Functions.py

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))