diff --git a/ClassSegFeat.py b/ClassSegFeat.py
index 92ac81f15995bb7eb6b43ff033be2570bc020a64..5486a938b056d1c8527a50b9a999a3e0da641c28 100644
--- a/ClassSegFeat.py
+++ b/ClassSegFeat.py
@@ -7,6 +7,10 @@ class Segment:
self.chr=chr
self.start=int(start)
self.stop=int(stop)
+
+ # segments précedent et suivant.
+ # séquence.
+ #Â cf odgi objets
self.size=self.stop-self.start+1
@@ -30,6 +34,8 @@ class Feature:
self.childs=childs # liste of childs features (exons, cds, etc)
self.parent=parent
self.segments_list=seg #Â list of oriented segment on which the feature is (-s1/+s1, depending on the strand)
+
+ self.note=""
def __str__(self):
if self.parent=="":
diff --git a/Functions.py b/Functions.py
index 43f4236324d46bf0ee0f3a3deda48d34000d8676..6e7b434067bb3b6b1b600871de2651b36a9ff4e7 100644
--- a/Functions.py
+++ b/Functions.py
@@ -1,4 +1,5 @@
import ClassSegFeat as Class
+import subprocess
# functions to create the segments and the features
@@ -73,6 +74,21 @@ def add_seg(feat,new_seg,strand):
Features[feat].segments_list.append(seg_stranded)
+def set_note(id):
+ feat=Features[id]
+ if feat.type=="gene":
+ feat.note=feat.annot.split(';')[-1]
+ else:
+ curent=feat.parent
+ ann=0
+ while ann==0:
+ if Features[curent].type=="gene":
+ fonction=Features[curent].annot.split(';')[-1]
+ feat.note=fonction
+ ann=1
+ else:
+ curent=Features[Features[curent].parent].id
+
# create all the Segment and Feature objects in the dictionnaries Segments and Features
def create_seg_feat(intersect_path):
@@ -92,6 +108,7 @@ def create_seg_feat(intersect_path):
if feature_id not in Features: # if the feature doesn't exist, create it and add the current segment to its seg list
init_feature(line)
+ #set_function(feature_id)
else: # add the current segment to the list of segments that have the existing feature
strand=line.split()[10]
add_seg(feature_id,segment_id,strand)
@@ -103,6 +120,9 @@ def create_seg_feat(intersect_path):
strand=line.split()[10]
add_feature(segment_id,feature_id,strand)
+ for feat_id in Features:
+ set_note(feat_id)
+
file.close()
@@ -253,8 +273,14 @@ def genome_gff(pos_seg, gff, out):
gff=open(gff,'r')
file_out = open(out, 'w')
-
+ file_out_alt=open("azucena_chr10_alt.gff",'w')
+ file_out2 = open("segments_manquants.txt", 'w')
+
lines=gff.readlines()
+
+ diff_list=list()
+
+ stats=True
# get the list of all the features to transfer
list_feature=list()
@@ -264,61 +290,135 @@ def genome_gff(pos_seg, gff, out):
list_feature.append(id)
# stats on how many segments are absent in azucena, their average length, etc
- stats=False
if stats==True:
seg_first=list()
seg_middle=list()
seg_last=list()
- seg_total=list()
+ seg_total_abs=list()
seg_ok=list()
seg_entier=list()
+ seg_total=list()
+
feature_missing_first=list()
feature_missing_middle=list()
feature_missing_last=list()
feature_missing_all=list()
feature_missing_total=list()
+ feature_total=list()
+ feature_ok=list()
+
+ #size_seg_missing=list()
+
+
+
+
- #Â for each feature, get list of the segments where it is
+ #Â for each feature, get list of the segments where it is and the first and last segment of the feature on the genome
for feat in list_feature:
list_seg=Features[feat].segments_list
size_list=len(list_seg)
+
+ segments_missing=list()
+
+ first_seg="0"
+ for segment in list_seg:
+ if segment[1:] in seg_ac:
+ first_seg=segment[1:]
+ break
+ last_seg="0"
+ for segment in reversed(list_seg):
+ if segment[1:] in seg_ac:
+ last_seg=segment[1:]
+ break
+
# stats on how many segments are absent in azucena, their average length, etc
- if stats==True:
+
+ #Â for the segments
+ # manque au début-seg_first
+ # manque à la fin-seg_last
+ # manque au milieu-seg_middle
+ # début milieu et fin, donc feature entier ?-seg_entier
+ # nb total de segments dans un gène et pas chez azucena-seg_total_abs
+ # présents chez azucena-seg_ok
+ # segments total dans une feature (présent ou pas dans azucena)-seg_total
+
+ if (stats==True):
+
for segment in list_seg:
seg_len=Segments[segment[1:]].size
if segment[1:] not in seg_ac:
seg_total.append(seg_len)
- if feat not in feature_missing_total:
- feature_missing_total.append(feat)
+ segments_missing.append(Segments[segment[1:]])
+ #if feat not in feature_missing_total:
+ # feature_missing_total.append(feat)
if segment==list_seg[0]:
- if segment==list_seg[size_list-1]:
- seg_entier.append(seg_len)
- if feat not in feature_missing_all:
- feature_missing_all.append(feat)
+ if segment==list_seg[-1]:
+ seg_entier.append(seg_len) # contient les features en un seul segment, absent chez azu.
+ # if feat not in feature_missing_all:
+ # feature_missing_all.append(feat)
else:
seg_first.append(seg_len)
- if feat not in feature_missing_first:
- feature_missing_first.append(feat)
- elif segment==list_seg[size_list-1]:
+ # if feat not in feature_missing_first:
+ # feature_missing_first.append(feat)
+ elif segment==list_seg[-1]:
seg_last.append(seg_len)
- if feat not in feature_missing_last:
- feature_missing_last.append(feat)
+ # if feat not in feature_missing_last:
+ # feature_missing_last.append(feat)
else:
seg_middle.append(seg_len)
- if feat not in feature_missing_middle:
- feature_missing_middle.append(feat)
+ #if feat not in feature_missing_middle:
+ # feature_missing_middle.append(feat)
else:
seg_ok.append(seg_len)
-
- gene_start="empty"
- seg_start="empty"
- seg_stop="empty"
-
+
+ #Â for the features :
+ # manque le premier->feature_missing_first
+ #Â manque le dernier->feature_missing_last
+ # trou au milieu->feature_missing_middle
+ # absent totalement (0) ->feature_missing_all
+ # au moins un segment qui manque->feature_missing_total
+ # features completes chez azucena->feature_ok
+ # nb features total->feature_total
+
+ if (stats==True):
+ feature_total.append(feat)
+ # premier dernier ou aucun seg présent :
+ if (first_seg=='0') & (last_seg=='0') : # aucun des segments de la feature n'est dans azucena.
+ feature_missing_all.append(feat)
+ elif first_seg != list_seg[0][1:]: # le premier segment est manquant chez azucena
+ feature_missing_first.append(feat)
+ elif last_seg!=list_seg[-1][1:]: # le dernier segment est manquant chez azucena
+ feature_missing_last.append(feat)
+
+ # parcourir les segments, voir s'ils manquent au milieu
+ elif (len(list_seg)!=1) & (feat not in feature_missing_all): # pour pouvoir accéder à l'avant dernier élément
+ for segment in list_seg[1-(len(list_seg)-2)]:
+ if segment not in seg_ac:
+ feature_missing_middle.append(feat)
+ break
+
+
+ # parcourir les segments, voir s'il en manque un n'importe où
+ for segment in list_seg:
+ if segment[1:] not in seg_ac:
+ if feat not in feature_missing_total:
+ feature_missing_total.append(feat)
+ break
+
+ if feat not in feature_missing_total:
+ feature_ok.append(feat)
+
+
+ # outputs each fragment of each feature, with its position on the new genome and its annotation :
# loop that goes through all the segments that have the current feature
# keeps the first segment present in azucena found, and when it finds a segment absent in azucena, prints the piece of the fragment, and resets the first segment present.
# at the end of the loop, prints the last piece of the fragment.
+ gene_start="empty"
+ seg_start="empty"
+ seg_stop="empty"
+
for i in range(0,size_list):
if list_seg[i][1:] in seg_ac:
if gene_start=="empty":
@@ -344,35 +444,91 @@ def genome_gff(pos_seg, gff, out):
if list_seg[i][1:] in seg_ac:
out_line=write_line(list_seg,i+1,feat,seg_start,gene_start,seg_ac)
file_out.write(out_line)
+
+
+ # outputs each feature once, from the first to the last segment present on the new genome and its annotation :
+ if (first_seg!='0') & (last_seg!='0'):
+ chr=seg_ac[first_seg][0]
+ strand=list_seg[i-1][0:1]
+ ligne=chr+" graph_gff "+Features[feat].type+" "+str(get_start_2(first_seg,seg_ac,feat))+" "+str(get_stop_2(last_seg,seg_ac,feat))+" . "+strand+" . "+Features[feat].annot+"\n"
+ file_out_alt.write(ligne)
+
+
+ # outputs the detail of the missing fragments for each feature :
+
+ for segment in list_seg:
+ if segment[1:] not in seg_ac:
+ segments_missing.append(Segments[segment[1:]])
+
+ if (len(segments_missing)!=0) & (first_seg!='0') & (last_seg!='0'):
+
+ #print(first_seg,last_seg)
+ start2=get_start_2(first_seg,seg_ac,feat)
+ stop2=get_stop_2(last_seg,seg_ac,feat)
+ size_on_genome=int(stop2)-int(start2)+1
+ size_diff=size_on_genome-Features[feat].size
+ diff_list.append(int(size_diff))
+
+ ligne=feat+" : "+str(len(segments_missing))+" variations. différence de taille (taille dans le nouveau génome-taille dans nipponbare) : "+str(size_diff)+"\n"
+ #taille du gene à l'origine : "+str(Features[feat].size)+", taille du gene sur ce génome : "+str(size_on_genome)+"\n"
+ file_out2.write(ligne)
+
+ for segment in segments_missing:
+ if (segment.id==Features[feat].segments_list[0][1:]) & (segment.id!=Features[feat].segments_list[-1][1:]):#premier et pas dernier
+ ligne="premier segment du gène manquant.\n"
+ elif (segment.id==Features[feat].segments_list[-1][1:]) & ((segment.id!=Features[feat].segments_list[0][1:])):#dernier et pas premier
+ ligne="dernier segment du gène manquant.\n"
+ elif (segment.id!=Features[feat].segments_list[0][1:]) & (segment.id!=Features[feat].segments_list[-1][1:]):#ni premier ni dernier
+ ligne="variation au milieu du gène, de taille "+str(segment.size)+"\n"
+ # voir si c'est substitution ou indel
+ # print ce qu'il y a en face dans nb
+
+ #size_seg_missing.append(segment.size)
+
+
+
+ file_out2.write(ligne)
+ file_out2.write("\n")
+ else:
+ ligne=feat+": aucune variation.\n\n"
+ file_out2.write(ligne)
+
+
+
+
+ #print("difference moyenne : "+str(sum(diff_list)/len(diff_list)))
+ #import matplotlib.pyplot as plt
+ #plt.hist(diff_list, range=(-1000,1000))
+ #plt.show()
+ #print("segment au millieu taille moyenne : "+str(sum(size_seg_missing)/len(size_seg_missing)))
+
file_out.close()
gff.close()
+ file_out2.close()
+ file_out_alt.close()
+
# print stats
from statistics import median, mean
if stats==True:
- print(len(seg_first),"segments missing at the beginning of a feature, of mean length", round(mean(seg_first),2), "and median length",median(seg_first))
- print(len(seg_middle),"segments missing in the middle of a feature, of mean length", round(mean(seg_middle),2), "and median length",median(seg_middle))
- multiple_3=0
- for seg in seg_middle:
- if seg%3==0:multiple_3+=1
- print(multiple_3,"segments missing in the middle of a feature, of length=3k")
- print(len(seg_last), "segments missing at the end of a feature, of mean length", round(mean(seg_last),2), "and median length",median(seg_last))
- print(len(seg_entier),"segments that have an entiere feature (not in beggining/middle/end) missing, of mean length", round(mean(seg_entier),2), "and median length",median(seg_entier))
- print(len(seg_total),"segments that have a feature piece missing, of mean length", round(mean(seg_total),2), "and median length",median(seg_total))
- print(len(seg_ok),"segments that have a feature found, of mean length", round(mean(seg_ok),2), "and median length", median(seg_ok))
-
- print("\nthe first segment is missing for", len(feature_missing_first) ,"features, including",round(100*(117+5)/153,2),"% hypothetical or putative.")
- print("a middle segment is missing for", len(feature_missing_middle) ,"features, including",round(100*(180+3)/263,2),"% hypothetical or putative.")
- print("the last segment is missing for", len(feature_missing_last) ,"features, including",round(100*(115+7)/156,2),"% hypothetical or putative.")
- print(len(feature_missing_all) ,"features are entirely missing, including",round(100*(314+24)/404,2),"% hypothetical or putative.")
- print("there is at least one segment missing", len(feature_missing_total) ,"features, including",round(100*(606+36)/817,2),"% hypothetical or putative.")
- print("there is", len(list_feature) ,"features in total, including",round(100*(2108+171)/3510,2),"% hypothetical or putative.")
+
+ # prints the stats for the segments
+ #print(len(seg_first),"segments missing at the beginning of a feature, of mean length", round(mean(seg_first),2), "and median length",median(seg_first))
+ #print(len(seg_middle),"segments missing in the middle of a feature, of mean length", round(mean(seg_middle),2), "and median length",median(seg_middle))
+ #print(len(seg_last), "segments missing at the end of a feature, of mean length", round(mean(seg_last),2), "and median length",median(seg_last))
+ #print(len(seg_entier),"segments that have an entiere feature (not in beggining/middle/end) missing, of mean length", round(mean(seg_entier),2), "and median length",median(seg_entier))
+ #print(len(seg_total),"segments that have a feature piece missing, of mean length", round(mean(seg_total),2), "and median length",median(seg_total))
+ #print(len(seg_ok),"segments that have a feature found, of mean length", round(mean(seg_ok),2), "and median length", median(seg_ok))
+ #Â creates files with the features by category
feat_miss_first=open('features_missing_first.txt','w')
feat_miss_first.write("features missing the first segment on azucena :\n")
for first in feature_missing_first :
feat_miss_first.write(Features[first].annot)
+ if Features[first].type!='gene':
+ feat_miss_first.write(';')
+ feat_miss_first.write(Features[first].note)
feat_miss_first.write("\n")
feat_miss_first.close()
@@ -380,6 +536,9 @@ def genome_gff(pos_seg, gff, out):
feat_miss_middle.write("\nfeatures missing a middle segment on azucena :\n")
for middle in feature_missing_middle :
feat_miss_middle.write(Features[middle].annot)
+ if Features[middle].type!='gene':
+ feat_miss_middle.write(';')
+ feat_miss_middle.write(Features[middle].note)
feat_miss_middle.write("\n")
feat_miss_middle.close()
@@ -387,6 +546,9 @@ def genome_gff(pos_seg, gff, out):
feat_miss_last.write("\nfeatures missing the last segment on azucena :\n")
for last in feature_missing_last :
feat_miss_last.write(Features[last].annot)
+ if Features[last].type!='gene':
+ feat_miss_last.write(';')
+ feat_miss_last.write(Features[last].note)
feat_miss_last.write("\n")
feat_miss_last.close()
@@ -394,82 +556,74 @@ def genome_gff(pos_seg, gff, out):
feat_miss.write("\nfeatures missing entirely on azucena :\n")
for entier in feature_missing_all :
feat_miss.write(Features[entier].annot)
+ if Features[entier].type!='gene':
+ feat_miss.write(';')
+ feat_miss.write(Features[entier].note)
feat_miss.write("\n")
feat_miss.close()
feat_miss_total=open('features_missing_total.txt','w')
- feat_miss_total.write("\nfeatures missing a segment on azucena :\n")
+ feat_miss_total.write("\nfeatures missing at least one segment on azucena :\n")
for total in feature_missing_total :
feat_miss_total.write(Features[total].annot)
+ if Features[total].type!='gene':
+ feat_miss_total.write(';')
+ feat_miss_total.write(Features[total].note)
feat_miss_total.write("\n")
feat_miss_total.close()
feat_all=open('all_features.txt','w')
for feat in list_feature:
feat_all.write(Features[feat].annot)
+ if Features[feat].type!='gene':
+ feat_all.write(';')
+ feat_all.write(Features[feat].note)
feat_all.write("\n")
feat_all.close()
-
+ feat_ok=open('features_ok.txt','w')
+ feat_ok.write("\nfeatures entirely present in azucena :\n")
+ for ok in feature_ok :
+ feat_ok.write(Features[ok].annot)
+ if Features[ok].type!='gene':
+ feat_ok.write(';')
+ feat_ok.write(Features[ok].note)
+ feat_ok.write("\n")
+ feat_ok.close()
+ # prints the stats for the features (hypothetical/putative rate, by category)
+ hyp_put=int(subprocess.getoutput("grep 'hypothetical\|putative' features_missing_first.txt | wc -l",))
+ total=int(subprocess.getoutput("wc -l < features_missing_first.txt"))
+ print("\nthe first segment is missing for", len(feature_missing_first) ,"features, including",round(100*(hyp_put)/len(feature_missing_first),2),"% hypothetical or putative.")
- # writes the gff of azucena using the gff of the graph
-def genome_gff_test(pos_seg, gff, out):
-
- print("generation of the genome's gff ")
-
- # create a dictionnary with the positions of the segments on azucena
- seg_ac={}
- bed=open(pos_seg,'r')
- lines=bed.readlines()
- for line in lines:
- line=line.split()
- s_id=line[3][1:]
- ch=line[0]
- start=line[1]
- stop=line[2]
- seg_ac[s_id]=list([ch,start,stop])
- bed.close()
-
- gff=open(gff,'r')
- file_out = open(out, 'w')
-
- lines=gff.readlines()
+ hyp_put=int(subprocess.getoutput("grep 'hypothetical\|putative' features_missing_middle.txt | wc -l",))
+ total=int(subprocess.getoutput("wc -l < features_missing_middle.txt"))
+ print("a middle segment is missing for", len(feature_missing_middle) ,"features, including",round(100*(hyp_put)/len(feature_missing_middle),2),"% hypothetical or putative.")
+
+ hyp_put=int(subprocess.getoutput("grep 'hypothetical\|putative' features_missing_last.txt | wc -l",))
+ total=int(subprocess.getoutput("wc -l < features_missing_last.txt"))
+ print("the last segment is missing for", len(feature_missing_last) ,"features, including",round(100*(hyp_put)/len(feature_missing_last),2),"% hypothetical or putative.")
+
+ hyp_put=int(subprocess.getoutput("grep 'hypothetical\|putative' features_missing.txt | wc -l",))
+ total=int(subprocess.getoutput("wc -l < features_missing.txt"))
+ print(len(feature_missing_all) ,"features are entirely missing, including",round(100*(hyp_put)/len(feature_missing_all),2),"% hypothetical or putative.")
+
+ hyp_put=int(subprocess.getoutput("grep 'hypothetical\|putative' features_missing_total.txt | wc -l",))
+ total=int(subprocess.getoutput("wc -l < features_missing_total.txt"))
+ print("there is at least one segment missing for", len(feature_missing_total) ,"features, including",round(100*(hyp_put)/len(feature_missing_total),2),"% hypothetical or putative.")
+
+ hyp_put=int(subprocess.getoutput("grep 'hypothetical\|putative' features_ok.txt | wc -l",))
+ total=int(subprocess.getoutput("wc -l < features_ok.txt"))
+ print(len(feature_ok) ,"features are entirely present in the new genome, including",round(100*(hyp_put)/len(feature_ok),2),"% hypothetical or putative.")
+
+ hyp_put=int(subprocess.getoutput("grep 'hypothetical\|putative' all_features.txt | wc -l",))
+ total=int(subprocess.getoutput("wc -l < all_features.txt"))
+ print("there is", len(list_feature) ,"features in total, including",round(100*(hyp_put)/len(list_feature),2),"% hypothetical or putative.")
+
+ command="rm features_missing*.txt && rm all_features.txt && rm features_ok.txt"
+ subprocess.run(command,shell=True)
- # get the list of all the features to transfer
- list_feature=list()
- for line in lines:
- id=(line.split()[8].split(";")[0].split("=")[1].replace(".","_").replace(":","_"))
- if id not in list_feature:
- list_feature.append(id)
-
-
- #Â for each feature, get list of the segments where it is
- for feat in list_feature:
- list_seg=Features[feat].segments_list
- size_list=len(list_seg)
-
- gene_start="empty"
- seg_start="empty"
- seg_stop="empty"
-
- # prints all gene fragments.
- for i in range(0,size_list):
-
- if (list_seg[i][1:] in seg_ac) & (1==1):
- feature=Features[feat]
- seg_start=list_seg[i][1:]
- seg_stop=list_seg[i][1:]
- chr=seg_ac[seg_start][0]
- start_azu=get_start_2(seg_start,seg_ac,feature.id)
- stop_azu=get_stop_2(seg_stop,seg_ac,feature.id)
- out_line=chr+" "+str(start_azu)+" "+str(stop_azu)+" "+seg_start+" "+seg_stop+" "+feature.id+"\n"
- file_out.write(out_line)
-
- file_out.close()
- gff.close()
-
diff --git a/main.py b/main.py
index 6d3ec680e47eb1e295db28beee8eed9b95c97ccb..36c88756b8b39350a24679b7261b9d9d5c1d48ef 100644
--- a/main.py
+++ b/main.py
@@ -1,7 +1,8 @@
import Functions as fct
# creates segments and features for the intersect between the graph for chr10 and the gff of IRGSP
-intersect_path='/home/nina/annotpangenome/align_genes/intersect_segments-features_chr10.bed'
+intersect_path='/home/nina/annotpangenome/align_genes/intersect_segments-genes_chr10.bed'
+#intersect_path='/home/nina/annotpangenome/align_genes/intersect_reel_genes_chr10.bed'
fct.create_seg_feat(intersect_path)
# outputs the gff of the graph for chr10
@@ -11,11 +12,14 @@ fct.graph_gff(output_file)
gff="new_graph_chr10.gff"
-if 1==0:
+genome = 'ac'
+
+if genome=='ac': # transfer grom graph to azucena
pos_seg="seg_coord/AzucenaRS1_chromosome10.bed"
- out="azucena_chr10_all.gff"
+ #out="azucena_chr10_all.gff"
+ out="azucena_chr10.gff"
-if 1==1:
+if genome=='nb': # transfer from graph to nipponbare
out="nb_chr10_all.gff"
pos_seg="seg_coord/IRGSP-1_0_Chr10.bed"