from Graph_gff import Segments, Features, get_feature_start_on_segment, get_feature_stop_on_segment,invert_seg,search_segment global segments_on_target_genome segments_on_target_genome={} # get the start position of the features on the linear target genome, using their coordinates on the graph and the coordinantes of the segments on the genome def get_feature_start_on_target_genome(start_seg,feat_id,walk): seg_start_pos=segments_on_target_genome[start_seg][walk][-1][1] feat_start_pos=get_feature_start_on_segment(start_seg,feat_id) return seg_start_pos+feat_start_pos-1 # get the stop position of the features on the linear target genome, using their coordinates on the graph and the coordinantes of the segments on the genome def get_feature_stop_on_target_genome(stop_seg,feat_id,walk): seg_start_pos=segments_on_target_genome[stop_seg][walk][-1][1] feat_stop_pos=get_feature_stop_on_segment(stop_seg,feat_id) return seg_start_pos+feat_stop_pos-1 # get the start position of the features on the linear target genome for inverted features def get_feature_start_on_target_genome_inv(start_seg,feat_id,walk): seg_end_pos=segments_on_target_genome[start_seg][walk][-1][2] feat_start_pos=get_feature_start_on_segment(start_seg,feat_id) return seg_end_pos-feat_start_pos+1 # get the stop position of the features on the linear target genome for inverted features def get_feature_stop_on_target_genome_inv(stop_seg,feat_id,walk): seg_end_pos=segments_on_target_genome[stop_seg][walk][-1][2] feat_stop_pos=get_feature_stop_on_segment(stop_seg,feat_id) return seg_end_pos-feat_stop_pos+1 # functions to get the gff with one line per feature # check if the length of the feature on the target genome passes the filter max_diff def right_size(size,max_diff,feat): if max_diff==0: return True return not ((size>Features[feat].size*max_diff) or (size<Features[feat].size/max_diff)) # generates the line for the gff of the target genome def create_line_target_gff(first_seg,last_seg,feature_id,size_diff,inversion,walk,cov,id): [chr,strand,feature]=[segments_on_target_genome[first_seg][walk][-1][0],Features[feature_id].strand,Features[feature_id]] annotation=f'{feature.annot};Size_diff={size_diff};coverage={cov};sequence_ID={id}' # Nb_variants={var_count}; if inversion: start=get_feature_start_on_target_genome_inv(last_seg,feature_id,walk) stop=get_feature_stop_on_target_genome_inv(first_seg,feature_id,walk) strand=invert_strand(strand) else: start=get_feature_start_on_target_genome(first_seg,feature_id,walk) stop=get_feature_stop_on_target_genome(last_seg,feature_id,walk) if start>stop: temp=start start=stop stop=temp output_line=f'{chr}\tGrAnnoT\t{feature.type}\t{start}\t{stop}\t.\t{strand}\t.\t{annotation}\n' return output_line # functions to get the alignment for the transfered genes # creates an alignment for two segments def segment_aln(type,seg_seq,seg_a,seg_b,first,feature_id,last): match type: case "identity": if first: feature=Features[feature_id] seq_aln=get_segment_sequence(seg_seq,seg_a)[feature.pos_start-1:] elif last: feature=Features[feature_id] seq_aln=get_segment_sequence(seg_seq,seg_a)[:feature.pos_stop] else: seq_aln=get_segment_sequence(seg_seq,seg_a) line_a=seq_aln line_b=seq_aln len_aln=len(seq_aln) line_c=len_aln*"*" case "substitution": seq_aln_a=get_segment_sequence(seg_seq,seg_a) seq_aln_b=get_segment_sequence(seg_seq,seg_b) len_a=len(seq_aln_a) len_b=len(seq_aln_b) if len_a>len_b: diff_len=len_a-len_b line_a=seq_aln_a line_b=seq_aln_b+diff_len*"-" line_c=len_a*" " else: diff_len=len_b-len_a line_a=seq_aln_a+diff_len*"-" line_b=seq_aln_b line_c=len_b*" " case "insertion": seq_aln_b=get_segment_sequence(seg_seq,seg_b) len_b=len(seq_aln_b) line_a=len_b*"-" line_b=seq_aln_b line_c=len_b*" " case "deletion": if first: feature=Features[feature_id] seq_aln_a=get_segment_sequence(seg_seq,seg_a)[feature.pos_start-1:] else: seq_aln_a=get_segment_sequence(seg_seq,seg_a) len_a=len(seq_aln_a) line_a=seq_aln_a line_b=len_a*"-" line_c=len_a*" " case "end_deletion": seq_aln_a="" for segment in seg_a[:-1]: seq_aln_a+=get_segment_sequence(seg_seq,segment) feature=Features[feature_id] seq_aln_a+=get_segment_sequence(seg_seq,seg_a[-1])[0:feature.pos_stop] # for the last segment, only take the part that the feature is on len_a=len(seq_aln_a) line_a=seq_aln_a line_b=len_a*"-" line_c=len_a*" " return [line_a,line_b,line_c,False] # check the orientation of the segment later # formats the alignment lines def parse_aln_lines(line_a,line_b,line_c,feature_id): if (len(line_a)!=len(line_b)) or (len(line_b)!=len(line_c)): print("line lengths differ in alignment") len_to_parse=len(line_a) len_parsed=0 aln_line="" nb_res_a=0 nb_res_b=0 while len_parsed<len_to_parse: len_header=len(feature_id)+11 headers=[feature_id+"_source ",feature_id+"_target ",len_header*" "] add_a=line_a[len_parsed:len_parsed+60] add_b=line_b[len_parsed:len_parsed+60] add_c=line_c[len_parsed:len_parsed+60] nb_res_a+=len(add_a)-add_a.count("-") nb_res_b+=len(add_b)-add_b.count("-") aln_line+=f'{headers[0]}{add_a} {nb_res_a}\n' aln_line+=f'{headers[1]}{add_b} {nb_res_b}\n' aln_line+=f'{headers[2]}{add_c}\n\n' len_parsed+=60 aln_line+="\n" return aln_line # creates the alignment for a feature def create_line_aln(feature_path_source_genome,feature_path_target_genome,seg_seq,feature_id): line_a="" line_b="" line_c="" [i,j]=[0,0] first=True # when writing the first part of the feature, dont take the whole segment, only the part that the feature is on last=False # same for the last part of the feature while (i<len(feature_path_source_genome)) and (j<len(feature_path_target_genome)): if i==len(feature_path_source_genome)-1: last=True if feature_path_source_genome[i] != feature_path_target_genome[j]: # if there is a difference between the two paths if feature_path_target_genome[j] not in feature_path_source_genome: # if the segment in target genome is absent in source genome if feature_path_source_genome[i] not in feature_path_target_genome: # if the segment in source genome is absent is target genome : substitution [add_a,add_b,add_c,first]=segment_aln("substitution",seg_seq,feature_path_source_genome[i],feature_path_target_genome[j],first,feature_id,last) line_a+=add_a;line_b+=add_b;line_c+=add_c i+=1;j+=1 else: # target genome segment not in source_genome, but source_genome segment in target genome : insertion [add_a,add_b,add_c,first]=segment_aln("insertion",seg_seq,"",feature_path_target_genome[j],first,feature_id,last) line_a+=add_a;line_b+=add_b;line_c+=add_c j+=1 elif feature_path_source_genome[i] not in feature_path_target_genome: # source_genome segment not in target genome, but target genome segment in source_genome : deletion [add_a,add_b,add_c,first]=segment_aln("deletion",seg_seq,feature_path_source_genome[i],"",first,feature_id,last) line_a+=add_a;line_b+=add_b;line_c+=add_c i+=1 else : # if both segments are present in the other genome but not at the same position. weird case never found yet [add_a,add_b,add_c,first]=segment_aln("substitution",seg_seq,feature_path_source_genome[i],feature_path_target_genome[j],first,feature_id,last) line_a+=add_a;line_b+=add_b;line_c+=add_c i+=1;j+=1 else: # segment present in both, no variation. [add_a,add_b,add_c,first]=segment_aln("identity",seg_seq,feature_path_source_genome[i],feature_path_target_genome[j],first,feature_id,last) line_a+=add_a;line_b+=add_b;line_c+=add_c i+=1;j+=1 if i<=len(feature_path_source_genome)-1: # if we didn't reach the length of the segment list for the first genome, the end is missing for the second genome [add_a,add_b,add_c,first]=segment_aln("end_deletion",seg_seq,feature_path_source_genome[i:],"",first,feature_id,last) line_a+=add_a;line_b+=add_b;line_c+=add_c return parse_aln_lines(line_a,line_b,line_c,feature_id) # functions to output the stats on the transfer # stats about missing segments and feature type, not used, will change. def stats_feature_missing_segment(feature_missing_segments,first_seg,last_seg,list_seg,feature_id,walk): # [feature_missing_first,feature_missing_middle,feature_missing_last,feature_missing_all,feature_missing_total,feature_total,feature_ok] feature_missing_segments[5].append(feature_id) if first_seg=='' : # no segment of the feature is in the genome, the feature is missing entirely feature_missing_segments[3].append(feature_id) elif first_seg != list_seg[0]: # the first segment is missing feature_missing_segments[0].append(feature_id) elif last_seg!=list_seg[-1]: # the last segment is missing feature_missing_segments[2].append(feature_id) # go through all the segments, check if some are missing in the middle of the feature elif (len(list_seg)!=1) and (feature_id not in feature_missing_segments[3]): # to access the second to last element for segment in list_seg[1-(len(list_seg)-2)]: if (segment not in segments_on_target_genome) or (walk not in segments_on_target_genome[segment]): feature_missing_segments[1].append(feature_id) break # go through the segments, to see if one is missing anywhere on the feature for segment in list_seg: if (segment not in segments_on_target_genome) or (walk not in segments_on_target_genome[segment]): if feature_id not in feature_missing_segments[4]: feature_missing_segments[4].append(feature_id) break # if the feature doesnt have a missing segment, it is complete. ADD THE PATH CHECK FOR INSERTIONS !! if feature_id not in feature_missing_segments[4]: feature_missing_segments[6].append(feature_id) def get_annot_features(list_features): list_annot_features=[] for feature in list_features: list_annot_features.append(Features[feature].note) return list_annot_features def count_hypput_total(list_annot_first): total=len(list_annot_first) count_hypput=0 for annot in list_annot_first: if ("hypothetical" in annot) or ("putative" in annot): count_hypput+=1 return [count_hypput,total] # print stats on the transfer : number of feature that have segments in different positions missing. def stats_features(feature_missing_segments): # [feature_missing_first,feature_missing_middle,feature_missing_last,feature_missing_all,feature_missing_total,feature_total,feature_ok] list_annot_first=get_annot_features(feature_missing_segments[0]) [hyp_put,total]=count_hypput_total(list_annot_first) print("\nthe first segment is missing for", total,"features, including",round(100*(hyp_put)/total,2),"% hypothetical or putative.") list_annot_middle=get_annot_features(feature_missing_segments[1]) [hyp_put,total]=count_hypput_total(list_annot_middle) print("a middle segment is missing for", total,"features, including",round(100*(hyp_put)/total,2),"% hypothetical or putative.") list_annot_last=get_annot_features(feature_missing_segments[2]) [hyp_put,total]=count_hypput_total(list_annot_last) print("the last segment is missing for", total,"features, including",round(100*(hyp_put)/total,2),"% hypothetical or putative.") list_annot_all=get_annot_features(feature_missing_segments[3]) [hyp_put,total]=count_hypput_total(list_annot_all) print(total,"features are entirely missing, including",round(100*(hyp_put)/total,2),"% hypothetical or putative.") list_annot_total=get_annot_features(feature_missing_segments[4]) [hyp_put,total]=count_hypput_total(list_annot_total) print("there is at least one segment missing for", total,"features, including",round(100*(hyp_put)/total,2),"% hypothetical or putative.") list_annot_ok=get_annot_features(feature_missing_segments[6]) [hyp_put,total]=count_hypput_total(list_annot_ok) print(total ,"features are entirely present in the new genome, including",round(100*(hyp_put)/total,2),"% hypothetical or putative.") list_annot_features=get_annot_features(feature_missing_segments[5]) [hyp_put,total]=count_hypput_total(list_annot_features) print("there is", total,"features in total, including",round(100*(hyp_put)/total,2),"% hypothetical or putative.") # functions to generate the different gffs # appends a dictionnary that associates a segments with its position on all the walks it's on (start stop and index in the segmnet list) def get_segments_positions_on_genome(pos_seg): # add to the dict the info about the segments. bed=open(pos_seg,'r') lines=bed.readlines() # read line by line ? bed.close() seg_count=0 file_name='.'.join(pos_seg.split('/')[-1].split('.')[0:-1]) # split by '.' to get the filename without the extention, then join by '.' in case there is a '.' in the filename for line in lines: line=line.split() [seg,chrom,start,stop,strand,index]=[line[3],line[0],int(line[1])+1,int(line[2]),line[3][0:1],seg_count] # +1 in the start to convert the bed 0-based coordinate to a 1-based system # check if segment present twice on the same walk ??? #segments_on_target_genome[seg]=[chrom,start,stop,strand,index,file_name] if seg not in segments_on_target_genome: segments_on_target_genome[seg]={} # dict of walks->segment_info; you get the info about the segment for each walk if file_name not in segments_on_target_genome[seg]: segments_on_target_genome[seg][file_name]=list() segments_on_target_genome[seg][file_name].append([chrom,start,stop,strand,index]) seg_count+=1 # look for the segment on either strand of the target genome def search_seg_on_target_genome(segment): inverted_segment=invert_seg(segment) if segment in segments_on_target_genome: #if inverted_segment in segments_on_target_genome: # print(segment," found in both orientations") return segment elif inverted_segment in segments_on_target_genome: #print("inverted seg found *****") return inverted_segment else: return False # look for a segment on a walk, in either orientations def search_seg_on_walk(segment,walk): # for now just print the first found, look for several later... inverted_segment=invert_seg(segment) if segment in segments_on_target_genome: if walk in segments_on_target_genome[segment]: return segment elif inverted_segment in segments_on_target_genome: if walk in segments_on_target_genome[inverted_segment]: return inverted_segment else: return False # generates a dictionnary that associaces the segments to their sequence : s5->AGGCTAA def get_segments_sequence(segments_file,segments_list): file_segments=open(segments_file,'r') lines_segments=file_segments.readlines() file_segments.close() seg_seq={} for line in lines_segments: line=line.split() seg_id='s'+line[1] if seg_id in segments_list: seg_seq[seg_id]=line[2] return seg_seq # generates a dictionnary that associates a walk_name to a list of segments : chr10->[>s1,>s2,>s4] def get_paths(walks_file,target_genome): file_walks=open(walks_file,'r') lines_walks=file_walks.readlines() file_walks.close() paths={} for line in lines_walks: line=line.split() seq_name=line[1]+"_"+line[3] if target_genome in seq_name: # get the walk of the genome path=line[6].split(',')[1:] list_segments=[] for segment in path: if segment[0:1]=='>': list_segments.append('>s'+segment[1:]) elif segment[0:1]=='<': list_segments.append('<s'+segment[1:]) paths[seq_name]=list_segments return paths # get the first and last segment of the list that is in the target genome (possibly several pairs) def get_first_last_seg(list_seg): list_first_last_segs=[] [first_seg_found,last_seg_found,walk_found]=['','',''] list_walks=get_walks_feature_cross(list_seg) # get all the walks where there is a segment of the feature for walk in list_walks: # find the first and last seg for each walk for segment in list_seg: # look for first_seg seg_found=search_seg_on_walk(segment,walk) if seg_found: first_seg_found=seg_found break if first_seg_found!='': # look for last_seg for segment in reversed(list_seg): last_seg_found=search_seg_on_walk(segment,walk) if last_seg_found: walk_found=walk break list_first_last_segs.append([first_seg_found,last_seg_found,walk_found]) [first_seg_found,last_seg_found,walk_found]=['','',''] # return all the match return list_first_last_segs # functions to get the detail of the variations in the features # find all the walks that contain a segment of the feature (list_seg is the walk of the feature on the source genome) def get_walks_feature_cross(list_seg): list_walks=list() for segment in list_seg: seg_found=search_seg_on_target_genome(segment) if seg_found: # if the segment or the reverse complement is on the target genome for walk in segments_on_target_genome[seg_found]: if walk not in list_walks: list_walks.append(walk) return list_walks # add the paths of the feature on the target genome in the object Feature def add_target_genome_paths(feature_id,target_genome_paths): feature=Features[feature_id] list_seg=feature.segments_list_source list_first_last_segs=get_first_last_seg(list_seg) for match in list_first_last_segs: [first_seg,last_seg,walk_name]=match feature_path=[walk_name] # get the first and last segments of all the copies [first_last_segs_list]=detect_gene_copies(list_seg,walk_name,feature_id) copy_number=0 for first_seg,last_seg in first_last_segs_list: # get the feature path for all the copies copy_number+=1 copy_id="copy_"+str(copy_number) # get the copy that corresponds to this pair of first_seg,last_seg feature_path.append(copy_id) feature_path.append(get_feature_path(target_genome_paths[walk_name],first_seg,last_seg,walk_name,copy_id,feature_id)) feature.segments_list_target.append(feature_path) if len(list_first_last_segs)==0: # the latter steps expect this list to not be empty. feature.segments_list_target.append(['',[]]) def detect_gene_copies(list_seg_source,walk_name,feature_id): # find all copies of all segments from the gene in the target genome (in both orientations) index=0 list_seg_target=[] # contains list of info for each seg [seg_id,seg_strand,start_pos,index_on_source_walk] list_seg_source_unstranded=[] for seg in list_seg_source: list_seg_source_unstranded.append([seg[1:],seg[0]]) # seg_id,seg_strand : [s24,>] seg_inverted=invert_seg(seg) # look for all the segment copies in the target genome walk, in both orientations if (seg in segments_on_target_genome) and (walk_name in segments_on_target_genome[seg]): for copy in segments_on_target_genome[seg][walk_name]: seg_info=[seg[1:],seg[0],int(copy[1]),index] # [s24,>,584425,4] list_seg_target.append(seg_info) if (seg_inverted in segments_on_target_genome) and (walk_name in segments_on_target_genome[seg_inverted]) : for copy in segments_on_target_genome[seg_inverted][walk_name]: seg_info=[seg_inverted[1:],seg_inverted[0],int(copy[1]),index] list_seg_target.append(seg_info) index+=1 list_seg_target.sort(key=sort_seg_info) # order the list of segments by start position old_index=list_seg_target[0][3] old_strand=list_seg_target[0][1] copy_number=1 first_segs_list=[] last_segs_list=[] old_seg_id=list_seg_target[0][1]+list_seg_target[0][0] first_segs_list.append(old_seg_id) # adjust old_index for the first iteration of the loop first_inversion=(old_strand!=list_seg_source_unstranded[old_index][1]) if first_inversion: old_index+=1 else: old_index-=1 # find each copy of the gene in the ordered list of segments for seg in list_seg_target: new_seg_id=seg[1]+seg[0] new_index=seg[3] # index in the list_source new_strand=seg[1] seg_start=seg[2] inversion=(seg[1]!=list_seg_source_unstranded[new_index][1]) # inversion if this segment's strand is not the same as in the source walk if inversion : if (old_strand==new_strand) and (old_index>new_index): # if the index decreases and the strand stays the same, it is the same gene copy for segment in segments_on_target_genome[new_seg_id][walk_name]: if segment[1]==seg_start: copy_id="copy_"+str(copy_number) feat_copy=(feature_id,copy_id) segment.append(feat_copy) break else: # end of the copy copy_number+=1 last_segs_list.append(old_seg_id) first_segs_list.append(new_seg_id) for segment in segments_on_target_genome[new_seg_id][walk_name]: if segment[1]==seg_start: copy_id="copy_"+str(copy_number) feat_copy=(feature_id,copy_id) segment.append(feat_copy) break else: if (old_strand==new_strand) and (old_index<new_index): # if the index increases and the strand stays the same, it is the same gene copy for segment in segments_on_target_genome[new_seg_id][walk_name]: if segment[1]==seg_start: copy_id="copy_"+str(copy_number) feat_copy=(feature_id,copy_id) segment.append(feat_copy) break else: # end of the copy copy_number+=1 last_segs_list.append(old_seg_id) first_segs_list.append(new_seg_id) for segment in segments_on_target_genome[new_seg_id][walk_name]: if segment[1]==seg_start: copy_id="copy_"+str(copy_number) feat_copy=(feature_id,copy_id) segment.append(feat_copy) break # if the strand changes, it is possible that it is an inversion inside the gene. treat this case later old_strand=new_strand old_index=new_index old_seg_id=new_seg_id last_segs_list.append(old_seg_id) first_last_segs_list=[] index=0 for first_seg in first_segs_list: last_seg=last_segs_list[index] pair=(first_seg,last_seg) first_last_segs_list.append(pair) index+=1 return [first_last_segs_list] # return a list of pairs (first_seg,last_seg) def sort_seg_info(seg_info): return seg_info[2] # find the feature's path in target genome walk def get_feature_path(target_genome_path,first_seg,last_seg,walk_name,copy_id,feature_id): # look for first_seg and last_seg that has the right copy_id for this feature seg_in_walk=segments_on_target_genome[first_seg][walk_name] for seg_occurence in seg_in_walk: for feat_seg in seg_occurence[5:]: if (feat_seg[0]==feature_id) & (feat_seg[1]==copy_id): first_seg_index=seg_occurence[4] # find first_seg_index seg_in_walk=segments_on_target_genome[last_seg][walk_name] for seg_occurence in seg_in_walk: for feat_seg in seg_occurence[5:]: if (feat_seg[0]==feature_id) & (feat_seg[1]==copy_id): last_seg_index=seg_occurence[4] # find last_seg_index first_index=min(first_seg_index,last_seg_index) last_index=max(first_seg_index,last_seg_index) feature_path_target_genome=target_genome_path[first_index:last_index+1] return feature_path_target_genome # count the variations between two lists def count_variations(feature_id,target_list): feature=Features[feature_id] if len(target_list)!=0: source_list=feature.segments_list_source inversion=detect_feature_inversion(source_list,target_list) if inversion: target_list=invert_segment_list(target_list) target_dict=dict.fromkeys(target_list,"") source_dict=dict.fromkeys(source_list,"") # convert list into dict to search segments in dict quicker. var_count=0 for segment in source_dict: if segment not in target_dict: var_count+=1 for segment in target_dict: if segment not in source_dict: var_count+=1 # this counts the substitutions twice, as insertion+deletion. return var_count # get the coverage and sequence id of a feature def get_id_cov(feature_id,seg_size,target_list): # seg_size has unoriented segments : s25 feature=Features[feature_id] source_list=feature.segments_list_source inversion=detect_feature_inversion(source_list,target_list) if inversion: target_list=invert_segment_list(target_list) [match,subs,inser,delet]=[0,0,0,0] [i,j]=[0,0] first=True # when writing the first part of the feature, dont take the whole segment, only the part that the feature is on last=False # same for the last part of the feature # for id and ins. while (i<len(source_list)) and (j<len(target_list)): if i==len(source_list)-1: last=True if source_list[i] != target_list[j]: # if there is a difference between the two paths if target_list[j] not in source_list: # if the segment in target genome is absent in source genome if source_list[i] not in target_list: # if the segment in source genome is absent is target genome : substitution add=segment_id_cov("substitution",seg_size,source_list[i],target_list[j],first,feature,last) match+=add[0];subs+=add[1];inser+=add[2];delet+=add[3];first=add[4] i+=1;j+=1 else: # target genome segment not in source_genome, but source_genome segment in target genome : insertion add=segment_id_cov("insertion",seg_size,source_list[i],target_list[j],first,feature,last) match+=add[0];subs+=add[1];inser+=add[2];delet+=add[3];first=add[4] j+=1 elif source_list[i] not in target_list: # source_genome segment not in target genome, but target genome segment in source_genome : deletion add=segment_id_cov("deletion",seg_size,source_list[i],target_list[j],first,feature,last) match+=add[0];subs+=add[1];inser+=add[2];delet+=add[3];first=add[4] i+=1 else : # if both segments are present in the other genome but not at the same position. weird case never found yet add=segment_id_cov("substitution",seg_size,source_list[i],target_list[j],first,feature,last) match+=add[0];subs+=add[1];inser+=add[2];delet+=add[3];first=add[4] i+=1;j+=1 else: # segment present in both, no variation. add=segment_id_cov("identity",seg_size,source_list[i],target_list[j],first,feature,last) match+=add[0];subs+=add[1];inser+=add[2];delet+=add[3];first=add[4] i+=1;j+=1 if i<=len(source_list)-1: # if we didn't reach the length of the segment list for the first genome, the end is missing for the second genome add=segment_id_cov("end_deletion",seg_size,source_list[i:],'',first,feature,last) match+=add[0];subs+=add[1];inser+=add[2];delet+=add[3];first=add[4] cov=round((match+subs)/(match+subs+delet),3) id=round(match/(match+subs+inser+delet),3) #var_count=count_variations(feature_id,target_list) return [cov,id] # computes the cov/id calculation for a segment pair def segment_id_cov(type,seg_size,seg_a,seg_b,first,feature,last): [match,subs,inser,delet]=[0,0,0,0] match type: case "identity": if first: match+=seg_size[seg_a[1:]]-feature.pos_start+1 elif last: match+=feature.pos_stop else: match+=seg_size[seg_a[1:]] case "substitution": if seg_size[seg_b[1:]]!=seg_size[seg_a[1:]]: # substitution can be between segments of different size if seg_size[seg_b[1:]]>seg_size[seg_a[1:]]: subs+=seg_size[seg_a[1:]] inser+=seg_size[seg_b[1:]]-seg_size[seg_a[1:]] elif seg_size[seg_b[1:]]<seg_size[seg_a[1:]]: subs+=seg_size[seg_b[1:]] delet+=seg_size[seg_a[1:]]-seg_size[seg_b[1:]] else: subs+=seg_size[seg_a[1:]] case "insertion": inser+=seg_size[seg_b[1:]] case "deletion": if first: delet+=seg_size[seg_a[1:]]-feature.pos_start+1 else: delet+=seg_size[seg_a[1:]] case "end_deletion": for seg in seg_a[:-1]: delet+=seg_size[seg[1:]] delet+=feature.pos_stop return [match,subs,inser,delet,False] # check the orientation of the segment later # invert the given strand def invert_strand(strand): match strand: case "+": return "-" case "-": return "+" case ">": return "<" case "<": return ">" case default: return "" # outputs the nucleotide sequence of a list of segments, corresponding to the end of a feature def get_sequence_list_seg(list_seg,i,feature,seg_seq): del_sequence="" for k in range(i,len(list_seg)): if k==len(list_seg)-1: del_sequence+=get_segment_sequence(seg_seq,list_seg[k])[0:feature.pos_stop] else: del_sequence+=get_segment_sequence(seg_seq,list_seg[k]) return del_sequence # outputs the sequence of an oriented segment def get_segment_sequence(seg_seq,segment): if segment[0]==">": return seg_seq[segment[1:]] else: return reverse_complement(seg_seq[segment[1:]]) # outputs the reverse complement of a sequence def reverse_complement(sequence): sequence_rc="" for char in sequence: sequence_rc+=complement(char) return sequence_rc[::-1] # outputs the reverse complement of a nucleotide def complement(nucl): match nucl: case "A": return "T" case "C": return "G" case "G": return "C" case "T": return "A" return nucl # stores information about a feature and its current variation class Variation: def __init__(self,feature_id,feature_type,chr,start_new,stop_new,inversion,size_diff,size_new): self.feature_id=feature_id self.feature_type=feature_type self.chr=chr self.start_new=start_new self.stop_new=stop_new self.inversion=inversion self.size_diff=size_diff self.size_new=size_new self.type='' self.last_seg_in_target='' self.seg_ref=list() self.seg_alt=list() # initiate a Variation object with the information on the feature it is on def create_var(feature_id,first_seg,last_seg,walk): feature=Features[feature_id] # get feature paths on the original genome and on the target genome feature_path_target_genome=feature.segments_list_target[0][1] feature_path_source_genome=feature.segments_list_source inversion=detect_feature_inversion(feature_path_source_genome,feature_path_target_genome) if inversion: feature_path_target_genome=invert_segment_list(feature_path_target_genome) start_new_genome=get_feature_start_on_target_genome_inv(last_seg,feature_id,walk) stop_new_genome=get_feature_stop_on_target_genome_inv(first_seg,feature_id,walk) size_new_genome=start_new_genome-stop_new_genome+1 else: start_new_genome=get_feature_start_on_target_genome(first_seg,feature_id,walk) stop_new_genome=get_feature_stop_on_target_genome(last_seg,feature_id,walk) size_new_genome=stop_new_genome-start_new_genome+1 size_diff=str(size_new_genome-feature.size) sequence_name=segments_on_target_genome[first_seg][walk][-1][0] variation=Variation(feature_id,feature.type,sequence_name,start_new_genome,stop_new_genome,inversion,size_diff,size_new_genome) return(variation,feature_path_source_genome,feature_path_target_genome) # reset the informations of the variation, but keep the information about the feature def reset_var(variation): variation.type='' # make type enumerate variation.size_var=0 variation.start_var='' variation.start_var_index=0 variation.ref='' variation.alt='' # find the position of a substitution on the source and the target sequence def get_old_new_pos_substitution(feat_start,variation,start_feat_seg_target,feat,walk): seg_pos=search_segment(variation.start_var) pos_old=str(int(Segments[seg_pos].start)-int(feat_start)) var_start_seg=variation.start_on_target if variation.inversion: start_feat_seg_target=invert_seg(start_feat_seg_target) var_start_seg=invert_seg(var_start_seg) end_var=segments_on_target_genome[var_start_seg][walk][-1][2] start_feat=get_feature_start_on_target_genome_inv(start_feat_seg_target,feat,walk) pos_new=str(start_feat-end_var) else: start_var=segments_on_target_genome[var_start_seg][walk][-1][1] start_feat=get_feature_start_on_target_genome(start_feat_seg_target,feat,walk) pos_new=str(start_var-start_feat) return [pos_old,pos_new] # pos_old and pos_new are the base before the change # find the position of an insertion on the source and the target sequence def get_old_new_pos_insertion(variation,feat_start,start_feat_seg_target,feat,walk): seg_pos=search_segment(variation.start_var) # start_var is the segment AFTER the insertion pos_old=str(int(Segments[seg_pos].start)-int(feat_start)) start_var_seg=variation.start_var if variation.inversion: start_feat_seg_target=invert_seg(start_feat_seg_target) start_var_seg=invert_seg(start_var_seg) end_var=segments_on_target_genome[start_var_seg][walk][-1][2]+len(variation.alt) # start_var_seg is the segment AFTER the insertion start_feat=get_feature_start_on_target_genome_inv(start_feat_seg_target,feat,walk) pos_new=str(start_feat-end_var) else: start_var=segments_on_target_genome[start_var_seg][walk][-1][1]-len(variation.alt) # start_var_seg is the segment AFTER the insertion start_feat=get_feature_start_on_target_genome(start_feat_seg_target,feat,walk) pos_new=str(start_var-start_feat) return [pos_old,pos_new] # pos_old and pos_new are the base before the change # find the position of a deletion on the source and the target sequence def get_old_new_pos_deletion(variation,feat_start,start_feat_seg_target,feat,walk): i=variation.start_var_index seg_pos=search_segment(variation.start_var) if i==0: pos_old=int(Segments[seg_pos].start)-int(feat_start)+Features[feat].pos_start-1 else: pos_old=int(Segments[seg_pos].start)-int(feat_start) if pos_old<0: pos_old=0 print("error with variation position",variation.inversion,"***") if variation.last_seg_in_target=="": # deletion of the beggining of the feature, so no segment placed in the new genome yet. pos_new=0 else: start_var_seg=variation.last_seg_in_target if variation.inversion: start_feat_seg_target=invert_seg(start_feat_seg_target) start_var_seg=invert_seg(start_var_seg) start_var=segments_on_target_genome[start_var_seg][walk][-1][1]-1 start_feat=get_feature_start_on_target_genome_inv(start_feat_seg_target,feat,walk) pos_new=str(start_feat-start_var) else: start_var=segments_on_target_genome[start_var_seg][walk][-1][2]+1 start_feat=get_feature_start_on_target_genome(start_feat_seg_target,feat,walk) pos_new=str(start_var-start_feat) return [pos_old,pos_new] # pos_old and pos_new are the base before the change # change the variation information, but keep the feature information (the variation is on the feature) def init_new_var(variation,type,feature_path_source_genome,feature_path_target_genome,i,j,seg_seq,feature): variation.type=type variation.start_var=feature_path_source_genome[i] variation.start_var_index=i if type=="substitution": variation.start_on_target=feature_path_target_genome[j] variation.ref=get_segment_sequence(seg_seq,feature_path_source_genome[i]) variation.alt=get_segment_sequence(seg_seq,feature_path_target_genome[j]) variation.seg_ref.append(feature_path_source_genome[i]) variation.seg_alt.append(feature_path_target_genome[j]) elif type=="insertion": variation.ref="-" variation.alt=get_segment_sequence(seg_seq,feature_path_target_genome[j]) variation.seg_alt.append(feature_path_target_genome[j]) elif type=="deletion": if i==0: # if the deletion is at the start of the feature, the deletion doesnt always start at the start at the first segment : #use pos_start, position of the feature on its first segment variation.ref=get_segment_sequence(seg_seq,feature_path_source_genome[i])[feature.pos_start-1:] variation.seg_ref.append(feature_path_source_genome[i]) else: # else, the deletion will always start at the start of the first segment. variation.ref=get_segment_sequence(seg_seq,feature_path_source_genome[i]) variation.seg_ref.append(feature_path_source_genome[i]) variation.alt="-" # update the variation def continue_var(variation,seg_seq,feature_path_source_genome,feature_path_target_genome,i,j,genome_to_continue): if variation.type=="substitution": if genome_to_continue==0: # genome_to_continue allows to choose if the substitution continues for the original or the target genome, or both. variation.ref+=get_segment_sequence(seg_seq,feature_path_source_genome[i]) variation.alt+=get_segment_sequence(seg_seq,feature_path_target_genome[j]) variation.seg_ref.append(feature_path_source_genome[i]) variation.seg_alt.append(feature_path_target_genome[j]) elif genome_to_continue==1: # deletion variation.ref+=get_segment_sequence(seg_seq,feature_path_source_genome[i]) variation.seg_ref.append(feature_path_source_genome[i]) elif genome_to_continue==2: # insertion variation.alt+=get_segment_sequence(seg_seq,feature_path_target_genome[j]) variation.seg_alt.append(feature_path_target_genome[j]) elif variation.type=="insertion": variation.alt+=get_segment_sequence(seg_seq,feature_path_target_genome[j]) variation.seg_alt.append(feature_path_target_genome[j]) elif variation.type=="deletion": variation.ref+=get_segment_sequence(seg_seq,feature_path_source_genome[i]) variation.seg_ref.append(feature_path_source_genome[i]) # functions to detect inversions # gives the list of segments from dict1 that are in dict2 def get_common_segments(dict1,dict2): list_common=[] for segment in dict1: if segment in dict2: list_common.append(segment) return list_common # check if common segments in the two dict have the same strand def compare_strand(dict1,dict2): # dict1 and dict2 : [seg_id]->[seg_strand] seg_common=get_common_segments(dict1,dict2) # for each segment in common, check if the strand is the same same_strand_count=0 for segment in seg_common: if dict1[segment]==dict2[segment]: same_strand_count+=1 return [len(seg_common),same_strand_count] # check if the two dict have their segments in the inverted order def detect_segment_order_inversion(dict1,dict2): list_1_common=get_common_segments(dict1,dict2) list_2_common=get_common_segments(dict2,dict1) # same segments, different orders list_2_common_reversed=list(reversed(list_2_common)) [cpt,i]=[0,0] while i<len(list_1_common): if list_2_common_reversed[i]==list_1_common[i]: cpt+=1 i+=1 return (cpt>len(list_1_common)*0.9) # if more than 90% of the segments are on the same position when the lists are reversed, there is an inversion. # check if the two dict have the same segments but in different orientation def detect_orient_inversion(dict1,dict2): [seg_common_count,same_strand_count]=compare_strand(dict1,dict2) if same_strand_count>=seg_common_count*0.9: # if more than 90% of segments shared have the same strand, no inversion return [False,dict1,dict2] else: return [True,dict1,dict2] # takes two lists of segments for two genes, check if the first list is an inversion of the second one (if the segments in common are on the opposite strand) def detect_feature_inversion(list_1,list_2): # convert list into dict with unstranded segment id as key and strand as value strand1=[seg[0] for seg in list_1] id1=[seg[1:] for seg in list_1] dict1 = {id1[i]: strand1[i] for i in range(len(strand1))} strand2=[seg[0] for seg in list_2] id2=[seg[1:] for seg in list_2] dict2 = {id2[i]: strand2[i] for i in range(len(strand2))} # check if we have an inversion of the orientation of the segments [strand_inversion,dict1,dict2]=detect_orient_inversion(dict1,dict2) # check if we have an inversion of the order of the segments segment_order_inversion=detect_segment_order_inversion(dict1,dict2) # if there we have both inversions, the gene is in an inverted region if segment_order_inversion and strand_inversion: return True else : return False # invert all the segments in a list (change the orientation) def invert_segment_list(seg_list): list_inverted=list() for seg in seg_list: list_inverted.append(invert_seg(seg)) return list(reversed(list_inverted))