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| -rw-r--r-- | wqflask/maintenance/convert_geno_to_bimbam.py | 239 |
1 files changed, 239 insertions, 0 deletions
diff --git a/wqflask/maintenance/convert_geno_to_bimbam.py b/wqflask/maintenance/convert_geno_to_bimbam.py new file mode 100644 index 00000000..05006d5c --- /dev/null +++ b/wqflask/maintenance/convert_geno_to_bimbam.py @@ -0,0 +1,239 @@ +#!/usr/bin/python + +""" +Convert .geno files to json + +This file goes through all of the genofiles in the genofile directory (.geno) +and converts them to json files that are used when running the marker regression +code + +""" + +from __future__ import print_function, division, absolute_import +import sys +sys.path.append("..") +import os +import glob +import traceback +import gzip + +#import numpy as np +#from pyLMM import lmm + +import simplejson as json + +from pprint import pformat as pf + +class EmptyConfigurations(Exception): pass + + + +class Marker(object): + def __init__(self): + self.name = None + self.chr = None + self.cM = None + self.Mb = None + self.genotypes = [] + +class ConvertGenoFile(object): + + def __init__(self, input_file, output_files): + + self.input_file = input_file + self.output_files = output_files + + self.mb_exists = False + self.cm_exists = False + self.markers = [] + + self.latest_row_pos = None + self.latest_col_pos = None + + self.latest_row_value = None + self.latest_col_value = None + + def convert(self): + + self.haplotype_notation = { + '@mat': "1", + '@pat': "0", + '@het': "0.5", + '@unk': "NA" + } + + self.configurations = {} + #self.skipped_cols = 3 + + #if self.input_file.endswith(".geno.gz"): + # print("self.input_file: ", self.input_file) + # self.input_fh = gzip.open(self.input_file) + #else: + self.input_fh = open(self.input_file) + + with open(self.output_files[0], "w") as self.geno_fh: + #if self.file_type == "geno": + self.process_csv() + #elif self.file_type == "snps": + # self.process_snps_file() + + + def process_csv(self): + for row_count, row in enumerate(self.process_rows()): + row_items = row.split("\t") + + this_marker = Marker() + this_marker.name = row_items[1] + this_marker.chr = row_items[0] + if self.cm_exists and self.mb_exists: + this_marker.cM = row_items[2] + this_marker.Mb = row_items[3] + genotypes = row_items[4:] + elif self.cm_exists: + this_marker.cM = row_items[2] + genotypes = row_items[3:] + elif self.mb_exists: + this_marker.Mb = row_items[2] + genotypes = row_items[3:] + else: + genotypes = row_items[2:] + for item_count, genotype in enumerate(genotypes): + if genotype.upper().strip() in self.configurations: + this_marker.genotypes.append(self.configurations[genotype.upper().strip()]) + else: + this_marker.genotypes.append("NA") + + #print("this_marker is:", pf(this_marker.__dict__)) + #if this_marker.chr == "14": + self.markers.append(this_marker.__dict__) + + self.write_to_bimbam() + + # with open(self.output_file, 'w') as fh: + # json.dump(self.markers, fh, indent=" ", sort_keys=True) + + # print('configurations:', str(configurations)) + #self.latest_col_pos = item_count + self.skipped_cols + #self.latest_col_value = item + + #if item_count != 0: + # self.output_fh.write(" ") + #self.output_fh.write(self.configurations[item.upper()]) + + #self.output_fh.write("\n") + + def write_to_bimbam(self): + with open(self.output_files[0], "w") as geno_fh: + # geno_fh.write(str(len(self.sample_list)) + "\n") + # geno_fh.write("2\n") + # geno_fh.write("IND") + # for sample in self.sample_list: + # geno_fh.write(" " + sample) + # geno_fh.write("\n") + for marker in self.markers: + geno_fh.write(marker['name']) + geno_fh.write(", X, Y") + geno_fh.write(", " + ", ".join(marker['genotypes'])) + geno_fh.write("\n") + + #pheno_fh = open(self.output_files[1], 'w') + with open(self.output_files[1], "w") as pheno_fh: + for sample in self.sample_list: + pheno_fh.write("1\n") + + with open(self.output_files[2], "w") as snp_fh: + for marker in self.markers: + if self.mb_exists: + snp_fh.write(marker['name'] +", " + str(int(float(marker['Mb'])*1000000)) + ", " + marker['chr'] + "\n") + else: + snp_fh.write(marker['name'] +", " + str(int(float(marker['cM'])*1000000)) + ", " + marker['chr'] + "\n") + + + def get_sample_list(self, row_contents): + self.sample_list = [] + if self.mb_exists: + if self.cm_exists: + self.sample_list = row_contents[4:] + else: + self.sample_list = row_contents[3:] + else: + if self.cm_exists: + self.sample_list = row_contents[3:] + else: + self.sample_list = row_contents[2:] + + def process_rows(self): + for self.latest_row_pos, row in enumerate(self.input_fh): + #if self.input_file.endswith(".geno.gz"): + # print("row: ", row) + self.latest_row_value = row + # Take care of headers + if not row.strip(): + continue + if row.startswith('#'): + continue + if row.startswith('Chr'): + if 'Mb' in row.split(): + self.mb_exists = True + if 'cM' in row.split(): + self.cm_exists = True + self.get_sample_list(row.split()) + continue + if row.startswith('@'): + key, _separater, value = row.partition(':') + key = key.strip() + value = value.strip() + if key in self.haplotype_notation: + self.configurations[value] = self.haplotype_notation[key] + continue + if not len(self.configurations): + raise EmptyConfigurations + yield row + + @classmethod + def process_all(cls, old_directory, new_directory): + os.chdir(old_directory) + for input_file in glob.glob("*"): + if not input_file.endswith(('geno', '.geno.gz')): + continue + group_name = ".".join(input_file.split('.')[:-1]) + geno_output_file = os.path.join(new_directory, group_name + "_geno.txt") + pheno_output_file = os.path.join(new_directory, group_name + "_pheno.txt") + snp_output_file = os.path.join(new_directory, group_name + "_snps.txt") + output_files = [geno_output_file, pheno_output_file, snp_output_file] + print("%s -> %s" % ( + os.path.join(old_directory, input_file), geno_output_file)) + convertob = ConvertGenoFile(input_file, output_files) + try: + convertob.convert() + except EmptyConfigurations as why: + print(" No config info? Continuing...") + #excepted = True + continue + except Exception as why: + + print(" Exception:", why) + print(traceback.print_exc()) + print(" Found in row %s at tabular column %s" % (convertob.latest_row_pos, + convertob.latest_col_pos)) + print(" Column is:", convertob.latest_col_value) + print(" Row is:", convertob.latest_row_value) + break + + #def process_snps_file(cls, snps_file, new_directory): + # output_file = os.path.join(new_directory, "mouse_families.json") + # print("%s -> %s" % (snps_file, output_file)) + # convertob = ConvertGenoFile(input_file, output_file) + + +if __name__=="__main__": + Old_Geno_Directory = """/home/zas1024/genotype_files/genotype/""" + New_Geno_Directory = """/home/zas1024/genotype_files/genotype/bimbam/""" + #Input_File = """/home/zas1024/gene/genotype_files/genotypes/BXD.geno""" + #Output_File = """/home/zas1024/gene/wqflask/wqflask/pylmm/data/bxd.snps""" + #convertob = ConvertGenoFile("/home/zas1024/gene/genotype_files/genotypes/SRxSHRSPF2.geno", "/home/zas1024/gene/genotype_files/new_genotypes/SRxSHRSPF2.json") + #convertob.convert() + ConvertGenoFile.process_all(Old_Geno_Directory, New_Geno_Directory) + #ConvertGenoFiles(Geno_Directory) + + #process_csv(Input_File, Output_File)
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