_position_right, j] = 1
}
}
gene_snp2 <- gene_snp[, 12:dim(gene_snp)[2]]
gene_snp2 <- as.matrix(sapply(gene_snp2, as.numeric))
snpgdsCreateGeno("test.gds", genmat = gene_snp2, sample.id = names(gene_snp)[12:dim(gene_snp)[2]],
snp.id = gene_snp$rs, snp.position = gene_snp$pos, snp.allele = gene_snp$alleles,
snpfirstdim = TRUE)
genofile <- snpgdsOpen("test.gds")
if (ldstatistics == "rsq") {
aa = snpgdsLDMat(genofile, slide = slide_length, method = "corr",
num.thread = threadN)
}
if (ldstatistics == "dprime") {
aa = snpgdsLDMat(genofile, slide = slide_length, method = "dprime",
num.thread = threadN)
}
snpgdsClose(genofile)
ld = aa$LD
if (ldstatistics == "rsq")
ld <- ld^2
names(ld) <- gene_snp$rs
ld <- melt(ld)
marker_info <- data.frame(index = 1:dim(gene_snp)[1], marker_name = gene_snp$rs)
ld$Var1 <- marker_info$marker[match(ld$Var1, marker_info$index)]
ld$Var2 <- marker_info$marker[match(ld$Var2, marker_info$index)]
if (ldstatistics == "rsq") {
lengend_name = expression(italic(r)^2)
} else if (ldstatistics == "dprime") {
lengend_name = expression(D * {
"'"
})
}
ld <- ld[!is.na(ld$value), ]
ld_reverse <- data.frame(Var1 = ld$Var2, Var2 = ld$Var1, value = ld$value)
ld <- rbind(ld, ld_reverse)
marker_pos <- transcript_association[, c("Marker", "Site")]
ld$Site1 <- marker_pos$Site[match(ld$Var1, marker_pos$Marker)]
ld$Site2 <- marker_pos$Site[match(ld$Var2, marker_pos$Marker)]
# ld <- merge(ld,marker_pos,by.x='Var1',by.y = 'Marker') ld <-
# merge(ld,marker_pos,by.x='Var2',by.y = 'Marker') names(ld) =
# sub('Site.x','Site1',names(ld)) names(ld) = sub('Site.y','Site2',names(ld))
if (isTRUE(leadsnpLD)) {
if (is.null(leadsnp)) {
leadsnp <- as.character(transcript_association[which.min(transcript_association$p),
"Marker"])
}
if (!is.null(leadsnp)) {
leadsnp <- leadsnp
}
ld_leadsnp <- ld[ld$Var1 == leadsnp, ]
ld_leadsnp <- merge(ld_leadsnp, transcript_association, by.x = "Var2",
by.y = "Marker")
ld_leadsnp$R2 <- 0.2 * (ld_leadsnp$value%/%0.2 + as.logical(ld_leadsnp$value%/%0.2))
ld_leadsnp$R2 <- as.character(ld_leadsnp$R2)
ld_leadsnp$R2[ld_leadsnp$R2 == "0"] = "0.2"
ld_leadsnp$R2[ld_leadsnp$R2 == "1.2"] = "1"
if (length(which(ld_leadsnp$Var1 == leadsnp & ld_leadsnp$Var2 ==
leadsnp)) >= 1) {
ld_leadsnp <- ld_leadsnp[!(ld_leadsnp$Var1 == leadsnp & ld_leadsnp$Var2 ==
leadsnp), ]
}
ld_leadsnp_colour <- list(geom_point(data = ld_leadsnp, aes(Site2,
-log10(p) * fold, fill = R2), pch = 21, colour = "black"), scale_fill_manual(values = c(`0.2` = colour02,
`0.4` = colour04, `0.6` = colour06, `0.8` = colour08, `1` = colour10),
labels = c("0-0.2", "0.2-0.4", "0.4-0.6", "0.6-0.8", "0.8-1.0"),
name = lengend_name))
}
if (!isTRUE(leadsnpLD)) {
ld_leadsnp_colour <- list(NULL)
}
if (isTRUE(triangleLD)) {
if (is.null(hapmap_ld)) {
hapmap_ld <- hapmap
}
hapmap_ld <- hapmap_ld[hapmap_ld$chrom == unique(transcript_corrdination$V1) &
hapmap_ld$pos >= transcript_min & hapmap_ld$pos <= transcript_max,
]
marker_number = dim(hapmap_ld)[1]
length = (transcript_max - transcript_min)
distance = 0.5 * length/(marker_number - 1)
names(hapmap_ld) <- sub("#", "", names(hapmap_ld))
gene_snp <- hapmap_ld
names(gene_snp) <- sub("#", "", names(gene_snp))
gene_snp <- gene_snp[!duplicated(gene_snp$rs), ]
# convert the SNP to numeric format
major_allele <- paste0(substr(gene_snp$allele, 1, 1), substr(gene_snp$allele,
1, 1))
minor_allele <- paste0(substr(gene_snp$allele, 3, 3), substr(gene_snp$allele,
3, 3))
heter_left <- paste0(substr(gene_snp$allele, 1, 1), substr(gene_snp$allele,
3, 3))
heter_right <- paste0(substr(gene_snp$allele, 3, 3), substr(gene_snp$allele,
1, 1))
# if allele equal to major allele, 0, else 2
for (j in 12:dim(gene_snp)[2]) {
gene_snp[gene_snp[, j] == major_allele, j] = 2
gene_snp[gene_snp[, j] == minor_allele, j] = 0
gene_snp[gene_snp[, j] == "NN", j] = NA
heter_position_left <- which(isTRUE(gene_snp[, j] == heter_left))
heter_position_right <- which(isTRUE(gene_snp[, j] == heter_right))
if (length(heter_position_left) > 1) {
gene_snp[heter_position_left, j] = 1
}
if (length(heter_position_right) > 1) {
gene_snp[heter_position_right, j] = 1
}
}
gene_snp2 <- gene_snp[, 12:dim(gene_snp)[2]]
gene_snp2 <- as.matrix(sapply(gene_snp2, as.numeric))
snpgdsCreateGeno("test.gds", genmat = gene_snp2, sample.id = names(gene_snp)[12:dim(gene_snp)[2]],
snp.id = gene_snp$rs, snp.position = gene_snp$pos, snp.allele = gene_snp$alleles,
snpfirstdim = TRUE)
genofile <- snpgdsOpen("test.gds")
if (ldstatistics == "rsq") {
aa = snpgdsLDMat(genofile, slide = slide_length, method = "corr",
num.thread = threadN)
}
if (ldstatistics == "dprime") {
aa = snpgdsLDMat(genofile, slide = slide_length, method = "dprime",
num.thread = threadN)
}
snpgdsClose(genofile)
ld = aa$LD
if (ldstatistics == "rsq")
ld <- ld^2
names(ld) <- gene_snp$rs
ld <- melt(ld)
marker_info <- data.frame(index = 1:dim(gene_snp)[1], marker_name = gene_snp$rs)
ld$Var1 <- marker_info$marker[match(ld$Var1, marker_info$index)]
ld$Var2 <- marker_info$marker[match(ld$Var2, marker_info$index)]
if (ldstatistics == "rsq") {
lengend_name = expression(italic(r)^2)
} else if (ldstatistics == "dprime") {
lengend_name = expression(D * {
"'"
})
}
ld <- ld[!is.na(ld$value), ]
ld_reverse <- data.frame(Var1 = ld$Var2, Var2 = ld$Var1, value = ld$value)
ld <- rbind(ld, ld_reverse)
marker_pos <- hapmap_ld[, c("rs", "pos")]
ld$Site1 <- marker_pos$pos[match(ld$Var1, marker_pos$rs)]
ld$Site2 <- marker_pos$pos[match(ld$Var2, marker_pos$rs)]
# ld <- merge(ld,marker_pos,by.x='Var1',by.y = 'rs') ld <-
# merge(ld,marker_pos,by.x='Var2',by.y = 'rs') names(ld) =
# sub('pos.x','Site1',names(ld)) names(ld) = sub('pos.y','Site2',names(ld))
# compute the LD position, the sequence ranged from small to big
marker_pair = NULL
center_x = NULL
center_y = NULL
locib <- rep(1:(marker_number-1),(marker_number-1):1)
locia <- NULL
for (row in 1:(marker_number - 1)) {
locia <- c(locia,seq(1:(marker_number-row)))
}
marker_pair <- paste0(locia,"_",locia+locib)
center_x <- distance*(locia+locia+locib-2)
center_y <- -locib*distance
upper_center_x <- center_x
upper_center_y <- center_y + distance
lower_center_x <- center_x
lower_center_y <- center_y - distance
left_center_x <- center_x - distance
left_center_y <- center_y
right_center_x <- center_x + distance
right_center_y <- center_y
poly_data <- data.frame(group = rep(marker_pair, 4), x = c(upper_center_x,
right_center_x, lower_center_x, left_center_x) + transcript_min,
y = c(upper_center_y, right_center_y, lower_center_y, left_center_y) -
4 * max(pvalue_range) * fold/30, label = rep(c(1, 2, 3, 4),
each = length(upper_center_x)))
poly_data$marker1 <- sub("([0-9]+)_[0-9]+", "\\1", poly_data$group)
poly_data$marker2 <- sub("[0-9]+_([0-9]+)", "\\1", poly_data$group)
# transcript_association <-
# transcript_association[order(transcript_association$Site),]
# transcript_association$marker_number <- 1:dim(transcript_association)[1]
# marker_index <- transcript_association[,c('Marker','marker_number')]
hapmap_ld <- hapmap_ld[order(hapmap_ld$pos), ]
hapmap_ld$marker_number <- 1:dim(hapmap_ld)[1]
marker_index <- hapmap_ld[, c("rs", "marker_number")]
poly_data$Var1 <- marker_index$rs[match(poly_data$marker1, marker_index$marker_number)]
poly_data$Var2 <- marker_index$rs[match(poly_data$marker2, marker_index$marker_number)]
# poly_data <- merge(poly_data,marker_index,by.x='marker1',by.y =
# 'marker_number') poly_data <- merge(poly_data,marker_index,by.x='marker2',by.y
# = 'marker_number') names(poly_data) = sub('rs.x','Var1',names(poly_data))
# names(poly_data) = sub('rs.y','Var2',names(poly_data))
poly_data$value <- ld$value[match(paste0(poly_data$Var1, "/",
poly_data$Var2), paste0(ld$Var1, "/", ld$Var2))]
poly_data$Site1 <- ld$Site1[match(paste0(poly_data$Var1, "/",
poly_data$Var2), paste0(ld$Var1, "/", ld$Var2))]
poly_data$Site2 <- ld$Site2[match(paste0(poly_data$Var1, "/",
poly_data$Var2), paste0(ld$Var1, "/", ld$Var2))]
# poly_data <- merge(poly_data,ld,by.x=c('Var1','Var2'),by.y = c('Var1','Var2'))
poly_data$R2 <- 0.2 * (poly_data$value%/%0.2 + as.logical(poly_data$value%/%0.2))
poly_data$R2 <- as.character(poly_data$R2)
poly_data$R2[poly_data$R2 == "0"] = "0.2"
poly_data$R2[poly_data$R2 == "1.2"] = "1"
poly_data <- poly_data[order(poly_data$group, poly_data$label),
]
if (!isTRUE(leadsnpLD)) {
bottom_trianglLD = list(geom_polygon(data = poly_data, aes(group = group,
x = x, y = y - (transcript_max - transcript_min)/50, fill = R2)),
scale_fill_manual(values = c(`0.2` = colour02, `0.4` = colour04,
`0.6` = colour06, `0.8` = colour08, `1` = colour10), labels = c("0-0.2",
"0.2-0.4", "0.4-0.6", "0.6-0.8", "0.8-1.0"), name = lengend_name))
}
if (isTRUE(leadsnpLD)) {
bottom_trianglLD = list(geom_polygon(data = poly_data, aes(group = group,
x = x, y = y - (transcript_max - transcript_min)/50, fill = R2)))
}
}
if (!isTRUE(triangleLD)) {
bottom_trianglLD <- list(NULL)
}
}
# link line from significant loci to the strucuture
if (!isTRUE(link2gene) & any(!is.null(threshold), is.null(threshold))) {
link_asso_gene <- list(NULL)
}
if (isTRUE(link2gene) & is.null(threshold)) {
print("threshold acquired")
link_asso_gene <- list(NULL)
}
if (isTRUE(link2gene) & !is.null(threshold)) {
link_association_structure <- transcript_association[-log10(transcript_association$p) >=
threshold, ]
link_association_structure <- link_association_structure[!duplicated(link_association_structure$p),
]
if (dim(link_association_structure)[1] == 0) {
print("no -log10(p) pass the threshold, will not draw link")
link_asso_gene <- list(NULL)
threshold_line <- list(NULL)
}
if (dim(link_association_structure)[1] > 0) {
link_association_structure <- transcript_association[-log10(transcript_association$p) >=
threshold, ]
link_association_structure <- link_association_structure[!duplicated(link_association_structure$p),
]
link_number <- dim(link_association_structure)[1]
link_asso_gene <- list(geom_segment(data = link_association_structure,
aes(x = Site, xend = Site, y = rep(-max(pvalue_range) * fold/30,
link_number), yend = -log10(p) * fold), linetype = "longdash",
colour = "red"))
}
}
if (isTRUE(triangleLD) & isTRUE(link2gene) & isTRUE(link2LD)) {
link_association_structure <- transcript_association[-log10(transcript_association$p) >=
threshold, ]
link_association_structure <- link_association_structure[!duplicated(link_association_structure$p),
]
link_number <- dim(link_association_structure)[1]
link_asso_gene <- list(geom_segment(data = link_association_structure,
aes(x = Site, xend = Site, y = rep(-max(pvalue_range) * fold/30,
link_number), yend = -log10(p) * fold), linetype = "longdash",
colour = "red"))
marker_axis_LD_x <- transcript_min + (seq(1:marker_number) - 1) *
2 * distance
marker_axis_genic_x <- hapmap_ld$pos
marker_axis_LD_y <- rep(-4 * max(pvalue_range) * fold/30, marker_number)
marker_axis_genic_y <- rep(-max(pvalue_range) * fold/30, marker_number)
link_ld_data <- data.frame(x = marker_axis_LD_x, xend = marker_axis_genic_x,
y = marker_axis_LD_y, yend = marker_axis_genic_y)
link_ld_data <- link_ld_data[link_ld_data$xend %in% link_association_structure$Site,
]
link_LD_genic_structure <- geom_segment(data = link_ld_data, aes(x = x,
xend = xend, y = y, yend = yend), colour = "red", linetype = "longdash")
} else {
link_LD_genic_structure <- list(NULL)
}
y_axis_text <- ifelse(unique(transcript_corrdination$V7) == "-", list(geom_text(aes(x = transcript_max +
(transcript_max - transcript_min)/6.5, y = mean(pvalue_range) *
fold), label = "atop(-log[10]*italic(P)[observed])", parse = T,
angle = 90)), list(geom_text(aes(x = transcript_min - (transcript_max -
transcript_min)/6.5, y = mean(pvalue_range) * fold), label = "atop(-log[10]*italic(P)[observed])",
parse = T, angle = 90)))
if (isTRUE(triangleLD)) {
xtext <- list(geom_text(aes(x = (transcript_max + transcript_min)/2,
y = min(poly_data$y) - 10 * distance, label = transcript)))
} else {
xtext <- list(geom_text(aes(x = (transcript_max + transcript_min)/2,
y = -(transcript_max - transcript_min)/10, label = transcript)))
}
plot <- ggplot() + geom_point(data = transcript_association, aes(Site,
-log10(p) * fold), colour = "black") + ld_leadsnp_colour + transcript_intron_structure +
transcript_structure_exon_list + transcript_structure_utr_list +
transcript_structure_cds_list + link_asso_gene + link_LD_genic_structure +
scale_x + scale_y_line + scale_y_ticks + scale_y_text + threshold_line +
bottom_trianglLD + y_axis_text + xtext + theme_bw() + theme(legend.key = element_rect(colour = "black"),
axis.title.x = element_blank(), axis.ticks = element_blank(), panel.border = element_blank(),
panel.grid = element_blank(), axis.text = element_blank(), axis.title.y = element_blank(),
text = element_text(size = 15, face = "bold"))
return(plot)
}
}
}
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