#' @title Annotate integration sites by repeats and microsatellites.
#'
#' @description
#' Annotate vector integration sites by repeat and microsatellite data.
#'
#' @usage
#' annoByRepeat(hits, ran_hits = NULL,
#' mapTool = 'blast',
#' organism = 'GRCh37',
#' interval = 5000,
#' range = c(-20000, 20000),
#' outPath = getwd(),
#' outFileName = paste0('RIPAT', round(unclass(Sys.time()))))
#'
#' @param hits a GR object. This object made by \code{\link{makeInputObj}} function.
#' @param hits GR object. This object made by \code{\link{makeExpSet}} function.
#' @param ran_hits GR object or list. This object is output of \code{\link{makeRanSet}} function.
#' @param mapTool Character. Function uses two types of object\cr from BLAST and BLAT.
#' Default is 'blast'. If you want to use BLAT result, use 'blat'.
#' @param organism Character. This function can run by two versions of organisms\cr
#' such as GRCh37, GRCh38 (Human). Default is 'GRCh37'.
#' @param interval Integer. This number means interval number\cr for
#' distribution analysis. Default is 5000.
#' @param range Integer array. The range of highlight region for analysis.\cr
#' Default range is \code{c(-20000, 20000)}.
#' @param outPath String. Plots are saved in this path. \cr Default value is R home directory.
#' @param outFileName Character. Attached ID to the result file name.
#'
#' @return Return a result list that is made up of insertion and distribution result tables
#' and GenomicRange object of Rpeat and microsatellite data.
#'
#' @examples
#' data(blast_obj); data(repeat_exam_db); data(micro_exam_db)
#' saveRDS(repeat_exam_db,
#' paste0(system.file("extdata", package = 'RIPAT'),
#' '/GRCh37_repeat.rds'))
#' saveRDS(micro_exam_db,
#' paste0(system.file("extdata", package = 'RIPAT'),
#' '/GRCh37_microsat.rds'))
#'
#' blast_repeat = annoByRepeat(hits = blast_obj, ran_hits = NULL,
#' outFileName = 'blast_res')
#'
#' @export
annoByRepeat = function(hits, ran_hits = NULL, mapTool = 'blast', organism = 'GRCh37', interval = 5000, range = c(-20000, 20000), outPath = getwd(), outFileName = paste0('RIPAT', round(unclass(Sys.time())))){
message('----- Annotate integration sites. (Time : ', date(), ')')
message('- Validate options')
if(length(which(c('blast', 'blat') %in% mapTool)) == 0){stop("[ERROR] Please confirm the alignment tool name.\n----- This process is halted. (Time : ", date(), ")\n")}
if(length(which(c('GRCh37', 'GRCh38') %in% organism)) == 0){stop("[ERROR] Please use GRCh37/GRCh38 data.\n----- This process is halted. (Time : ", date(), ")\n")}
if(stringr::str_ends(outPath, pattern = '/')){outPath = stringr::word(outPath, start = 1, end = nchar(outPath), sep = '')}
if(range[1] - range[2] >= 0){
stop("[ERROR] Please check distribution range.\n----- This process is halted. (Time : ", date(), ")\n")
} else {ranges = seq(from = range[1], to = range[2], by = interval)}
message('- OK!')
message('- Load the dataset.')
dbPath = system.file("extdata", package = "RIPAT")
dbFile = paste0('/', organism, '_repeat.rds')
dataTable = data.frame(readRDS(paste0(dbPath, dbFile)), stringsAsFactors = FALSE)
colnames(dataTable) = c('chr', 'start', 'end', 'strand','repName', 'repClass', 'repFamily')
dbFile2 = paste0('/', organism, '_microsat.rds')
dataTable_micro = data.frame(readRDS(paste0(dbPath, dbFile2)), stringsAsFactors = FALSE)
colnames(dataTable_micro) = c('chr', 'start', 'end', 'name')
dataTable$chr = as.character(dataTable$chr); dataTable_micro$chr = as.character(dataTable_micro$chr)
gr_repeat = GenomicRanges::makeGRangesFromDataFrame(dataTable, keep.extra.columns = TRUE, ignore.strand = FALSE)
gr_micro = GenomicRanges::makeGRangesFromDataFrame(dataTable_micro, keep.extra.columns = TRUE, ignore.strand = TRUE)
message('- OK!')
message('- Find integration sites located in repeats.')
inside_repeat_only = as.data.frame(GenomicRanges::findOverlaps(hits[[1]], gr_repeat, type = 'any', ignore.strand = TRUE), stringsAsFactors = FALSE)
inside_micro_only = as.data.frame(GenomicRanges::findOverlaps(hits[[1]], gr_micro, type = 'any', ignore.strand = TRUE), stringsAsFactors = FALSE)
only_res_que = data.frame(hits[[1]][inside_repeat_only$queryHits,], stringsAsFactors = FALSE)[,c(1:3,6:8)]
only_res_sub = dataTable[inside_repeat_only$subjectHits,]
only_res_que_m = data.frame(hits[[1]][inside_micro_only$queryHits,], stringsAsFactors = FALSE)[,c(1:3,6:8)]
only_res_sub_m = dataTable_micro[inside_micro_only$subjectHits,]
inside_tab = unique(cbind(only_res_que, only_res_sub)[,c(4,1:3,5,6,11,7:10,12,13)])
inside_tab_m = unique(cbind(only_res_que_m, only_res_sub_m)[,c(4,1:3,5,6,7:10)])
names(inside_tab) = c('q_name', 'q_chr', 'q_start', 'q_end', 'identity', 'align_length', 'rep_name', 'chr', 'start', 'end', 'strand', 'repClass', 'repFamily')
names(inside_tab_m) = c('q_name', 'q_chr', 'q_start', 'q_end', 'identity', 'align_length', 'chr', 'start', 'end', 'microName')
message('- OK!')
message('- Calculate distance.')
strp = dataTable[which(dataTable$strand == '+'),]; strn = dataTable[which(dataTable$strand == '-'),]
only_hits_tab = data.frame(hits[[1]], stringsAsFactors = FALSE)
dist_only = lapply(c(1:nrow(only_hits_tab)), function(a){
x = only_hits_tab$start[a]; y = only_hits_tab$query[a]; z = as.character(only_hits_tab$seqnames)[a]
cal1p = strp$start-x; cal2p = strp$end-x; cal1n = strn$end-x; cal2n = strn$start-x
cal1_ip = intersect(which(cal1p <= abs(range[1])), which(cal1p > 0)); cal2_ip = intersect(which(abs(cal2p) <= range[2]), which(cal2p < 0))
cal1_in = intersect(which(cal1n >= range[1]), which(cal1n < 0)); cal2_in = intersect(which(cal2n <= range[2]), which(cal2n > 0))
dat = data.frame(rbind(strp[c(cal1_ip, cal2_ip),], strn[c(cal1_in, cal2_in),]), dist = c(-c(cal1p[cal1_ip], cal2p[cal2_ip]), cal1n[cal1_in], cal2n[cal2_in]))
dat = unique(data.frame('query' = rep(y, nrow(dat)), dat))
dat = dat[which(dat$chr == z),]
dat = dat[order(abs(dat$dist), decreasing = FALSE),][1,]
cal1m = dataTable_micro$start-x; cal2m = dataTable_micro$end-x
cal1_im = intersect(which(cal1m <= abs(range[1])), which(cal1m > 0))
cal2_im = intersect(which(abs(cal2m) <= range[2]), which(cal2m < 0))
dat_m = data.frame(dataTable_micro[c(cal1_im, cal2_im),], dist = -c(cal1m[cal1_im], cal2m[cal2_im]))
dat_m = unique(data.frame('query' = rep(y, nrow(dat_m)), dat_m))
dat_m = dat_m[which(dat_m$chr == z),]
dat_m = dat_m[order(abs(dat_m$dist), decreasing = FALSE),][1,]
return(list(dat, dat_m))
})
hist_only_r = hist(unlist(lapply(dist_only, function(x){x[[1]]$dist/1000})), breaks = ranges/1000, plot = FALSE)
hist_only_m = hist(unlist(lapply(dist_only, function(x){x[[2]]$dist/1000})), breaks = ranges/1000, plot = FALSE)
message('- OK!')
if(!is.null(ran_hits)){
message('- Do random set analysis.')
randomSize = length(ran_hits); gr_random = ran_hits
random_set = data.frame(c(1:randomSize), data.frame(ran_hits), stringsAsFactors = FALSE)[,c(1:3)]; names(random_set) = c('Random', 'Random_chr', 'Random_pos')
inside_repeat_ran = as.data.frame(GenomicRanges::findOverlaps(gr_random, gr_repeat, type = 'any', ignore.strand = TRUE), stringsAsFactors = FALSE)
a = as.data.frame(gr_random[inside_repeat_ran$queryHits,], stringsAsFactors = FALSE)
b = dataTable[inside_repeat_ran$subjectHits,]
inside_repeat_ran_tab = unique(cbind(a,b)[,c(1:3, 10, 6:9, 11, 12)])
names(inside_repeat_ran_tab) = c('q_chr', 'q_start', 'q_end', 'repeat', 'chr', 'start', 'end', 'strand', 'repClass', 'repFamily')
inside_micro_ran = as.data.frame(GenomicRanges::findOverlaps(gr_random, gr_micro, type = 'any', ignore.strand = TRUE), stringsAsFactors = FALSE)
a2 = as.data.frame(gr_random[inside_micro_ran$queryHits,], stringsAsFactors = FALSE)
b2 = dataTable_micro[inside_micro_ran$subjectHits,]
inside_micro_ran_tab = unique(cbind(a2,b2)[,c(1:3, 9, 6:8)])
names(inside_micro_ran_tab) = c('q_chr', 'q_start', 'q_end', 'microsatellite', 'chr', 'start', 'end')
dist_ran = lapply(c(1:nrow(random_set)), function(a){
x = as.numeric(random_set$Random_pos[a]); y = random_set$Random[a]; z = random_set$Random_chr[a]
cal1p = strp$start-x; cal2p = strp$end-x; cal1n = strn$end-x; cal2n = strn$start-x
cal1_ip = intersect(which(cal1p <= abs(range[1])), which(cal1p > 0)); cal2_ip = intersect(which(abs(cal2p) <= range[2]), which(cal2p < 0))
cal1_in = intersect(which(cal1n >= range[1]), which(cal1n < 0)); cal2_in = intersect(which(cal2n <= range[2]), which(cal2n > 0))
dat = data.frame(rbind(strp[c(cal1_ip, cal2_ip),], strn[c(cal1_in, cal2_in),]), dist = c(-c(cal1p[cal1_ip], cal2p[cal2_ip]), cal1n[cal1_in], cal2n[cal2_in]))
dat = unique(data.frame('query' = rep(y, nrow(dat)), dat))
dat = dat[which(dat$chr == z),]
dat = dat[order(abs(dat$dist), decreasing = FALSE),][1,]
cal1m = dataTable_micro$start-x; cal2m = dataTable_micro$end-x
cal1_im = intersect(which(cal1m <= abs(range[1])), which(cal1m > 0))
cal2_im = intersect(which(abs(cal2m) <= range[2]), which(cal2m < 0))
dat_m = data.frame(dataTable_micro[c(cal1_im, cal2_im),], dist = -c(cal1m[cal1_im], cal2m[cal2_im]))
dat_m = unique(data.frame('query' = rep(y, nrow(dat_m)), dat_m))
dat_m = dat_m[which(dat_m$chr == z),]
dat_m = dat_m[order(abs(dat_m$dist), decreasing = FALSE),][1,]
return(list(dat, dat_m))
})
all_dist_ran = unlist(lapply(dist_ran, function(x){x[[1]]$dist})); all_dist_m_ran = unlist(lapply(dist_ran, function(x){x[[2]]$dist}))
hist_obj_ran = hist(all_dist_ran, plot = FALSE, breaks = ranges); hist_obj_m_ran = hist(all_dist_m_ran, plot = FALSE, breaks = ranges)
message('- OK!')
} else {message('[WARN] Skip random set analysis.')}
message('- Draw histograms.')
all_dist_only = unlist(lapply(dist_only, function(x){x[[1]]$dist}))
all_dist_m_only = unlist(lapply(dist_only, function(x){x[[2]]$dist}))
hist_obj = hist(all_dist_only, plot = FALSE, breaks = ranges)
hist_obj_m = hist(all_dist_m_only, plot = FALSE, breaks = ranges)
r_dist = list('Decided' = lapply(dist_only, function(x){x[[1]]}))
m_dist = list('Decided' = lapply(dist_only, function(x){x[[2]]}))
if(!is.null(ran_hits)){
count_site = hist_obj$counts; count_site_ran = hist_obj_ran$counts
count_m_site = hist_obj_m$counts; count_m_site_ran = hist_obj_m_ran$counts
count_all = nrow(only_hits_tab)
count_data = data.frame('Range' = factor(rep(ranges[ranges != 0]/1000, 2), levels = ranges[ranges != 0]/1000), 'Group' = c(rep('Observed', length(count_site)), rep('Random', length(count_site_ran))), 'Count' = c(count_site, count_site_ran), 'Freq' = c(count_site/count_all, count_site_ran/randomSize))
count_m_data = data.frame('Range' = factor(rep(ranges[ranges != 0]/1000, 2), levels = ranges[ranges != 0]/1000), 'Group' = c(rep('Observed', length(count_m_site)), rep('Random', length(count_m_site_ran))), 'Count' = c(count_m_site, count_m_site_ran), 'Freq' = c(count_m_site/count_all, count_m_site_ran/randomSize))
} else {
count_site = hist_obj$counts; count_m_site = hist_obj_m$counts
count_all = nrow(only_hits_tab)
count_data = data.frame('Range' = factor(ranges[ranges != 0]/1000, levels = ranges[ranges != 0]/1000), 'Group' = rep('Observed', length(count_site)), 'Count' = count_site, 'Freq' = count_site/count_all)
count_m_data = data.frame('Range' = factor(ranges[ranges != 0]/1000, levels = ranges[ranges != 0]/1000), 'Group' = rep('Observed', length(count_m_site)), 'Count' = count_m_site, 'Freq' = count_m_site/count_all)
}
grDevices::png(paste0(outPath, '/', outFileName, '_distribution_repeat_', organism, '.png'), width = 1200, height = 750)
r_plot = ggplot2::ggplot(count_data) + ggplot2::geom_bar(ggplot2::aes(x = Range, y = Freq, fill = Group), stat = "identity", position = "dodge", width = 0.5) +
ggplot2::lims(y = c(0, max(count_data$Freq)*1.5)) + ggplot2::ggtitle(label = "Random distribution (Repeat)") +
ggplot2::xlab('Intervals (Kbs)') + ggplot2::ylab("Ratio of Integration Events") + ggplot2::scale_fill_manual(values = c('mediumspringgreen', 'mediumpurple')) +
ggplot2::theme(panel.background = ggplot2::element_rect(fill="white", colour = "white"), panel.grid.major = ggplot2::element_line(size = 0.5, linetype = 'dotted', colour = 'black'),
axis.line = ggplot2::element_line(colour = "darkgrey"), legend.title = ggplot2::element_blank(),
legend.key.size = ggplot2::unit(0.7, "cm"), plot.title = ggplot2::element_text(hjust = 0.5, face = "bold", size = 20),
legend.text = ggplot2::element_text(size = 18), axis.text = ggplot2::element_text(size = 17),
axis.title = ggplot2::element_text(size = 18))
print(r_plot)
grDevices::dev.off()
grDevices::png(paste0(outPath, '/', outFileName, '_distribution_microsatellite_', organism, '.png'), width = 1200, height = 750)
m_plot = ggplot2::ggplot(count_m_data) + ggplot2::geom_bar(ggplot2::aes(x = Range, y = Freq, fill = Group), stat = "identity", position = "dodge", width = 0.5) +
ggplot2::lims(y = c(0, max(count_m_data$Freq)*1.5)) + ggplot2::ggtitle(label = "Random distribution (Microsatellite)") +
ggplot2::xlab('Intervals (Kbs)') + ggplot2::ylab("Ratio of Integration Events") + ggplot2::scale_fill_manual(values = c('mediumspringgreen', 'mediumpurple')) +
ggplot2::theme(panel.background = ggplot2::element_rect(fill="white", colour = "white"), panel.grid.major = ggplot2::element_line(size = 0.5, linetype = 'dotted', colour = 'black'),
axis.line = ggplot2::element_line(colour = "darkgrey"), legend.title = ggplot2::element_blank(),
legend.key.size = ggplot2::unit(0.7, "cm"), plot.title = ggplot2::element_text(hjust = 0.5, face = "bold", size = 20),
legend.text = ggplot2::element_text(size = 18), axis.text = ggplot2::element_text(size = 17),
axis.title = ggplot2::element_text(size = 18))
print(m_plot)
grDevices::dev.off()
message('- OK!')
result_list = list(inside_tab, r_dist, count_data, gr_repeat, inside_tab_m, m_dist, count_m_data, gr_micro, organism)
names(result_list) = c('Repeat_inside', 'Repeat_distribution', 'Repeat_plot_data', 'Repeat_data', 'Micro_inside', 'Micro_distribution', 'Micro_plot_data', 'Micro_data', 'Target_ver')
if(!is.null(ran_hits)){
result_list = c(result_list, list(inside_repeat_ran_tab, inside_micro_ran_tab, dist_ran))
names(result_list)[10:12] = c('Repeat_inside_ran', 'Micro_inside_ran', 'Random_distribution')
}
result_list = c(result_list, list('Repeat_hist_plot' = r_plot, 'Microsatellite_hist_plot' = m_plot))
message('----- Finish. (Time : ', date(), ')')
return(result_list)
}
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