Mercurial > repos > gregory-minevich > snp_mapping_using_wgs
view SNP_Mapping.py @ 29:6b5bd5faf836 draft
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author | gregory-minevich |
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date | Sat, 22 Jun 2013 18:39:29 -0400 |
parents | 12846439eeaf |
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#!/usr/bin/python import re import sys import optparse import csv import re import pprint from decimal import * from rpy import * def main(): csv.field_size_limit(1000000000) parser = optparse.OptionParser() parser.add_option('-v', '--sample_vcf', dest = 'sample_vcf', action = 'store', type = 'string', default = None, help = "Sample VCF from GATK Unified Genotyper") parser.add_option('-l', '--loess_span', dest = 'loess_span', action = 'store', type = 'float', default = .01, help = "Loess span") parser.add_option('-d', '--d_yaxis', dest = 'd_yaxis', action = 'store', type = 'float', default = .7, help = "y-axis upper limit for dot plot") parser.add_option('-y', '--h_yaxis', dest = 'h_yaxis', action = 'store', type = 'int', default = 5, help = "y-axis upper limit for histogram plot") parser.add_option('-c', '--points_color', dest = 'points_color', action = 'store', type = 'string', default = "gray27", help = "Color for data points") parser.add_option('-k', '--loess_color', dest = 'loess_color', action = 'store', type = 'string', default = "red", help = "Color for loess regression line") parser.add_option('-z', '--standardize', dest = 'standardize', default= 'true', help = "Standardize X-axis") parser.add_option('-b', '--break_file', dest = 'break_file', action = 'store', type = 'string', default = 'C.elegans', help = "File defining the breaks per chromosome") parser.add_option('-x', '--bin_size', dest = 'bin_size', action = 'store', type = 'int', default = 1000000, help = "Size of histogram bins, default is 1mb") parser.add_option('-n', '--normalize_bins', dest = 'normalize_bins', default= 'true', help = "Normalize histograms") parser.add_option('-o', '--output', dest = 'output', action = 'store', type = 'string', default = None, help = "Output file name") parser.add_option('-s', '--location_plot_output', dest = 'location_plot_output', action = 'store', type = 'string', default = "SNP_Mapping_Plot.pdf", help = "Output file name of SNP plots by chromosomal location") (options, args) = parser.parse_args() vcf_info = parse_vcf(sample_vcf = options.sample_vcf) output_vcf_info(output = options.output, vcf_info = vcf_info) #output plot with all ratios rounded_bin_size = int(round((float(options.bin_size) / 1000000), 1) * 1000000) normalized_histogram_bins_per_mb = calculate_normalized_histogram_bins_per_xbase(vcf_info = vcf_info, xbase = rounded_bin_size, normalize_bins = options.normalize_bins) normalized_histogram_bins_per_5kb = calculate_normalized_histogram_bins_per_xbase(vcf_info = vcf_info, xbase = (rounded_bin_size / 2), normalize_bins = options.normalize_bins) break_dict = parse_breaks(break_file = options.break_file) output_scatter_plots_by_location(location_plot_output = options.location_plot_output, vcf_info = vcf_info, loess_span=options.loess_span, d_yaxis=options.d_yaxis, h_yaxis=options.h_yaxis, points_color=options.points_color, loess_color=options.loess_color, standardize =options.standardize, normalized_hist_per_mb = normalized_histogram_bins_per_mb, normalized_hist_per_5kb = normalized_histogram_bins_per_5kb, breaks = break_dict, rounded_bin_size = rounded_bin_size) def skip_headers(reader = None, i_file = None): # count headers comment = 0 while reader.next()[0].startswith('#'): comment = comment + 1 # skip headers i_file.seek(0) for i in range(0, comment): reader.next() def parse_breaks(break_file = None): if break_file == 'C.elegans': break_dict = { 'I' : 16 , 'II' : 16, 'III' : 14, 'IV' : 18, 'V' : 21, 'X' : 18 } return break_dict elif break_file == 'Arabidopsis': break_dict = { '1' : 31 , '2' : 20, '3' : 24, '4' : 19, '5' : 27 } return break_dict else: i_file = open(break_file, 'rU') break_dict = {} reader = csv.reader(i_file, delimiter = '\t') for row in reader: chromosome = row[0].upper() chromosome = re.sub("chr", "", chromosome, flags = re.IGNORECASE) chromosome = re.sub("CHROMOSOME_", "", chromosome, flags = re.IGNORECASE) break_count = row[1] break_dict[chromosome] = int(break_count) return break_dict def location_comparer(location_1, location_2): chr_loc_1 = location_1.split(':')[0] pos_loc_1 = int(location_1.split(':')[1]) chr_loc_2 = location_2.split(':')[0] pos_loc_2 = int(location_2.split(':')[1]) if chr_loc_1 == chr_loc_2: if pos_loc_1 < pos_loc_2: return -1 elif pos_loc_1 == pos_loc_1: return 0 elif pos_loc_1 > pos_loc_2: return 1 elif chr_loc_1 < chr_loc_2: return -1 elif chr_loc_1 > chr_loc_2: return 1 def output_vcf_info(output = None, vcf_info = None): o_file = open(output, 'wb') writer = csv.writer(o_file, delimiter = '\t') writer.writerow(["#Chr\t", "Pos\t", "Alt Count\t", "Ref Count\t", "Read Depth\t", "Ratio\t"]) location_sorted_vcf_info_keys = sorted(vcf_info.keys(), cmp=location_comparer) for location in location_sorted_vcf_info_keys: alt_allele_count, ref_allele_count, read_depth, ratio = vcf_info[location] location_info = location.split(':') chromosome = location_info[0] position = location_info[1] writer.writerow([chromosome, position, alt_allele_count, ref_allele_count, read_depth, ratio]) o_file.close() def output_scatter_plots_by_location(location_plot_output = None, vcf_info = None, loess_span="", d_yaxis="", h_yaxis="", points_color="", loess_color="", standardize=None, normalized_hist_per_mb = None, normalized_hist_per_5kb = None, breaks = None, rounded_bin_size = 1000000): positions = {} current_chr = "" prev_chr = "" x_label = "Location (Mb)" filtered_label = '' location_sorted_vcf_info_keys = sorted(vcf_info.keys(), cmp=location_comparer) break_unit = Decimal(rounded_bin_size) / Decimal(1000000) max_breaks = max(breaks.values()) try: r.pdf(location_plot_output, 8, 8) for location in location_sorted_vcf_info_keys: current_chr = location.split(':')[0] position = location.split(':')[1] alt_allele_count, ref_allele_count, read_depth, ratio = vcf_info[location] if prev_chr != current_chr: if prev_chr != "": hist_dict_mb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_mb, chr = prev_chr) hist_dict_5kb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_5kb, chr = prev_chr) plot_data(chr_dict = positions, hist_dict_mb = hist_dict_mb, hist_dict_5kb = hist_dict_5kb, chr = prev_chr + filtered_label, x_label = "Location (Mb)", divide_position = True, draw_secondary_grid_lines = True, loess_span=loess_span, d_yaxis=d_yaxis, h_yaxis=h_yaxis, points_color=points_color, loess_color=loess_color, breaks = breaks[prev_chr], standardize=standardize, max_breaks = max_breaks, break_unit = break_unit) prev_chr = current_chr positions = {} positions[position] = ratio hist_dict_mb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_mb, chr = current_chr) hist_dict_5kb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_5kb, chr = current_chr) plot_data(chr_dict = positions, hist_dict_mb = hist_dict_mb, hist_dict_5kb = hist_dict_5kb, chr = current_chr + filtered_label, x_label = "Location (Mb)", divide_position = True, draw_secondary_grid_lines = True, loess_span=loess_span, d_yaxis=d_yaxis, h_yaxis=h_yaxis, points_color=points_color, loess_color=loess_color, breaks = breaks[current_chr], standardize=standardize, max_breaks = max_breaks, break_unit = break_unit) r.dev_off() except Exception as inst: print inst print "There was an error creating the location plot pdf... Please try again" def get_hist_dict_by_chr(normalized_hist_per_xbase = None, chr = ''): hist_dict = {} for location in normalized_hist_per_xbase: chromosome = location.split(':')[0] if chromosome == chr: position = int(location.split(':')[1]) hist_dict[position] = normalized_hist_per_xbase[location] max_location = max(hist_dict.keys(), key=int) for i in range(1, max_location): if i not in hist_dict: hist_dict[i] = 0 return hist_dict def plot_data(chr_dict = None, hist_dict_mb = None, hist_dict_5kb = None, chr = "", x_label = "", divide_position = False, draw_secondary_grid_lines = False, loess_span=None, d_yaxis=None, h_yaxis=None, points_color="", loess_color="", breaks = None, standardize= None, max_breaks = 1, break_unit = 1): ratios = "c(" positions = "c(" for position in chr_dict: ratio = chr_dict[position] if divide_position: position = float(position) / 1000000.0 positions = positions + str(position) + ", " ratios = ratios + str(ratio) + ", " if len(ratios) == 2: ratios = ratios + ")" else: ratios = ratios[0:len(ratios) - 2] + ")" if len(positions) == 2: positions = positions + ")" else: positions = positions[0:len(positions) - 2] + ")" r("x <- " + positions) r("y <- " + ratios) hist_mb_values = "c(" for position in sorted(hist_dict_mb): hist_mb_values = hist_mb_values + str(hist_dict_mb[position]) + ", " if len(hist_mb_values) == 2: hist_mb_values = hist_mb_values + ")" else: hist_mb_values = hist_mb_values[0:len(hist_mb_values) - 2] + ")" hist_5kb_values = "c(" for position in sorted(hist_dict_5kb): hist_5kb_values = hist_5kb_values + str(hist_dict_5kb[position]) + ", " if len(hist_5kb_values) == 2: hist_5kb_values = hist_5kb_values + ")" else: hist_5kb_values = hist_5kb_values[0:len(hist_5kb_values) - 2] + ")" r("xz <- " + hist_mb_values) r("yz <- " + hist_5kb_values) max_break_str = str(max_breaks) break_unit_str = str(Decimal(break_unit)) half_break_unit_str = str(Decimal(break_unit) / Decimal(2)) break_penta_unit_str = str(Decimal(break_unit) * Decimal(5)) if (standardize=='true'): r("plot(x, y, ,cex=0.60, xlim=c(0," + max_break_str + "), main='LG " + chr + " (Hawaiian Variant Mapping)', xlab= '" + x_label + "', ylim = c(0, %f " %d_yaxis + "), ylab='Ratios of mapping strain alleles/total reads (at SNP positions)', pch=10, col='"+ points_color +"')") r("lines(loess.smooth(x, y, span = %f "%loess_span + "), lwd=5, col='"+ loess_color +"')") r("axis(1, at=seq(0, " + max_break_str + ", by=" + break_unit_str + "), labels=FALSE, tcl=-0.5)") r("axis(1, at=seq(0, " + max_break_str + ", by=" + half_break_unit_str + "), labels=FALSE, tcl=-0.25)") r("axis(2, at=seq(floor(min(y)), 1, by=0.1), labels=FALSE, tcl=-0.2)") elif (standardize=='false'): r("plot(x, y, cex=0.60, main='LG " + chr + " (Hawaiian Variant Mapping)', xlab= '" + x_label + "', ylim = c(0, %f " %d_yaxis + "), ylab='Ratios of mapping strain alleles/total reads (at SNP positions)', pch=10, col='"+ points_color +"')") r("lines(loess.smooth(x, y, span = %f "%loess_span + "), lwd=5, col='"+ loess_color +"')") r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + break_unit_str + "), labels=FALSE, tcl=-0.5)") r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + half_break_unit_str + "), labels=FALSE, tcl=-0.25)") r("axis(2, at=seq(floor(min(y)), 1, by=0.1), labels=FALSE, tcl=-0.2)") if draw_secondary_grid_lines: r("abline(h = seq(floor(min(y)), 1, by=0.1), v = seq(floor(min(x)), length(x), by= 1), col='gray')") else: r("grid(lty = 1, col = 'gray')") if (standardize=='true'): r("barplot(xz, xlim=c(0, " + max_break_str + "), ylim = c(0, " + str(h_yaxis) + "), yaxp=c(0, " + str(h_yaxis) + ", 1), space = 0, col='darkgray', width = " + break_unit_str + ", xlab='Location (Mb)', ylab='Normalized frequency of pure parental alleles ', main='LG " + chr + " (Hawaiian Variant Mapping)')") r("barplot(yz, space = 0, add=TRUE, width = " + half_break_unit_str + ", col=rgb(1, 0, 0, 1))") r("axis(1, hadj = 1, at=seq(0, " + max_break_str + ", by= " + break_unit_str + "), labels=FALSE, tcl=-0.5)") r("axis(1, at=seq(0, " + max_break_str + ", by= " + break_penta_unit_str + "), labels=TRUE, tcl=-0.5)") r("axis(1, at=seq(0, " + max_break_str + ", by= " + half_break_unit_str + "), labels=FALSE, tcl=-0.25)") elif (standardize=='false'): r("barplot(xz, ylim = c(0, " + str(h_yaxis) + "), yaxp=c(0, " + str(h_yaxis) + ", 1), space = 0, col='darkgray', width = 1, xlab='Location (Mb)', ylab='Normalized frequency of pure parental alleles ', main='LG " + chr + " (Hawaiian Variant Mapping)')") r("barplot(yz, space = 0, add=TRUE, width = 0.5, col=rgb(1, 0, 0, 1))") r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + break_unit_str + "), labels=FALSE, tcl=-0.5)") r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + break_penta_unit_str + "), labels=TRUE, tcl=-0.5)") r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + half_break_unit_str + "), labels=FALSE, tcl=-0.25)") def calculate_normalized_histogram_bins_per_xbase(vcf_info = None, xbase = 1000000, normalize_bins = None): normalized_histogram_bins_per_xbase = {} ref_snp_count_per_xbase = get_ref_snp_count_per_xbase(vcf_info = vcf_info, xbase = xbase) #print "ref_snp_count_per_xbase: " + str(ref_snp_count_per_xbase) mean_zero_snp_count_per_chromosome = get_mean_zero_snp_count_per_chromosome(vcf_info = vcf_info, xbase = xbase) #print "mean_zero_snp_count_per_chromosome: " + str(mean_zero_snp_count_per_chromosome) zero_snp_count_per_xbase = get_zero_snp_count_per_xbase(vcf_info = vcf_info, xbase = xbase) #print "zero_snp_count_per_xbase: " + str(zero_snp_count_per_xbase) for location in ref_snp_count_per_xbase: chromosome = location.split(':')[0] mean_zero_snp_count = mean_zero_snp_count_per_chromosome[chromosome] ref_snp_count = ref_snp_count_per_xbase[location] zero_snp_count = 0 if location in zero_snp_count_per_xbase: zero_snp_count = zero_snp_count_per_xbase[location] if normalize_bins == 'true': if zero_snp_count == 0 or ref_snp_count == 0: normalized_histogram_bins_per_xbase[location] = 0 elif zero_snp_count == ref_snp_count: normalized_histogram_bins_per_xbase[location] = 0 else: normalized_histogram_bins_per_xbase[location] = (Decimal(zero_snp_count) / (Decimal(ref_snp_count)-Decimal(zero_snp_count))) * Decimal(mean_zero_snp_count) else: normalized_histogram_bins_per_xbase[location] = zero_snp_count return normalized_histogram_bins_per_xbase def get_ref_snp_count_per_xbase(vcf_info = None, xbase = 1000000): ref_snps_per_xbase = {} for location in vcf_info: location_info = location.split(':') chromosome = location_info[0].upper() chromosome = re.sub("chr", "", chromosome, flags = re.IGNORECASE) chromosome = re.sub("CHROMOSOME_", "", chromosome, flags = re.IGNORECASE) position = location_info[1] xbase_position = (int(position) / xbase) + 1 location = chromosome + ":" + str(xbase_position) if location in ref_snps_per_xbase: ref_snps_per_xbase[location] = ref_snps_per_xbase[location] + 1 else: ref_snps_per_xbase[location] = 1 return ref_snps_per_xbase def get_mean_zero_snp_count_per_chromosome(vcf_info, xbase = 1000000): sample_snp_count_per_xbase = {} for location in vcf_info: alt_allele_count, ref_allele_count, read_depth, ratio = vcf_info[location] location_info = location.split(':') chromosome = location_info[0] position = location_info[1] xbase_position = (int(position) / xbase) + 1 xbase_location = chromosome + ":" + str(xbase_position) if int(alt_allele_count) == 0: if xbase_location in sample_snp_count_per_xbase: sample_snp_count_per_xbase[xbase_location] = sample_snp_count_per_xbase[xbase_location] + 1 else: sample_snp_count_per_xbase[xbase_location] = 1 elif int(alt_allele_count) != 0 and xbase_location not in sample_snp_count_per_xbase: sample_snp_count_per_xbase[xbase_location] = 0 mean_zero_snp_count_per_chromosome = {} for location in sample_snp_count_per_xbase: chromosome = location.split(':')[0] sample_count = sample_snp_count_per_xbase[location] if chromosome in mean_zero_snp_count_per_chromosome: mean_zero_snp_count_per_chromosome[chromosome].append(sample_count) else: mean_zero_snp_count_per_chromosome[chromosome] = [sample_count] for chromosome in mean_zero_snp_count_per_chromosome: summa = sum(mean_zero_snp_count_per_chromosome[chromosome]) count = len(mean_zero_snp_count_per_chromosome[chromosome]) mean_zero_snp_count_per_chromosome[chromosome] = Decimal(summa) / Decimal(count) return mean_zero_snp_count_per_chromosome def get_zero_snp_count_per_xbase(vcf_info = None, xbase = 1000000): zero_snp_count_per_xbase = {} for location in vcf_info: alt_allele_count, ref_allele_count, read_depth, ratio = vcf_info[location] location_info = location.split(':') chromosome = location_info[0] position = location_info[1] xbase_position = (int(position) / xbase) + 1 xbase_location = chromosome + ":" + str(xbase_position) if int(alt_allele_count) == 0: if xbase_location in zero_snp_count_per_xbase: zero_snp_count_per_xbase[xbase_location] = zero_snp_count_per_xbase[xbase_location] + 1 else: zero_snp_count_per_xbase[xbase_location] = 1 elif int(alt_allele_count) != 0 and xbase_location not in zero_snp_count_per_xbase: zero_snp_count_per_xbase[xbase_location] = 0 return zero_snp_count_per_xbase def parse_vcf(sample_vcf = None): i_file = open(sample_vcf, 'rU') reader = csv.reader(i_file, delimiter = '\t', quoting = csv.QUOTE_NONE) skip_headers(reader = reader, i_file = i_file) vcf_info = {} for row in reader: chromosome = row[0].upper() chromosome = re.sub("chr", "", chromosome, flags = re.IGNORECASE) chromosome = re.sub("CHROMOSOME_", "", chromosome, flags = re.IGNORECASE) if chromosome != 'MTDNA': position = row[1] #ref_allele = row[2] #read_depth = row[3] #read_bases = row[4] vcf_format_info = row[8].split(":") vcf_allele_freq_data = row[9] read_depth_data_index = vcf_format_info.index("DP") read_depth = vcf_allele_freq_data.split(":")[read_depth_data_index] ref_and_alt_counts_data_index = vcf_format_info.index("AD") ref_and_alt_counts = vcf_allele_freq_data.split(":")[ref_and_alt_counts_data_index] ref_allele_count = ref_and_alt_counts.split(",")[0] alt_allele_count = ref_and_alt_counts.split(",")[1] location = chromosome + ":" + position if (Decimal(read_depth)!=0): getcontext().prec = 6 ratio = Decimal(alt_allele_count) / Decimal(read_depth) vcf_info[location] = (alt_allele_count, ref_allele_count, read_depth, ratio) #debug line #print chromosome, position, read_depth, ref_allele_count, alt_allele_count, ratio, id i_file.close() return vcf_info def parse_read_bases(read_bases = None, alt_allele = None): read_bases = re.sub('\$', '', read_bases) read_bases = re.sub('\^[^\s]', '', read_bases) ref_allele_matches = re.findall("\.|\,", read_bases) ref_allele_count = len(ref_allele_matches) alt_allele_matches = re.findall(alt_allele, read_bases, flags = re.IGNORECASE) alt_allele_count = len(alt_allele_matches) #debug line #print read_bases, alt_allele, alt_allele_count, ref_allele_count return ref_allele_count, alt_allele_count if __name__ == "__main__": main()