Mercurial > repos > davidvanzessen > shm_csr
view shm_csr.py @ 96:385dea3c6cb5 draft
planemo upload commit 423a48569c69301fdbf893ac3a649128404dfff5
author | rhpvorderman |
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date | Fri, 05 Jan 2024 08:53:22 +0000 |
parents | 6809c63d9161 |
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import argparse import logging import sys import os import traceback import typing from typing import Optional from collections import defaultdict REGION_FILTERS = ("leader", "FR1", "CDR1", "FR2", "CDR2", "None") def int_or_zero(value: typing.Any): try: return int(value) except ValueError: return 0 class Mutation(typing.NamedTuple): """Represent a mutation type as a tuple""" frm: str # 'from' is a reserved python keyword. where: int to: str frmAA: Optional[str] = None whereAA: Optional[int] = None toAA: Optional[str] = None thing: Optional[str] = None # '(---)' or '(+-+)' etc. No idea @classmethod def from_string(cls, string: str): # Complete mutation example: a88>g,I30>V(+ - +) # Only nucleotide example: g303>t # Including codon change: # t169>g,Y57>D(- - -); Y57 tat 169-171 [ta 169-170]>D gac # Including codon change (synonumous mutation): # c114>t, Y38; Y38 tac 112-114 [tact 112-115]>Y tat if ',' in string: nucleotide_change, aa_change = string.split(',', maxsplit=1) # type: str, Optional[str] else: nucleotide_change = string aa_change = None frm_part, to = nucleotide_change.split('>', maxsplit=1) frm = frm_part[0] where = int(frm_part[1:]) if aa_change is None: return cls(frm, where, to) aa_change = aa_change.strip() # The part after semicolon indicates the codon change. This part may # not be present. semi_colon_index = aa_change.find(";") if semi_colon_index == -1: codon_change = "" else: codon_change = aa_change[semi_colon_index:] aa_change = aa_change[:semi_colon_index] change_operator_index = aa_change.find(">") if change_operator_index == -1: # Synonymous change frmAA_part = aa_change toAA_part = "" else: frmAA_part, toAA_part = aa_change.split('>', maxsplit=1) # type: str, str frmAA = frmAA_part[0] whereAA = int(frmAA_part[1:]) if toAA_part: brace_start = toAA_part.index('(') toAA = toAA_part[:brace_start] thing = toAA_part[brace_start:] + codon_change else: # Synonymous mutation toAA = frmAA thing = codon_change return cls(frm, where, to, frmAA, whereAA, toAA, thing) class Hotspot(typing.NamedTuple): start: int end: int region: str @classmethod def from_string(cls, string): # Example: aa,40-41(FR1) sequence, rest = string.split(',') # type: str, str brace_pos = rest.index('(') numbers = rest[:brace_pos] start, end = numbers.split('-') region = rest[brace_pos + 1:-1] # Remove the braces return cls(int(start), int(end), region) def main(): parser = argparse.ArgumentParser() parser.add_argument("--input", help="The '7_V-REGION-mutation-and-AA-change-table' and '10_V-REGION-mutation-hotspots' merged together, with an added 'best_match' annotation") parser.add_argument("--genes", help="The genes available in the 'best_match' column") parser.add_argument("--empty_region_filter", help="Where does the sequence start?", choices=REGION_FILTERS) parser.add_argument("--output", help="Output file") args = parser.parse_args() infile = args.input genes = str(args.genes).split(",") empty_region_filter = args.empty_region_filter outfile = args.output genedic = dict() mutationdic = dict() NAMatchResult = (None, None, None, None, None, None, '') linecount = 0 IDIndex = 0 best_matchIndex = 0 fr1Index = 0 cdr1Index = 0 fr2Index = 0 cdr2Index = 0 fr3Index = 0 first = True IDlist = [] mutationList = [] mutationListByID = {} cdr1AALengthDic = {} cdr2AALengthDic = {} LengthDic = {} cdr1LengthIndex = 0 cdr2LengthIndex = 0 tandem_sum_by_class = defaultdict(int) expected_tandem_sum_by_class = defaultdict(float) with open(infile, 'r') as i: for line in i: if first: linesplt = line.split("\t") IDIndex = linesplt.index("Sequence.ID") best_matchIndex = linesplt.index("best_match") fr1Index = linesplt.index("FR1.IMGT") cdr1Index = linesplt.index("CDR1.IMGT") fr2Index = linesplt.index("FR2.IMGT") cdr2Index = linesplt.index("CDR2.IMGT") fr3Index = linesplt.index("FR3.IMGT") fr1LengthIndex = linesplt.index("FR1.IMGT.Nb.of.nucleotides") fr2LengthIndex = linesplt.index("FR2.IMGT.Nb.of.nucleotides") fr3LengthIndex = linesplt.index("FR3.IMGT.Nb.of.nucleotides") cdr1LengthIndex = linesplt.index("CDR1.IMGT.Nb.of.nucleotides") cdr2LengthIndex = linesplt.index("CDR2.IMGT.Nb.of.nucleotides") cdr1AALengthIndex = linesplt.index("CDR1.IMGT.length") cdr2AALengthIndex = linesplt.index("CDR2.IMGT.length") first = False continue linecount += 1 linesplt = line.split("\t") ID = linesplt[IDIndex] genedic[ID] = linesplt[best_matchIndex] mutationdic[ID + "_FR1"] = [] if len(linesplt[fr1Index]) > 5 and empty_region_filter == "leader": mutationdic[ID + "_FR1"] = [Mutation.from_string(x) for x in linesplt[fr1Index].split("|") if x] mutationdic[ID + "_CDR1"] = [] if len(linesplt[cdr1Index]) > 5 and empty_region_filter in ["leader", "FR1"]: mutationdic[ID + "_CDR1"] = [Mutation.from_string(x) for x in linesplt[cdr1Index].split("|") if x] mutationdic[ID + "_FR2"] = [] if len(linesplt[fr2Index]) > 5 and empty_region_filter in ["leader", "FR1", "CDR1"]: mutationdic[ID + "_FR2"] = [Mutation.from_string(x) for x in linesplt[fr2Index].split("|") if x] mutationdic[ID + "_CDR2"] = [] if len(linesplt[cdr2Index]) > 5: mutationdic[ID + "_CDR2"] = [Mutation.from_string(x) for x in linesplt[cdr2Index].split("|") if x] mutationdic[ID + "_FR2-CDR2"] = mutationdic[ID + "_FR2"] + mutationdic[ID + "_CDR2"] mutationdic[ID + "_FR3"] = [] if len(linesplt[fr3Index]) > 5: mutationdic[ID + "_FR3"] = [Mutation.from_string(x) for x in linesplt[fr3Index].split("|") if x] mutationList += mutationdic[ID + "_FR1"] + mutationdic[ID + "_CDR1"] + mutationdic[ID + "_FR2"] + mutationdic[ID + "_CDR2"] + mutationdic[ID + "_FR3"] mutationListByID[ID] = mutationdic[ID + "_FR1"] + mutationdic[ID + "_CDR1"] + mutationdic[ID + "_FR2"] + mutationdic[ID + "_CDR2"] + mutationdic[ID + "_FR3"] fr1Length = int_or_zero(linesplt[fr1LengthIndex]) fr2Length = int_or_zero(linesplt[fr2LengthIndex]) fr3Length = int_or_zero(linesplt[fr3LengthIndex]) cdr1Length = int_or_zero(linesplt[cdr1LengthIndex]) cdr2Length = int_or_zero(linesplt[cdr2LengthIndex]) LengthDic[ID] = (fr1Length, cdr1Length, fr2Length, cdr2Length, fr3Length) cdr1AALengthDic[ID] = int_or_zero(linesplt[cdr1AALengthIndex]) cdr2AALengthDic[ID] = int_or_zero(linesplt[cdr2AALengthIndex]) IDlist += [ID] print("len(mutationdic) =", len(mutationdic)) with open(os.path.join(os.path.dirname(os.path.abspath(infile)), "mutationdict.txt"), 'w') as out_handle: for ID, lst in mutationdic.items(): for mut in lst: out_handle.write("{0}\t{1}\n".format(ID, "\t".join([str(x) for x in mut]))) #tandem mutation stuff tandem_frequency = defaultdict(int) mutation_frequency = defaultdict(int) mutations_by_id_dic = {} first = True mutation_by_id_file = os.path.join(os.path.dirname(outfile), "mutation_by_id.txt") with open(mutation_by_id_file, 'r') as mutation_by_id: for l in mutation_by_id: if first: first = False continue splt = l.split("\t") mutations_by_id_dic[splt[0]] = int(splt[1]) tandem_file = os.path.join(os.path.dirname(outfile), "tandems_by_id.txt") with open(tandem_file, 'w') as o: highest_tandem_length = 0 # LengthDic stores length as a tuple # (fr1Length, cdr1Length, fr2Length, cdr2Length, fr3Length) # To get the total length, we can sum(region_lengths) # To get the total length for leader: # sum(region_lengths[0:]) (Equivalent to everything) # sum(region_lengths[1:]) Gets everything except FR1 etc. # We determine the position to start summing below. # This returns 0 for leader, 1 for FR1 etc. length_start_pos = REGION_FILTERS.index(empty_region_filter) if empty_region_filter == "None": length_start_pos = 0 o.write("Sequence.ID\tnumber_of_mutations\tnumber_of_tandems\tregion_length\texpected_tandems\tlongest_tandem\ttandems\n") for ID in IDlist: mutations = mutationListByID[ID] region_length = sum(LengthDic[ID][length_start_pos:]) if len(mutations) == 0: continue last_mut = max(mutations, key=lambda x: int(x[1])) last_mut_pos = int(last_mut[1]) mut_positions = [False] * (last_mut_pos + 1) for mutation in mutations: frm, where, to, frmAA, whereAA, toAA, thing = mutation where = int(where) mut_positions[where] = True tandem_muts = [] tandem_start = -1 tandem_length = 0 for i in range(len(mut_positions)): if mut_positions[i]: if tandem_start == -1: tandem_start = i tandem_length += 1 #print "".join(["1" if x else "0" for x in mut_positions[:i+1]]) else: if tandem_length > 1: tandem_muts.append((tandem_start, tandem_length)) #print "{0}{1} {2}:{3}".format(" " * (i - tandem_length), "^" * tandem_length, tandem_start, tandem_length) tandem_start = -1 tandem_length = 0 if tandem_length > 1: # if the sequence ends with a tandem mutation tandem_muts.append((tandem_start, tandem_length)) if len(tandem_muts) > 0: if highest_tandem_length < len(tandem_muts): highest_tandem_length = len(tandem_muts) longest_tandem = max(tandem_muts, key=lambda x: x[1]) if len(tandem_muts) else (0, 0) num_mutations = mutations_by_id_dic[ID] # len(mutations) f_num_mutations = float(num_mutations) num_tandem_muts = len(tandem_muts) expected_tandem_muts = f_num_mutations * (f_num_mutations - 1.0) / float(region_length) # String format and round disagree slightly (see 3.605). # So round before formatting. o.write(f"{ID}\t{num_mutations}\t{num_tandem_muts}\t{region_length}\t" f"{round(expected_tandem_muts, 2):.2f}\t" f"{longest_tandem[1]}\t{tandem_muts}\n") gene = genedic[ID] if gene.find("unmatched") == -1: tandem_sum_by_class[gene] += num_tandem_muts expected_tandem_sum_by_class[gene] += expected_tandem_muts tandem_sum_by_class["all"] += num_tandem_muts expected_tandem_sum_by_class["all"] += expected_tandem_muts gene = gene[:3] if gene in ["IGA", "IGG"]: tandem_sum_by_class[gene] += num_tandem_muts expected_tandem_sum_by_class[gene] += expected_tandem_muts else: tandem_sum_by_class["unmatched"] += num_tandem_muts expected_tandem_sum_by_class["unmatched"] += expected_tandem_muts for tandem_mut in tandem_muts: tandem_frequency[str(tandem_mut[1])] += 1 #print "\t".join([ID, str(len(tandem_muts)), str(longest_tandem[1]) , str(tandem_muts)]) tandem_freq_file = os.path.join(os.path.dirname(outfile), "tandem_frequency.txt") with open(tandem_freq_file, 'w') as o: for frq in sorted([int(x) for x in list(tandem_frequency.keys())]): o.write("{0}\t{1}\n".format(frq, tandem_frequency[str(frq)])) tandem_row = [] genes_extra = list(genes) genes_extra.append("all") for x, y, in zip([tandem_sum_by_class[x] for x in genes_extra], [expected_tandem_sum_by_class[x] for x in genes_extra]): if y != 0: tandem_row += [x, round(y, 2), round(x / y, 2)] else: tandem_row += [x, round(y, 2), 0] tandem_freq_file = os.path.join(os.path.dirname(outfile), "shm_overview_tandem_row.txt") with open(tandem_freq_file, 'w') as o: o.write("Tandems/Expected (ratio),{0}\n".format(",".join([str(x) for x in tandem_row]))) #print mutationList, linecount AALength = (int(max(mutationList, key=lambda i: int(i[4]) if i[4] and i[5] != ";" else 0)[4]) + 1) # [4] is the position of the AA mutation, None if silent if AALength < 60: AALength = 64 AA_mutation = [0] * AALength AA_mutation_dic = {"IGA": AA_mutation[:], "IGG": AA_mutation[:], "IGM": AA_mutation[:], "IGE": AA_mutation[:], "unm": AA_mutation[:], "all": AA_mutation[:]} AA_mutation_empty = AA_mutation[:] print("AALength:", AALength) aa_mutations_by_id_file = outfile[:outfile.rindex("/")] + "/aa_id_mutations.txt" with open(aa_mutations_by_id_file, 'w') as o: o.write("ID\tbest_match\t" + "\t".join([str(x) for x in range(1,AALength)]) + "\n") for ID in list(mutationListByID.keys()): AA_mutation_for_ID = AA_mutation_empty[:] for mutation in mutationListByID[ID]: if mutation[4] and mutation[5] != ";": AA_mutation_position = int(mutation[4]) try: AA_mutation[AA_mutation_position] += 1 AA_mutation_for_ID[AA_mutation_position] += 1 except Exception as e: print(e) print(mutation) sys.exit() clss = genedic[ID][:3] AA_mutation_dic[clss][AA_mutation_position] += 1 o.write(ID + "\t" + genedic[ID] + "\t" + "\t".join([str(x) for x in AA_mutation_for_ID[1:]]) + "\n") #absent AA stuff absentAACDR1Dic = defaultdict(list) absentAACDR1Dic[5] = list(range(29,36)) absentAACDR1Dic[6] = list(range(29,35)) absentAACDR1Dic[7] = list(range(30,35)) absentAACDR1Dic[8] = list(range(30,34)) absentAACDR1Dic[9] = list(range(31,34)) absentAACDR1Dic[10] = list(range(31,33)) absentAACDR1Dic[11] = [32] absentAACDR2Dic = defaultdict(list) absentAACDR2Dic[0] = list(range(55,65)) absentAACDR2Dic[1] = list(range(56,65)) absentAACDR2Dic[2] = list(range(56,64)) absentAACDR2Dic[3] = list(range(57,64)) absentAACDR2Dic[4] = list(range(57,63)) absentAACDR2Dic[5] = list(range(58,63)) absentAACDR2Dic[6] = list(range(58,62)) absentAACDR2Dic[7] = list(range(59,62)) absentAACDR2Dic[8] = list(range(59,61)) absentAACDR2Dic[9] = [60] absentAA = [len(IDlist)] * (AALength-1) for k, cdr1Length in cdr1AALengthDic.items(): for c in absentAACDR1Dic[cdr1Length]: absentAA[c] -= 1 for k, cdr2Length in cdr2AALengthDic.items(): for c in absentAACDR2Dic[cdr2Length]: absentAA[c] -= 1 aa_mutations_by_id_file = outfile[:outfile.rindex("/")] + "/absent_aa_id.txt" with open(aa_mutations_by_id_file, 'w') as o: o.write("ID\tcdr1length\tcdr2length\tbest_match\t" + "\t".join([str(x) for x in range(1,AALength)]) + "\n") for ID in IDlist: absentAAbyID = [1] * (AALength-1) cdr1Length = cdr1AALengthDic[ID] for c in absentAACDR1Dic[cdr1Length]: absentAAbyID[c] -= 1 cdr2Length = cdr2AALengthDic[ID] for c in absentAACDR2Dic[cdr2Length]: absentAAbyID[c] -= 1 o.write(ID + "\t" + str(cdr1Length) + "\t" + str(cdr2Length) + "\t" + genedic[ID] + "\t" + "\t".join([str(x) for x in absentAAbyID]) + "\n") if linecount == 0: print("No data, exiting") with open(outfile, 'w') as o: o.write("RGYW (%)," + ("0,0,0\n" * len(genes))) o.write("WRCY (%)," + ("0,0,0\n" * len(genes))) o.write("WA (%)," + ("0,0,0\n" * len(genes))) o.write("TW (%)," + ("0,0,0\n" * len(genes))) sys.exit() RGYWCount = {} WRCYCount = {} WACount = {} TWCount = {} #IDIndex = 0 ataIndex = 0 tatIndex = 0 aggctatIndex = 0 atagcctIndex = 0 first = True with open(infile, 'r') as i: for line in i: if first: linesplt = line.split("\t") ataIndex = linesplt.index("X.a.t.a") tatIndex = linesplt.index("t.a.t.") aggctatIndex = linesplt.index("X.a.g.g.c.t..a.t.") atagcctIndex = linesplt.index("X.a.t..a.g.c.c.t.") first = False continue linesplt = line.split("\t") gene = linesplt[best_matchIndex] ID = linesplt[IDIndex] RGYW = [Hotspot.from_string(x) for x in linesplt[aggctatIndex].split("|") if x] WRCY = [Hotspot.from_string(x) for x in linesplt[atagcctIndex].split("|") if x] WA = [Hotspot.from_string(x) for x in linesplt[ataIndex].split("|") if x] TW = [Hotspot.from_string(x) for x in linesplt[tatIndex].split("|") if x] RGYWCount[ID], WRCYCount[ID], WACount[ID], TWCount[ID] = 0, 0, 0, 0 with open(os.path.join(os.path.dirname(os.path.abspath(infile)), "RGYW.txt"), 'a') as out_handle: for hotspot in RGYW: out_handle.write("{0}\t{1}\n".format(ID, "\t".join([str(x) for x in hotspot]))) mutationList = mutationdic[ID + "_FR1"] + mutationdic[ID + "_CDR1"] + mutationdic[ID + "_FR2"] + mutationdic[ID + "_CDR2"] + mutationdic[ID + "_FR3"] for mutation in mutationList: frm, where, to, AAfrm, AAwhere, AAto, junk = mutation mutation_in_RGYW = any(((start <= int(where) <= end) for (start, end, region) in RGYW)) mutation_in_WRCY = any(((start <= int(where) <= end) for (start, end, region) in WRCY)) mutation_in_WA = any(((start <= int(where) <= end) for (start, end, region) in WA)) mutation_in_TW = any(((start <= int(where) <= end) for (start, end, region) in TW)) in_how_many_motifs = sum([mutation_in_RGYW, mutation_in_WRCY, mutation_in_WA, mutation_in_TW]) if in_how_many_motifs > 0: RGYWCount[ID] += (1.0 * int(mutation_in_RGYW)) / in_how_many_motifs WRCYCount[ID] += (1.0 * int(mutation_in_WRCY)) / in_how_many_motifs WACount[ID] += (1.0 * int(mutation_in_WA)) / in_how_many_motifs TWCount[ID] += (1.0 * int(mutation_in_TW)) / in_how_many_motifs mutations_in_motifs_file = os.path.join(os.path.dirname(os.path.abspath(infile)), "mutation_in_motifs.txt") if not os.path.exists(mutation_by_id_file): with open(mutations_in_motifs_file, 'w') as out_handle: out_handle.write("{0}\n".format("\t".join([ "Sequence.ID", "mutation_position", "region", "from_nt", "to_nt", "mutation_position_AA", "from_AA", "to_AA", "motif", "motif_start_nt", "motif_end_nt", "rest" ]))) with open(mutations_in_motifs_file, 'a') as out_handle: motif_dic = {"RGYW": RGYW, "WRCY": WRCY, "WA": WA, "TW": TW} for mutation in mutationList: frm, where, to, AAfrm, AAwhere, AAto, junk = mutation for motif in list(motif_dic.keys()): for start, end, region in motif_dic[motif]: if start <= int(where) <= end: out_handle.write("{0}\n".format( "\t".join([ ID, str(where), region, frm, to, str(AAwhere), str(AAfrm), str(AAto), motif, str(start), str(end), str(junk) ]) )) def mean(lst): return (float(sum(lst)) / len(lst)) if len(lst) > 0 else 0.0 def median(lst): lst = sorted(lst) l = len(lst) if l == 0: return 0 if l == 1: return lst[0] l = int(l / 2) if len(lst) % 2 == 0: return float(lst[l] + lst[(l - 1)]) / 2.0 else: return lst[l] funcs = {"mean": mean, "median": median, "sum": sum} directory = outfile[:outfile.rfind("/") + 1] value = 0 valuedic = dict() for fname in list(funcs.keys()): for gene in genes: with open(directory + gene + "_" + fname + "_value.txt", 'r') as v: valuedic[gene + "_" + fname] = float(v.readlines()[0].rstrip()) with open(directory + "all_" + fname + "_value.txt", 'r') as v: valuedic["total_" + fname] = float(v.readlines()[0].rstrip()) def get_xyz(lst, gene, f, fname): x = round(round(f(lst), 1)) y = valuedic[gene + "_" + fname] z = str(round(x / float(y) * 100, 1)) if y != 0 else "0" return (str(x), str(y), z) dic = {"RGYW": RGYWCount, "WRCY": WRCYCount, "WA": WACount, "TW": TWCount} arr = ["RGYW", "WRCY", "WA", "TW"] for fname in list(funcs.keys()): func = funcs[fname] foutfile = outfile[:outfile.rindex("/")] + "/hotspot_analysis_" + fname + ".txt" with open(foutfile, 'w') as o: for typ in arr: o.write(typ + " (%)") curr = dic[typ] for gene in genes: if valuedic[gene + "_" + fname] == 0: o.write(",0,0,0") else: x, y, z = get_xyz([curr[x] for x in [y for y, z in genedic.items() if z.startswith(gene)]], gene, func, fname) o.write("," + x + "," + y + "," + z) x, y, z = get_xyz([y for x, y in curr.items() if not genedic[x].startswith("unmatched")], "total", func, fname) #x, y, z = get_xyz([y for x, y in curr.iteritems()], "total", func, fname) o.write("," + x + "," + y + "," + z + "\n") # for testing seq_motif_file = outfile[:outfile.rindex("/")] + "/motif_per_seq.txt" with open(seq_motif_file, 'w') as o: o.write("ID\tRGYW\tWRCY\tWA\tTW\n") for ID in IDlist: #o.write(ID + "\t" + str(round(RGYWCount[ID], 2)) + "\t" + str(round(WRCYCount[ID], 2)) + "\t" + str(round(WACount[ID], 2)) + "\t" + str(round(TWCount[ID], 2)) + "\n") o.write(ID + "\t" + str(RGYWCount[ID]) + "\t" + str(WRCYCount[ID]) + "\t" + str(WACount[ID]) + "\t" + str(TWCount[ID]) + "\n") if __name__ == "__main__": main()