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from Graph_gff import Segments, Features, get_feature_start_on_segment, get_feature_stop_on_segment, write_line
### functions to generate a genome's gff from the graph's gff
# get the start position of the features on the linear genome, using their coordinates on the graph and the coordinantes of the segments on the genome
def get_feature_start_on_genome(start_seg,feat_id):
seg_start_pos=segments_on_target_genome[start_seg][1]
feat_start_pos=get_feature_start_on_segment(start_seg,feat_id)
start=int(seg_start_pos)+int(feat_start_pos)-1
return start
# get the stop position of the features on the linear genome, using their coordinates on the graph and the coordinantes of the segments on the genome
def get_feature_stop_on_genome(stop_seg,feat_id):
seg_start_pos=segments_on_target_genome[stop_seg][1]
feat_stop_pos=get_feature_stop_on_segment(stop_seg,feat_id)
stop=int(seg_start_pos)+int(feat_stop_pos)-1
return stop
# functions to get the detailed gff with all the fragments of the features
# get the position of a part of a feature on the complete feature (on the original genome)
def get_position_on_feature(start_seg,stop_seg,feature_start_segment,feature):
start_on_feature=get_segment_start_on_feature(feature_start_segment,start_seg,feature)
stop_on_feature=get_segment_stop_on_feature(start_seg,stop_seg,feature,start_on_feature)
position=";position="+str(start_on_feature)+"-"+str(stop_on_feature)
#position=";start_position_on_feature="+str(start_on_gene)+":stop_position_on_feature="+str(stop_on_gene)
return position
def get_segment_start_on_feature(feature_start_segment,start_seg,feature):
feature_start_pos=Segments[feature_start_segment].start+get_feature_start_on_segment(feature_start_segment,feature.id)-1
start_on_reference=Segments[start_seg].start+get_feature_start_on_segment(start_seg,feature.id)-1
start_on_feature=int(start_on_reference)-int(feature_start_pos)+1
return start_on_feature
def get_segment_stop_on_feature(start_seg,stop_seg,feature,start_on_feature):
start_on_new_genome=get_feature_start_on_genome(start_seg,feature.id)
stop_on_new_genome=get_feature_stop_on_genome(stop_seg,feature.id)
# length on new genome is the same as length on reference, as we only get the positions of conserved parts of the feature
stop_on_feature=start_on_feature+(stop_on_new_genome-start_on_new_genome) # stop position : start+length
return stop_on_feature
# get the proportion of a part of the feature on the total length
def get_proportion_of_feature_part(start_seg,stop_seg,feature):
start_on_new_genome=get_feature_start_on_genome(start_seg,feature.id)
stop_on_new_genome=get_feature_stop_on_genome(stop_seg,feature.id)
# length on new genome is the same as length on reference, as we only get the positions of conserved parts of the feature
proportion=";proportion="+str(stop_on_new_genome-start_on_new_genome+1)+"/"+str(feature.size)
#proportion=";number_bases="+str(stop_new_genome-start_new_genome+1)+";total_bases="+str(feature.size)
return proportion
# 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_inversion(list_1,list_2):
# removes strand for the lists of stranded segments
list_1_unstrand=[segment_stranded[1:] for segment_stranded in list_1]
list_2_unstrand=[segment_stranded[1:] for segment_stranded in list_2]
[seg_common,same_strand_count]=compare_strand(list_1,list_2,list_1_unstrand,list_2_unstrand)
# if there is less than 10% of strand difference among the common segments (ie more than 90% of same strand), return False, no inversion
if len(seg_common)-same_strand_count<len(seg_common)/10:
return [list_1_unstrand,list_2_unstrand,0]
else:
return [list_1_unstrand,list_2_unstrand,1]
def compare_strand(list_1,list_2,list_1_unstrand,list_2_unstrand):
# get the list of segments in common
seg_common=[]
for segment in list_1_unstrand:
if segment in list_2_unstrand:
seg_common.append(segment)
# for each segment in common, check if the strand is the same. check index in list unstranded to get the segment in list stranded
same_strand_count=0
for segment in seg_common:
index_1=list_1_unstrand.index(segment)
index_2=list_2_unstrand.index(segment)
if list_1[index_1]==list_2[index_2]:
same_strand_count+=1
return [seg_common,same_strand_count]
# returns the gff line to write in the output file for the function gff_detail
def create_line_detail(last_seg,feature_id,start_seg,feat_start):
[stop_seg,feature,chr,strand]=[last_seg[1:],Features[feature_id],segments_on_target_genome[start_seg][0],last_seg[0:1]]
# start and stop position of the feature on the genome we transfer on
start_on_new_genome=get_feature_start_on_genome(start_seg,feature_id)
stop_on_new_genome=get_feature_stop_on_genome(stop_seg,feature_id)
proportion=get_proportion_of_feature_part(start_seg,stop_seg,feature)
position=get_position_on_feature(start_seg,stop_seg,feat_start,feature)
annotation=feature.annot+proportion+position
output_line=chr+"\tGrAnnot\t"+feature.type+"\t"+str(start_on_new_genome)+"\t"+str(stop_on_new_genome)+"\t.\t"+strand+"\t.\t"+annotation+"\n"
return output_line
# outputs each fragment of the feature in a gff
def gff_detail(list_seg,feature_id):
# loop that goes through all the segments that have the current feature
# keeps the first segment present in the genome found, and when it finds a segment absent in the genome, prints the current part of the fragment, and resets the first segment present.
# continues to go through the segments, keeps the next segment present in the genome, and when it finds a segment absent, prints the second part of the feature, etc.
# at the end of the loop, prints the last part of the fragment.
[feat_start,seg_start,last_seg]=["","",""] # first segment of the feature, first segment of the current part of the feature, last segment in the for loop below
for segment in list_seg:
if segment[1:] in segments_on_target_genome:
if feat_start=="":
feat_start=segment[1:]
if seg_start=="": # if we dont have a start, take the current segment for the start of the part of the feature
seg_start=segment[1:]
#else: if we already have a start, keep going though the segments until we find a stop (segment not in azucena)
else:
if seg_start!="": # found a stop and we have a start. print the line, reset seg_start, and keep going through the segments to find the next seg_start
out_line=create_line_detail(last_seg,feature_id,seg_start,feat_start)
write_line(out_line,output_detail_gff,False)
seg_start=""
#else: if the current segment is not in azucena but there is no start, keep looking for a start
last_seg=segment
if last_seg[1:] in segments_on_target_genome:
out_line=create_line_detail(list_seg[-1],feature_id,seg_start,feat_start)
write_line(out_line,output_detail_gff,False)
# functions to get the gff with one line per feature
def right_size(size,max_diff,feat):
if max_diff==0:
return True
return not ((size>Features[feat].size*max_diff) | (size<Features[feat].size/max_diff))
def create_line_gff_one(first_seg,last_seg,feature_id,size_diff,list_seg):
[chr,strand,feature]=[segments_on_target_genome[first_seg][0],list_seg[0][0:1],Features[feature_id]]
variant_count=0
for segment in list_seg:
if segment[1:] not in segments_on_target_genome: # if a segment is absent, it is either a deletion of a substitution. insertions are not considered here.
variant_count+=1
annotation=feature.annot+";Size_diff="+str(size_diff)+";Nb_variants="+str(variant_count)
line=chr+" GrAnnot "+feature.type+" "+str(get_feature_start_on_genome(first_seg,feature_id))+" "+str(get_feature_stop_on_genome(last_seg,feature_id))+" . "+strand+" . "+annotation+"\n"
return line
# outputs the feature once in a gff, from the first to the last segment present on the new genome (if the size is ok) :
def gff_one(first_seg,last_seg,feature_id,list_seg,max_diff):
if (first_seg!=''): # feature present on the target genome
size_on_new_genome=get_feature_stop_on_genome(last_seg,feature_id)-get_feature_start_on_genome(first_seg,feature_id)+1
size_diff=abs(size_on_new_genome-Features[feature_id].size)
if right_size(size_on_new_genome,max_diff,feature_id):
line=create_line_gff_one(first_seg,last_seg,feature_id,size_diff,list_seg)
write_line(line,output_gff_one,False)
return size_diff
else:
return "bad_size"
else :
return "absent"
# functions to get the detail of the variations in the features
def print_variations(first_seg,last_seg,feat,paths,seg_seq):
if (first_seg!=''): # if the feature is not completly absent
var=0 # count variations, to see if there is any
feature=Features[feat]
feat_start=feature.start
# get the lengths of the feature, on the original genome and on the new one
start_new_genome=get_feature_start_on_genome(first_seg,feat)
stop_new_genome=get_feature_stop_on_genome(last_seg,feat)
size_new_genome=int(stop_new_genome)-int(start_new_genome)+1
size_diff=str(size_new_genome-feature.size)
# get feature paths on the original genome and on the target genome
list_segfeat_azu=get_feature_path(paths,first_seg,last_seg)
list_segfeat_nb=feature.segments_list
# loop to go through both paths
i=0
j=0
[last,last_taille,last_seq,last_start,last_in_azu]=['',0,'','','']
# check if there is an inversion and remove strands
[list_segfeat_nb,list_segfeat_azu,inversion]=detect_inversion(list_segfeat_nb,list_segfeat_azu)
# detect and print variations ignoring the strands
while (i<len(list_segfeat_nb)) & (j<len(list_segfeat_azu)):
if list_segfeat_nb[i] != list_segfeat_azu[j]: # if there is a difference between the two paths
if list_segfeat_azu[j] not in list_segfeat_nb: # if the segment in azu is absent in nb
if list_segfeat_nb[i] not in list_segfeat_azu: # if the segment in nb is absent is azu
# is both segments are absent in the other genome, its a substitution
last_in_azu=list_segfeat_azu[j]
# print if we had an insertion or deletion running
if last=='insertion':
[pos_old,pos_new]=get_old_new_pos_insertion(last_start,feat_start,list_segfeat_azu,feat)
line=feat+"\t"+feature.type+"\t"+feature.chr+"\t"+str(start_new_genome)+"\t"+str(stop_new_genome)+"\t"+str(size_new_genome)+"\t"+str(inversion)+"\t"+size_diff+"\tinsertion\t-\t"+last_seq+"\t"+str(len(last_seq))+"\t"+str(pos_old)+"\t"+pos_new+"\n"
write_line(line,output_variations,False)
var+=1
elif last=='deletion':
[pos_old,pos_new]=get_old_new_pos_deletion(last_start,feat_start,list_segfeat_azu,feat,last_in_azu,i)
line=feat+"\t"+feature.type+"\t"+feature.chr+"\t"+str(start_new_genome)+"\t"+str(stop_new_genome)+"\t"+str(size_new_genome)+"\t"+str(inversion)+"\t"+size_diff+"\tdeletion\t"+last_seq+"\t-\t"+str(len(last_seq))+"\t"+str(pos_old)+"\t"+pos_new+"\n"
write_line(line,output_variations,False)
var+=1
last='';last_taille=0;last_seq='';last_start=''
# print the substitution
# substitution of segment list_segfeat_nb[i][1:] by segment list_segfeat_azu[j][1:]
[pos_old,pos_new]=get_old_new_pos_substitution(feat_start,list_segfeat_nb,list_segfeat_azu,feat,i,j)
if len(seg_seq[list_segfeat_nb[i]]) == len(seg_seq[list_segfeat_azu[j]]): # if the substituion is between two segment of the same size, print it
size_subs=len(seg_seq[list_segfeat_nb[i]])
line=feat+"\t"+feature.type+"\t"+feature.chr+"\t"+str(start_new_genome)+"\t"+str(stop_new_genome)+"\t"+str(size_new_genome)+"\t"+str(inversion)+"\t"+size_diff+"\tsubstitution\t"+seg_seq[list_segfeat_nb[i]]+"\t"+seg_seq[list_segfeat_azu[j]]+"\t"+str(size_subs)+"\t"+str(pos_old)+"\t"+pos_new+"\n"
else :
# if the segments of the substitution have a different size, print deletion then insertion at the same position.
line=feat+"\t"+feature.type+"\t"+feature.chr+"\t"+str(start_new_genome)+"\t"+str(stop_new_genome)+"\t"+str(size_new_genome)+"\t"+str(inversion)+"\t"+size_diff+"\tdeletion\t"+seg_seq[list_segfeat_nb[i]]+"\t-\t"+str(len(seg_seq[list_segfeat_nb[i]]))+"\t"+str(pos_old)+"\t"+pos_new+"\n"
line+=feat+"\t"+feature.type+"\t"+feature.chr+"\t"+str(start_new_genome)+"\t"+str(stop_new_genome)+"\t"+str(size_new_genome)+"\t"+str(inversion)+"\t"+size_diff+"\tinsertion\t-\t"+seg_seq[list_segfeat_azu[j]]+"\t"+str(len(seg_seq[list_segfeat_azu[j]]))+"\t"+str(pos_old)+"\t"+pos_new+"\n"
var+=1
write_line(line,output_variations,False)
var+=1;i+=1;j+=1
else: # azu segment not in nb, but nb segment in azu : insertion
if last=='deletion':
[pos_old,pos_new]=get_old_new_pos_deletion(last_start,feat_start,list_segfeat_azu,feat,last_in_azu,i)
line=feat+"\t"+feature.type+"\t"+feature.chr+"\t"+str(start_new_genome)+"\t"+str(stop_new_genome)+"\t"+str(size_new_genome)+"\t"+str(inversion)+"\t"+size_diff+"\tdeletion\t"+last_seq+"\t-\t"+str(len(last_seq))+"\t"+str(pos_old)+"\t"+pos_new+"\n"
write_line(line,output_variations,False)
var+=1;last='';last_taille=0;last_start='';last_seq=''
last_in_azu=list_segfeat_azu[j]
if last=='insertion':
last_seq=last_seq+seg_seq[list_segfeat_azu[j]]
else:
last='insertion'
last_seq=seg_seq[list_segfeat_azu[j]]
last_start=list_segfeat_nb[i]
j+=1
elif list_segfeat_nb[i] not in list_segfeat_azu: # nb segment not in azu, but azu segment in nb : deletion
if last=='insertion':
[pos_old,pos_new]=get_old_new_pos_insertion(last_start,feat_start,list_segfeat_azu,feat)
line=feat+"\t"+feature.type+"\t"+feature.chr+"\t"+str(start_new_genome)+"\t"+str(stop_new_genome)+"\t"+str(size_new_genome)+"\t"+str(inversion)+"\t"+size_diff+"\tinsertion\t-\t"+last_seq+"\t"+str(len(last_seq))+"\t"+str(pos_old)+"\t"+pos_new+"\n"
write_line(line,output_variations,False)
var+=1;last='';last_start='';last_taille=0;last_seq=''
if last=='deletion':
last_seq=last_seq+seg_seq[list_segfeat_nb[i]]
else:
last='deletion'
last_start=list_segfeat_nb[i]
if i==0: # if the deletion is at the start of the feature, the deletion doesnt start at the start at the first segment :
#use pos_start, position of the feature on its first segment
last_seq=seg_seq[list_segfeat_nb[i]][feature.pos_start-1:]
else: # else, the deletion will always start at the start of the first segment.
last_seq=seg_seq[list_segfeat_nb[i]]
i+=1
else : # idk yet. if both segments are present in the other genome but not at the same position. probably substitution then
line="weird order change"
write_line(line,output_variations,False)
var+=1;i+=1;j+=1
else: # segment present in both. print the running indel if there is one
if last=='insertion':
[pos_old,pos_new]=get_old_new_pos_insertion(last_start,feat_start,list_segfeat_azu,feat)
line=feat+"\t"+feature.type+"\t"+feature.chr+"\t"+str(start_new_genome)+"\t"+str(stop_new_genome)+"\t"+str(size_new_genome)+"\t"+str(inversion)+"\t"+size_diff+"\tinsertion\t-\t"+last_seq+"\t"+str(len(last_seq))+"\t"+str(pos_old)+"\t"+pos_new+"\n"
write_line(line,output_variations,False)
var+=1
elif last=='deletion':
[pos_old,pos_new]=get_old_new_pos_deletion(last_start,feat_start,list_segfeat_azu,feat,last_in_azu,i)
line=feat+"\t"+feature.type+"\t"+feature.chr+"\t"+str(start_new_genome)+"\t"+str(stop_new_genome)+"\t"+str(size_new_genome)+"\t"+str(inversion)+"\t"+size_diff+"\tdeletion\t"+last_seq+"\t-\t"+str(len(last_seq))+"\t"+str(pos_old)+"\t"+pos_new+"\n"
write_line(line,output_variations,False)
var+=1
last_in_azu=list_segfeat_azu[j]
last='';last_taille=0;last_start='';last_seq='';i+=1;j+=1
# finish printing the current indel
if last=='insertion':
[pos_old,pos_new]=get_old_new_pos_insertion(last_start,feat_start,list_segfeat_azu,feat)
line=feat+"\t"+feature.type+"\t"+feature.chr+"\t"+str(start_new_genome)+"\t"+str(stop_new_genome)+"\t"+str(size_new_genome)+"\t"+str(inversion)+"\t"+size_diff+"\tinsertion\t-\t"+last_seq+"\t"+str(last_taille)+"\t"+str(pos_old)+"\t"+pos_new+"\n"
write_line(line,output_variations,False)
var+=1
elif last=='deletion':
[pos_old,pos_new]=get_old_new_pos_deletion(last_start,feat_start,list_segfeat_azu,feat,last_in_azu,i)
line=feat+"\t"+feature.type+"\t"+feature.chr+"\t"+str(start_new_genome)+"\t"+str(stop_new_genome)+"\t"+str(size_new_genome)+"\t"+str(inversion)+"\t"+size_diff+"\tdeletion\t"+last_seq+"\t-\t"+str(len(last_seq))+"\t"+str(pos_old)+"\t"+pos_new+"\n"
write_line(line,output_variations,False)
var+=1
# see if the end is missing for one of the two genomes
if not((i>=len(list_segfeat_nb)-1) & (j>=len(list_segfeat_azu)-1)):
pos_old=int(Segments[list_segfeat_nb[i]].start)-int(feat_start)+1
del_sequence=get_sequence_list_seg(list_segfeat_nb,i,feature,seg_seq)
length=len(del_sequence)
pos_new=str(size_new_genome+1) # the deletion is at the end of the feature on the new genome
line=feat+"\t"+feature.type+"\t"+feature.chr+"\t"+str(start_new_genome)+"\t"+str(stop_new_genome)+"\t"+str(size_new_genome)+"\t"+str(inversion)+"\t"+size_diff+"\tdeletion\t"+del_sequence+"\t-\t"+str(length)+"\t"+str(pos_old)+"\t"+pos_new+"\n"
write_line(line,output_variations,False)
var+=1
if var==0:
line=feat+"\t"+feature.type+"\t"+feature.chr+"\t"+str(start_new_genome)+"\t"+str(size_new_genome)+"\t"+size_diff+"\tno_var\t-\t-\t-\t-\t-\n"
write_line(line,output_variations,False)
def get_feature_path(paths,first_seg,last_seg):
# find the path in azucena.
first_strand=segments_on_target_genome[first_seg][3]
first_seg_stranded=first_strand+first_seg
last_strand=segments_on_target_genome[last_seg][3]
last_seg_stranded=last_strand+last_seg
id_first_seg=int(paths["CM020642.1_Azucena_chromosome10"].index(first_seg_stranded))
id_last_seg=int(paths["CM020642.1_Azucena_chromosome10"].index(last_seg_stranded))
first_index=min(id_first_seg,id_last_seg)
last_index=max(id_last_seg,id_first_seg)
list_segfeat_azu=paths["CM020642.1_Azucena_chromosome10"][first_index:last_index+1]
return list_segfeat_azu
def get_sequence_list_seg(list_segfeat_nb,i,feature,seg_seq):
del_sequence=""
for k in range(i,len(list_segfeat_nb)):
if k==len(list_segfeat_nb):
del_sequence+=seg_seq[list_segfeat_nb[k]][0:feature.pos_stop]
del_sequence+=seg_seq[list_segfeat_nb[k]]
return del_sequence
def get_old_new_pos_substitution(feat_start,list_segfeat_nb,list_segfeat_azu,feat,i,j):
pos_old=int(Segments[list_segfeat_nb[i]].start)-int(feat_start)+1
start_feat=get_feature_start_on_genome(list_segfeat_azu[0],feat)
start_var=int(segments_on_target_genome[list_segfeat_azu[j-1]][2])+1
pos_new=str(start_var-start_feat+1)
return [pos_old,pos_new]
def get_old_new_pos_insertion(last_start,feat_start,list_segfeat_azu,feat):
pos_old=str(int(Segments[last_start].start)-int(feat_start)+1)
start_feat=get_feature_start_on_genome(list_segfeat_azu[0],feat)
start_var=int(segments_on_target_genome[last_start][1])-1
pos_new=str(start_var-start_feat+1)
return [pos_old,pos_new]
def get_old_new_pos_deletion(last_start,feat_start,list_segfeat_azu,feat,last_in_azu,i):
if i==0:
pos_old=int(Segments[last_start].start)-int(feat_start)+1+Features[feat].pos_start
else:
pos_old=int(Segments[last_start].start)-int(feat_start)+1
if pos_old<0:
pos_old=0
if last_in_azu=="": # deletion of the beggining of the feature, so no segment placed in the new genome yet.
pos_new="1"
else:
start_feat=get_feature_start_on_genome(list_segfeat_azu[0],feat)
start_var=int(segments_on_target_genome[last_in_azu][2])+1
pos_new=str(start_var-start_feat+1)
return [pos_old,pos_new]
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# functions to output the stats on the transfer
def stats_feature_missing_segment(feature_missing_segments,first_seg,last_seg,list_seg,feature_id):
# [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][1:]: # the first segment is missing
feature_missing_segments[0].append(feature_id)
elif last_seg!=list_seg[-1][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) & (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[1:] not in segments_on_target_genome:
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[1:] not in segments_on_target_genome:
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) | ("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.")
def get_segments_positions_on_genome(pos_seg):
global segments_on_target_genome
segments_on_target_genome={}
bed=open(pos_seg,'r')
lines=bed.readlines() # read line by line ?
bed.close()
for line in lines:
line=line.split()
[seg,chrom,start,stop]=[line[3][1:],line[0],line[1],line[2]]
if line[3][0:1]=='>':
strand='+'
elif line[3][0:1]=='<':
strand='-'
else:
strand=''
segments_on_target_genome[seg]=[chrom,start,stop,strand]
def get_segments_sequence_and_paths(gfa):
file_gfa=open(gfa,'r')
lines_gfa=file_gfa.readlines()
file_gfa.close()
seg_seq={}
paths={}
for line in lines_gfa:
line=line.split()
if (line[0]=="S"): # get the sequence of the segment
seg_id='s'+line[1]
seg_seq[seg_id]=line[2]
if (line[0]=="W") & (line[1]!="_MINIGRAPH_"): # get the walk of the genome
path=line[6].replace(">",";>")
path=path.replace("<",";<").split(';')
list_path=[]
for segment in path:
if segment[0:1]=='>':
list_path.append('+s'+segment[1:])
elif segment[0:1]=='<':
list_path.append('-s'+segment[1:])
else:
list_path.append('s'+segment[1:])
paths[line[3]]=list_path
return [paths,seg_seq]
def get_first_seg(list_seg):
first_seg_found=''
for segment in list_seg:
if segment[1:] in segments_on_target_genome:
first_seg_found=segment[1:]
break
return first_seg_found
def get_all_features_in_gff(gff):
gff=open(gff,'r')
lines=gff.readlines()
gff.close()
list_feature=[]
for line in lines:
feature_id=(line.split()[8].split(";")[0].split("=")[1].replace(".","_").replace(":","_"))
if feature_id not in list_feature:
list_feature.append(feature_id)
return list_feature
# writes the gff of azucena using the gff of the graph
def genome_gff(pos_seg, gff, out, gfa):
print("generation of the genome's gff ")
[once,detail,var,stats]=[True,False,True,True]
if var:
[paths,seg_seq]=get_segments_sequence_and_paths(gfa)
file_out_var = open("variations.txt", 'w')
global output_variations
output_variations=[0,"",file_out_var]
if detail:
file_out_detail = open("azucena_chr10_detail.gff", 'w')
global output_detail_gff
output_detail_gff=[0,"",file_out_detail]
if once:
file_out=open(out,'w')
global output_gff_one
output_gff_one=[0,"",file_out]
bad_size_features=0
absent_features=0
diff_size_transfered_features=[0,0] # [count,sum], to get the average
get_segments_positions_on_genome(pos_seg)
list_feature_to_transfer=get_all_features_in_gff(gff) # get the list of all the features to transfer from the gff
# create objects for stats on how many segments are absent in azucena, their average length, etc
if stats==True:
feature_missing_segments=[[],[],[],[],[],[],[]] # [feature_missing_first,feature_missing_middle,feature_missing_last,feature_missing_all,feature_missing_total,feature_total,feature_ok]
# the fist segment of the feature is missing - feature_missing_first
# the last segment of the feature is missing - feature_missing_last
# at least one middle segment of the feature is missing - feature_missing_middle
# the entire feature is missing - feature_missing_all
# at least one segment is missing first, last, or middle) - feature_missing_total
# no segment is missing, the feature is complete - feature_ok
# total number of features, with missing segments or not - feature_total
for feat in list_feature_to_transfer:
# for each feature, get list of the segments where it is and the first and last segment of the feature on the new genome
list_seg=Features[feat].segments_list
first_seg=get_first_seg(list_seg)
last_seg=get_first_seg(reversed(list_seg))
if stats==True:
stats_feature_missing_segment(feature_missing_segments,first_seg,last_seg,list_seg,feat)
# outputs the feature once in a gff, from the first to the last segment present on the new genome
if once:
max_diff=2 # maximum difference size (n times bigger of smaller)
add=gff_one(first_seg,last_seg,feat,list_seg,max_diff)
if add=="bad_size":
bad_size_features+=1
elif add=="absent":
absent_features+=1
else:
diff_size_transfered_features[0]+=1
diff_size_transfered_features[1]+=add
write_line("",output_gff_one,True)
# outputs each fragment of the feature in a gff
if detail:
gff_detail(list_seg,feat) # insertions !
write_line("",output_detail_gff,True)
# outputs the detail of variations of the feature :
if var:
print_variations(first_seg,last_seg,feat,paths,seg_seq)
write_line("",output_variations,True)
if detail:
file_out_detail.close()
if once:
file_out.close()
if var:
file_out_var.close()
# print stats
from statistics import median, mean
if stats==True:
if once:
print(len(Features)-(bad_size_features+absent_features),"out of",len(Features),"features are transfered.")
print(bad_size_features,"out of",len(Features), "features are not transfered because they are too big or too small compared to the original genome.")
print(absent_features,"out of",len(Features),"features are not transfered because they are absent in the new genome.")
print("average length difference of the transfered genes : ",diff_size_transfered_features[1]/diff_size_transfered_features[0])
stats_features(feature_missing_segments)
# not used.
def get_list_segments_missing(list_seg,segments_on_target_genome):
segments_missing=[]
for segment in list_seg:
if segment[1:] not in segments_on_target_genome:
segments_missing.append(Segments[segment[1:]])
return segments_missing
# takes a feature and a feature type, returns a list of child features that have the wanted type. currently not used.
def get_child_list(feature,child_type):
if type=="":
return feature.childs
list_childs=[]
for child in feature.childs:
if Features[child].type==child_type:
list_childs.append(child)
return list_childs