Mercurial > repos > proteore > proteore_get_unique_peptide_srm_method
view get_unique_srm.py @ 0:a2b06836de90 draft
planemo upload commit f9de6f4e3302c41e64c39d639bee780e5eafd84d-dirty
author | proteore |
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date | Fri, 12 Jul 2019 07:49:45 -0400 |
parents | |
children | b526dba9dc40 |
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import argparse, csv, re def get_args(): parser = argparse.ArgumentParser() parser.add_argument("--input_type", help="type of input (list of id or filename)", required=True) parser.add_argument("-i", "--input", help="list of IDs (text or filename)", required=True) parser.add_argument("--header", help="true/false if your file contains a header") parser.add_argument("-c", "--column_number", help="list of IDs (text or filename)") parser.add_argument("-f", "--features", help="Protein features to return from SRM Atlas", required=True) parser.add_argument("-d", "--ref_file", help="path to reference file", required=True) parser.add_argument("-o", "--output", help="output filename", required=True) args = parser.parse_args() return args #return the column number in int format def nb_col_to_int(nb_col): try : nb_col = int(nb_col.replace("c", "")) - 1 return nb_col except : sys.exit("Please specify the column where you would like to apply the filter with valid format") #replace all blank cells to NA def blank_to_NA(csv_file) : tmp=[] for line in csv_file : line = ["NA" if cell=="" or cell==" " or cell=="NaN" else cell for cell in line] tmp.append(line) return tmp #convert string to boolean def str2bool(v): if v.lower() in ('yes', 'true', 't', 'y', '1'): return True elif v.lower() in ('no', 'false', 'f', 'n', '0'): return False else: raise argparse.ArgumentTypeError('Boolean value expected.') #return list of (unique) ids from string def get_input_ids_from_string(input) : ids_list = list(set(re.split(r'\s+',input.replace("_SNP","").replace("d_","").replace("\r","").replace("\n"," ").replace("\t"," ")))) if "" in ids_list : ids_list.remove("") return ids_list #return input_file and list of unique ids from input file path def get_input_ids_from_file(input,nb_col,header) : with open(input, "r") as csv_file : input_file= list(csv.reader(csv_file, delimiter='\t')) input_file, ids_list = one_id_one_line(input_file,nb_col,header) if "" in ids_list : ids_list.remove("") return input_file, ids_list #function to check if an id is an uniprot accession number : return True or False- def check_uniprot (id): uniprot_pattern = re.compile("[OPQ][0-9][A-Z0-9]{3}[0-9]|[A-NR-Z][0-9]([A-Z][A-Z0-9]{2}[0-9]){1,2}") if uniprot_pattern.match(id) : return True else : return False #return input file by adding lines when there are more than one id per line def one_id_one_line(input_file,nb_col,header) : if header : new_file = [input_file[0]] input_file = input_file[1:] else : new_file=[] ids_list=[] for line in input_file : if line != [] and set(line) != {''}: line[nb_col] = re.sub(r"\s+","",line[nb_col]) if line[nb_col] == "" : line[nb_col]='NA' if ";" in line[nb_col] : ids = line[nb_col].split(";") for id in ids : new_file.append(line[:nb_col]+[id]+line[nb_col+1:]) ids_list.append(id) else : new_file.append(line) ids_list.append(line[nb_col]) ids_list=[e.replace("_SNP","").replace("d_","") for e in ids_list] ids_list= list(set(ids_list)) return new_file, ids_list def create_srm_atlas_dictionary(features,srm_atlas_csv): srm_atlas={} features_index = {"PeptideSeq" : 0, "SSRT" : 1 , "Length" : 2 , "type": 3 , "PA_AccNum" : 4, "MW" : 5 } features_to_get = [features_index[feature] for feature in features] for line in srm_atlas_csv[1:]: id = line[9].replace("_SNP","").replace("d_","") if id not in srm_atlas: srm_atlas[id]=[[line[i] for i in features_to_get]] else: srm_atlas[id].append([line[i] for i in features_to_get]) return srm_atlas def retrieve_srm_features(srm_atlas,ids): result_dict = {} for id in ids: if id in srm_atlas: res = srm_atlas[id] else : res="" result_dict[id]=res return result_dict def create_header(input_file,ncol,features): col_names = list(range(1,len(input_file[0])+1)) col_names = ["col"+str(e) for e in col_names] col_names[ncol]="Uniprot-AC" col_names = col_names+features return(col_names) def main(): #Get args from command line args = get_args() features=args.features.split(",") header=False if args.input_type=="file" : column_number = nb_col_to_int(args.column_number) header = str2bool(args.header) #Get reference file (Human SRM Atlas) with open(args.ref_file, "r") as csv_file : srm_atlas_csv = csv.reader(csv_file, delimiter='\t') srm_atlas_csv = [line for line in srm_atlas_csv] #Create srm Atlas dictionary srm_atlas = create_srm_atlas_dictionary(features,srm_atlas_csv) #Get file and/or ids from input if args.input_type == "list" : ids = get_input_ids_from_string(args.input) elif args.input_type == "file" : input_file, ids = get_input_ids_from_file(args.input,column_number,header) #Check Uniprot-AC if not any([check_uniprot(id) for id in ids]): print ("No Uniprot-AC found, please check your input") exit() #retrieve features result_dict = retrieve_srm_features(srm_atlas,ids) #write output with open(args.output,"w") as output : writer = csv.writer(output,delimiter="\t") #write header if header : writer.writerow(input_file[0]+features) input_file = input_file[1:] elif args.input_type=="file": col_names = [create_header(input_file,column_number,features)] writer.writerow(col_names) else : writer.writerow(["Uniprot-AC"]+features) #write lines previous_line="" if args.input_type=="file" : for line in input_file : for res in result_dict[line[column_number]]: output_line = ["NA" if cell=="" or cell==" " or cell=="NaN" else cell for cell in line+res] if previous_line != output_line : writer.writerow(output_line) previous_line=output_line elif args.input_type=="list" : for id in ids : for res in result_dict[id]: line = ["NA" if cell=="" or cell==" " or cell=="NaN" else cell for cell in [id]+res] if previous_line != line : writer.writerow(line) previous_line=line if __name__ == "__main__": main()