Mercurial > repos > petr-novak > dante_ltr

annotate extract_putative_ltr.R @ 5:0c3111ab729b draft

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"planemo upload commit 5a81f1734493a3acf5ff24a573fa2887d92b58a8"
author petr-novak
date Mon, 16 May 2022 07:50:41 +0000
parents f131886ea194
children c33d6583e548
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1 #!/usr/bin/env Rscript
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2 initial_options <- commandArgs(trailingOnly = FALSE)
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3 file_arg_name <- "--file="
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4 script_name <- normalizePath(sub(file_arg_name, "", initial_options[grep(file_arg_name, initial_options)]))
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5 script_dir <- dirname(script_name)
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6 library(optparse)
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7
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8 parser <- OptionParser()
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9 option_list <- list(
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10 make_option(c("-g", "--gff3"), action = "store", type = "character",
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11 help = "gff3 with dante results", default = NULL),
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12 make_option(c("-s", "--reference_sequence"), action = "store", type = "character",
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13 help = "reference sequence as fasta", default = NULL),
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14 make_option(c("-o", "--output"), action = "store", type = "character",
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15 help = "output file path and prefix", default = NULL),
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16 make_option(c("-c", "--cpu"), type = "integer", default = 5,
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17 help = "Number of cpu to use [default %default]", metavar = "number")
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18
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19 )
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20 description <- paste(strwrap(""))
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21
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22 epilogue <- ""
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23 parser <- OptionParser(option_list = option_list, epilogue = epilogue, description = description,
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24 usage = "usage: %prog COMMAND [OPTIONS]")
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25 opt <- parse_args(parser, args = commandArgs(TRUE))
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27
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28 # load packages
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29 suppressPackageStartupMessages({
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30 library(rtracklayer)
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31 library(Biostrings)
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32 library(BSgenome)
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33 library(parallel)
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34 })
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35
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36
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37 # CONFIGURATION
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38 OFFSET <- 15000
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39 # load configuration files and functions:
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40 lineage_file <- paste0(script_dir, "/databases/lineage_domain_order.csv")
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41 trna_db <- paste0(script_dir, "/databases/tRNAscan-SE_ALL_spliced-no_plus-old-tRNAs_UC_unique-3ends.fasta")
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42 ltr_utils_r <- paste0(script_dir, "/R/ltr_utils.R")
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43 if (file.exists(lineage_file) & file.exists(trna_db)) {
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44 lineage_info <- read.table(lineage_file, sep = "\t", header = TRUE, as.is = TRUE)
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45 source(ltr_utils_r)
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46 }else {
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47 lineage_file <- paste0(script_dir, "/../share/dante_ltr/databases/lineage_domain_order.csv")
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48 trna_db <- paste0(script_dir, "/../share/dante_ltr/databases/tRNAscan-SE_ALL_spliced-no_plus-old-tRNAs_UC_unique-3ends.fasta")
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49 ltr_utils_r <- paste0(script_dir, "/../share/dante_ltr/R/ltr_utils.R")
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50 if (file.exists(lineage_file) & file.exists((trna_db))) {
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51 lineage_info <- read.table(lineage_file, sep = "\t", header = TRUE, as.is = TRUE)
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52 source(ltr_utils_r)
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53 }else(
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54 stop("configuration files not found")
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55 )
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56 }
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57
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58
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59 # for testing
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60 if (FALSE) {
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61 g <- rtracklayer::import("/mnt/raid/454_data/cuscuta/Ceuropea_assembly_v4/0_final_asm_hifiasm+longstitch/repeat_annotation/DANTE_on_CEUR_filtered_short_names.gff3")
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62 s <- readDNAStringSet("/mnt/raid/454_data/cuscuta/Ceuropea_assembly_v4/0_final_asm_hifiasm+longstitch/asm.bp.p.ctg_scaffolds.short_names.fa")
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63 lineage_info <- read.table("/mnt/raid/users/petr/workspace/ltr_finder_test/lineage_domain_order.csv", sep = "\t", header = TRUE, as.is = TRUE)
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64
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65 g <- rtracklayer::import("/mnt/raid/users/petr/workspace/ltr_finder_test/test_data
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66 /DANTE_filtered_part.gff3")
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67 s <- readDNAStringSet("/mnt/raid/users/petr/workspace/ltr_finder_test/test_data
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68 /Rbp_part.fa")
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69
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70 g <- rtracklayer::import("/mnt/raid/users/petr/workspace/dante_ltr/test_data
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71 /DANTE_Vfaba_chr5.gff3")
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72 s <- readDNAStringSet("/mnt/ceph/454_data/Vicia_faba_assembly/assembly/ver_210910
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73 /fasta_parts/211010_Vfaba_chr5.fasta")
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74
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75 g <- rtracklayer::import("/mnt/raid/users/petr/workspace/dante_ltr/test_data/big_test_data//Cocoa_theobroma_DANTE_filtered.gff3")
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76 s <- readDNAStringSet("/mnt/raid/users/petr/workspace/dante_ltr/test_data/big_test_data/Cocoa_theobroma_chr1.fasta.gz")
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77
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78 source("R/ltr_utils.R")
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79
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80 g <- rtracklayer::import("./test_data/sample_DANTE.gff3")
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81 s <- readDNAStringSet("./test_data/sample_genome.fasta")
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82 outfile <- "/mnt/raid/users/petr/workspace/ltr_finder_test/te_with_domains_2.gff3"
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83 lineage_info <- read.table("databases/lineage_domain_order.csv", sep = "\t", header =
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84 TRUE, as.is = TRUE)
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85 trna_db <- "./databases/tRNAscan-SE_ALL_spliced-no_plus-old-tRNAs_UC_unique-3ends.fasta"
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86
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87 }
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88
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89 # MAIN #############################################################
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90
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91 # load data:
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92
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93 cat("reading gff...")
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94 g <- rtracklayer::import(opt$gff3, format = 'gff3') # DANTE gff3
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95 cat("done\n")
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96 cat("reading fasta...")
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97 s <- readDNAStringSet(opt$reference_sequence) # genome assembly
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98 cat("done\n")
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99 outfile <- opt$output
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100 # clean sequence names:
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101 names(s) <- gsub(" .+", "", names(s))
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102 lineage_domain <- lineage_info$Domains.order
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103 lineage_offset5prime <- lineage_info$offset5prime
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104 lineage_offset3prime <- lineage_info$offset3prime
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105 ln <- gsub("ss/I", "ss_I", gsub("_", "/", gsub("/", "|", lineage_info$Lineage)))
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106 names(lineage_offset3prime) <- ln
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107 names(lineage_offset5prime) <- ln
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108 names(lineage_domain) <- ln
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109
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110
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111 seqlengths(g) <- seqlengths(s)[names(seqlengths(g))]
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112 g <- add_coordinates_of_closest_neighbor(g)
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113
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114 gcl <- get_domain_clusters(g)
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115 gcl_clean <- clean_domain_clusters(gcl)
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116 # glc annotation
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117 gcl_clean_lineage <- sapply(gcl_clean, function(x) x$Final_Classification[1])
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118 gcl_clean_domains <- sapply(gcl_clean, function(x) ifelse(x$strand[1] == "-",
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119 paste(rev(x$Name), collapse = " "),
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120 paste(x$Name, collapse = " "))
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121 )
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122
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123 # get lineages which has correct number and order of domains
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124 gcl_clean2 <- gcl_clean[gcl_clean_domains == lineage_domain[gcl_clean_lineage]]
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125 gcl_clean_with_domains <- gcl_clean2[check_ranges(gcl_clean2, s)]
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126 gr <- get_ranges(gcl_clean_with_domains)
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127
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128
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129 cat('Number of analyzed regions:\n')
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130 cat('Total number of domain clusters : ', length(gcl), '\n')
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131 cat('Number of clean clusters : ', length(gcl_clean), '\n')
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132 cat('Number of clusters with complete domain set : ', length(gcl_clean_with_domains), '\n')
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133
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134
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135 te_strand <- sapply(gcl_clean_with_domains, function(x)x$strand[1])
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136 te_lineage <- sapply(gcl_clean_with_domains, function(x)x$Final_Classification[1])
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137
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138 max_left_offset <- ifelse(te_strand == "+", lineage_offset5prime[te_lineage], lineage_offset3prime[te_lineage])
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139 max_right_offset <- ifelse(te_strand == "-", lineage_offset5prime[te_lineage], lineage_offset3prime[te_lineage])
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140
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141 grL <- get_ranges_left(gcl_clean_with_domains, max_left_offset)
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142 grR <- get_ranges_right(gcl_clean_with_domains, max_right_offset)
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143
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144 s_left <- getSeq(s, grL)
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145 s_right <- getSeq(s, grR)
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146
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147 # for statistics
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148 RT <- g[g$Name == "RT" & substring(g$Final_Classification, 1, 11) == "Class_I|LTR"]
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149 # cleanup
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150 rm(g)
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151 rm(gcl)
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152 rm(gcl_clean)
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153 rm(gcl_clean2)
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154
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155 names(te_strand) <- paste(seqnames(gr), start(gr), end(gr), sep = "_")
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156 names(s_left) <- paste(seqnames(grL), start(grL), end(grL), sep = "_")
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157 names(s_right) <- paste(seqnames(grR), start(grR), end(grR), sep = "_")
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158 cat('Identification of LTRs...')
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159 TE <- mclapply(seq_along(gr), function(x)get_TE(s_left[x],
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160 s_right[x],
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161 gcl_clean_with_domains[[x]],
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162 gr[x],
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163 grL[x],
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164 grR[x]),
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165 mc.set.seed = TRUE, mc.cores = opt$cpu, mc.preschedule = FALSE
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166 )
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167
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168 cat('done.\n')
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169
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170 good_TE <- TE[!sapply(TE, is.null)]
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171 cat('Number of putative TE with identified LTR :', length(good_TE), '\n')
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172
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173
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174 ID <- paste0('TE_', sprintf("%08d", seq(good_TE)))
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175 gff3_list <- mcmapply(get_te_gff3, g = good_TE, ID = ID, mc.cores = opt$cpu)
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176
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177 cat('Identification of PBS ...')
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178 gff3_list2 <- mclapply(gff3_list, FUN = add_pbs, s = s, trna_db = trna_db, mc.set.seed = TRUE, mc.cores = opt$cpu, mc.preschedule = FALSE)
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179 cat('done\n')
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180 gff3_out <- do.call(c, gff3_list2)
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181
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182 # define new source
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183 src <- as.character(gff3_out$source)
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184 src[is.na(src)] <- "dante_ltr"
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185 gff3_out$source <- src
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186 gff3_out$Rank <- get_te_rank(gff3_out)
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187 # TODO add attributte specifying individual groups DL, DLT, DLP DLPT gff3
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188
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189 export(gff3_out, con = paste0(outfile, ".gff3"), format = 'gff3')
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190
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191 all_tbl <- get_te_statistics(gff3_out, RT)
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192 write.table(all_tbl, file = paste0(outfile, "_statistics.csv"), sep = "\t", quote = FALSE, row.names = TRUE)
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193 # export fasta files:
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194 s_te <- get_te_sequences(gff3_out, s)
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195
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196 for (i in seq_along(s_te)) {
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197 outname <- paste0(outfile, "_", names(s_te)[i], ".fasta")
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198 writeXStringSet(s_te[[i]], filepath = outname)
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199 }
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200