inference.py

from Graph_gff import Features,load_intersect
from Functions import get_segment_sequence,convert_strand

target_genome_name="genome4_chr10"

intersect_path='/home/nina/annotpangenome/test_data/input_data_inf/intersect.bed'
load_intersect(intersect_path)

gfa="test_data/input_data_inf/graph_test.gfa"
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:])
 
            paths[line[3]]=list_path
    return [paths,seg_seq]

[paths,seg_seq]=get_segments_sequence_and_paths(gfa)

segments_on_target_genome={}
pos_seg="test_data/input_data_inf/genome3_chr10.bed"
def get_segments_positions_on_genome(pos_seg):
    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,strand]=[line[3][1:],line[0],line[1],line[2],line[3][0:1]]
        segments_on_target_genome[seg]=[chrom,start,stop,strand]
get_segments_positions_on_genome(pos_seg)

def add_feature_sequence(feature,seg_seq):
    feature_sequence=""
    for segment in feature.segments_list:
        if segment==feature.segments_list[0]:
            feature_sequence+=get_segment_sequence(seg_seq,segment)[feature.pos_start-1:] # revérifier les +/- 1 pour la position, avec de vraies données
        elif segment==feature.segments_list[-1]:
            feature_sequence+=get_segment_sequence(seg_seq,segment)[0:feature.pos_stop] # revérifier les +/- 1 pour la position, avec de vraies données
        else:
            feature_sequence+=get_segment_sequence(seg_seq,segment)
    feature.sequence=feature_sequence

def get_first_seg(list_seg,segments_on_target_genome):
    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_feature_path(paths,first_seg,last_seg):
    # find the path in azucena. 
    first_strand=convert_strand(segments_on_target_genome[first_seg][3])
    first_seg_stranded=first_strand+first_seg
    last_strand=convert_strand(segments_on_target_genome[last_seg][3])
    last_seg_stranded=last_strand+last_seg
    index_first_seg=int(paths[target_genome_name].index(first_seg_stranded))
    index_last_seg=int(paths[target_genome_name].index(last_seg_stranded))
    first_index=min(index_first_seg,index_last_seg)
    last_index=max(index_last_seg,index_first_seg)
    list_segfeat_azu=paths[target_genome_name][first_index:last_index+1]
    list_segfeat_azu_corrected=[convert_strand(segment_stranded[0])+segment_stranded[1:] for segment_stranded in list_segfeat_azu]
    return list_segfeat_azu_corrected


def get_rna(dna_sequence):
    return dna_sequence.replace("T","U")

# penser à transcrire la séquence codante du gène !!
def get_aa(codon):
    match codon[0:2]:
        case "UU":
            if (codon[2]=="U") | (codon[2]=="C"):
                return "Phe"
            else:
                return "Leu"
        case "UC":
            return "Ser"
        case "UA":
            if (codon[2]=="U") | (codon[2]=="C"):
                return "Tyr"
            else:
                return "*"
        case "UG":
            if (codon[2]=="U") | (codon[2]=="C"):
                return "Cys"
            elif codon[2]=="A":
                return "*"
            else:
                return "Trp"
        case "CU":
            return "Leu"
        case "CC":
            return "Pro"
        case "CA":
            if (codon[2]=="U") | (codon[2]=="C"):
                return "His"
            else:
                return "Gln"
        case "CG":
            return "Arg"
        case "AU":
            if codon[2]=="G":
                return "Met"
            else:
                return "Ile"
        case "AC":
            return "Thr"
        case "AA":
            if (codon[2]=="U") | (codon[2]=="C"):
                return "Asn"
            else:
                return "Lys"
        case "AG":
            if (codon[2]=="U") | (codon[2]=="C"):
                return "Ser"
            else:
                return "Arg"
        case "GU":
            return "Val"
        case "GC":
            return "Ala"
        case "GA":
            if (codon[2]=="U") | (codon[2]=="C"):
                return "Asp"
            else:
                return "Glu"
        case "GG":
            return "Gly"


def traduction(sequence_arn):
    list_codons=decoupe_codon(sequence_arn)
    prot=list()
    for codon in list_codons:
        prot.append(get_aa(codon))
    return prot


from textwrap import wrap
def decoupe_codon(sequence):
    return wrap(sequence,3)








def get_sequence_before(first_seg,seg_seq,n,paths,feat):
    first_strand=convert_strand(first_seg[0])
    first_seg_stranded=first_strand+first_seg[1:]
    index_first_seg=int(paths[target_genome_name].index(first_seg_stranded))

    sequence_before=seg_seq[first_seg[1:]][0:feat.pos_start-1] # sequence left on the segment on which the cds start (can be empty)
    current_index=index_first_seg-1
    while (len(sequence_before)<n) & (current_index>=0):
        segment=paths[target_genome_name][current_index]
        sequence_before=seg_seq[segment[1:]]+sequence_before
        current_index-=1
    return sequence_before[0:99]

def get_sequence_after(last_seg,seg_seq,n,paths,feat):
    last_strand=convert_strand(last_seg[0])
    last_seg_stranded=last_strand+last_seg[1:]
    index_last_seg=int(paths[target_genome_name].index(last_seg_stranded))

    sequence_after=seg_seq[last_seg[1:]][feat.pos_stop:] # sequence left on the segment on which the cds ends (can be empty)
    current_index=index_last_seg+1
    while (len(sequence_after)<n) & (current_index>len(paths[target_genome_name])):
        segment=paths[target_genome_name][current_index]
        sequence_after=sequence_after+seg_seq[segment[1:]]
        current_index+=1
    return sequence_after[len(sequence_after)-100:]



    '''
    first_strand=convert_strand(segments_on_target_genome[first_seg][3])
    first_seg_stranded=first_strand+first_seg
    last_strand=convert_strand(segments_on_target_genome[last_seg][3])
    last_seg_stranded=last_strand+last_seg
    index_first_seg=int(paths[target_genome_name].index(first_seg_stranded))
    index_last_seg=int(paths[target_genome_name].index(last_seg_stranded))
    first_index=min(index_first_seg,index_last_seg)
    last_index=max(index_last_seg,index_first_seg)
    list_segfeat_azu=paths[target_genome_name][first_index:last_index+1]
    list_segfeat_azu_corrected=[convert_strand(segment_stranded[0])+segment_stranded[1:] for segment_stranded in list_segfeat_azu]
    '''


def get_sequence_on_genome(feature,segments_on_target_genome):
    list_seg=Features[feature].segments_list
    first_seg=get_first_seg(list_seg,segments_on_target_genome)
    last_seg=get_first_seg(reversed(list_seg),segments_on_target_genome)
    path_on_target=get_feature_path(paths,first_seg,last_seg)

    new_sequence=""
    for segment in path_on_target:
        if segment==cds.segments_list[0]:
            new_sequence+=get_segment_sequence(seg_seq,segment)[cds.pos_start-1:]
        elif segment==cds.segments_list[-1]:
            new_sequence+=get_segment_sequence(seg_seq,segment)[0:cds.pos_stop]
        else:
            new_sequence+=get_segment_sequence(seg_seq,segment)
    return new_sequence


var=open("test_data/variations.txt",'r')
lines=var.readlines()
var.close()

# dict cds-var
cds_var={}
for line in lines:
    line=line.split()
    if line[1]=="CDS":
        cds_id=line[0].replace('.','_').replace(':','_')
        if cds_id not in cds_var.keys():
            cds_var[cds_id]=list()
        cds_var[cds_id].append(line)


for feature in Features.values():
    add_feature_sequence(feature,seg_seq)


version="new"
import re
for cds_id in cds_var.keys():
    cds=Features[cds_id]
    print("analysing variations in cds",cds_id)

    for var in cds_var[cds_id]:
        size_var=int(var[11])
        type_var=var[8]
        pos_var=int(var[12])-1

        if pos_var<=3:
            print("codon start touché")

            #chercher start (dans le mrna) avant et apres

            # chercher codon start en amont du cds, dans le mrna
            seq_parent=get_sequence_on_genome(cds.parent,segments_on_target_genome)
            seq_cds=get_sequence_on_genome(cds_id,segments_on_target_genome)
            sequence_amont=seq_parent[0:seq_parent.rfind(seq_cds)] # get the mrna sequence before the last occurence of the cds sequence
            print(sequence_amont)
            if "ATG" in sequence_amont:
                start_pos_list=[m.start() for m in re.finditer('(?=ATG)', sequence_amont)]
                stop_pos_list=[m.start() for m in re.finditer('(?=TAG|TAA|TGA)', sequence_amont)]
                print(start_pos_list,stop_pos_list) # positions (overlapping) où on trouve un atg.
                # vérifier ensuite s'il y a un stop après un atg, et sinon le cadre de lecture de l'atg (peut décaler toute la prot !)
                for start_pos in start_pos_list:
                    print(start_pos)
                    start_pos_frame=start_pos%3
                    test_list=[39,46,47]
                    if True not in ( (stop_pos%3==start_pos_frame) & (stop_pos>start_pos) for stop_pos in stop_pos_list) :
                        n=len(sequence_amont)-start_pos
                        print("codon start candidat trouvé dans l'arn messager,",n,"bases en amont du cds")
                        # calculer le décalage : si on en trouve un 2 bases en amont, ça décale le cadre de lecture !
                        frame_shift=n%3 # mais si on a plusieurs start candidats il faut choisir celui qu'on prend !??

            # chercher codon start en aval, dans le cds
            if "ATG" in seq_cds:
                start_pos_list=[m.start() for m in re.finditer('(?=ATG)', seq_cds)]
                for pos in start_pos_list:
                    print("codon start candidat trouvé plus loin dans le cds, à la base",pos)
            







if version=="old":
    for cds_id in cds_var.keys(): # for a gene that has cds, concatenate all cds to make a prot. then detail var by cds.
        cds=Features[cds_id]
        print("analysing variations in cds",cds_id)
        add_feature_sequence(cds,seg_seq)
        cds_prot=traduction(get_rna(cds.sequence))

        list_seg=Features[cds_id].segments_list
        first_seg=get_first_seg(list_seg)
        last_seg=get_first_seg(reversed(list_seg))
        path_on_target=get_feature_path(paths,first_seg,last_seg)

        new_sequence=""
        for segment in path_on_target:
            if segment==cds.segments_list[0]:
                new_sequence+=get_segment_sequence(seg_seq,segment)[cds.pos_start-1:]
            elif segment==cds.segments_list[-1]:
                new_sequence+=get_segment_sequence(seg_seq,segment)[0:cds.pos_stop]
            else:
                new_sequence+=get_segment_sequence(seg_seq,segment)

        new_prot=traduction(get_rna(new_sequence))
        print("original prot = ", cds_prot)
        print("new prot = ", new_prot) # print new version with new start and stop codons of deleted. (before and after the gene sequence)


        if new_prot[0]!="Met":
            print("no Met at the start of the new version of the protein -> start codon loss")
            if "Met" in new_prot:
                print("Met found at position", (new_prot.index("Met")+1),"-> possible later start codon") # print cette version de la prot

            print("look for start codon before. if none, print 'no start codon, likely gene not active'")
            # récupérer n pb avant, les traduire, chercher la dernière Met (list[::-1].index("Met")), donner cette version de la prot

        sequence_before=get_sequence_before(path_on_target[0],seg_seq,100,paths,cds)
        print(sequence_before)


        first_stop_index=new_prot.index("*") if "*" in new_prot else "None"
        if "*" not in new_prot:
            print("no stop codon")
            # récupérer n pb après, les traduire, chercher le premier *, donner cette version de la prot.
        elif first_stop_index+1!=len(new_prot):
            print("early stop codon at position",(first_stop_index+1),"instead of",len(new_prot))
        else:
            print("stop codon found at expected position")

        sequence_after=get_sequence_after(path_on_target[-1],seg_seq,100,paths,cds)
        print(sequence_after)



        for var in cds_var[cds_id]:
            #print("\n",var)
            size_var=int(var[11])
            type_var=var[8]
            pos_var=int(var[12])-1


            if type_var=="insertions":
                sequence_var=var[10]
                if size_var%3==0:
                    print("pas de décalage du cadre de lecture")
                    trad_seq_ins=traduction(get_rna(sequence_var))

                    if pos_var%3==0:
                        print("insertion entre deux codons")
                        if "*" in trad_seq_ins:
                            print("apparition d'un codon stop")
                            print(f'ancienne sequence : {", ".join(cds_prot)}')
                            print(f'nouvelle sequence : {", ".join(cds_prot[0:(pos_var//3)-1])}, *')
                        else:
                            print(f'ancienne sequence : {", ".join(cds_prot)}')
                            print(f'{type_var} de {size_var//3} acides amines {", ".join(trad_seq_ins)} à la position {pos_var//3}')
                    else:
                        print("insertion au milieu d'un codon, changement de certains acides amines")

            elif type_var=="deletions":
                sequence_var=line[9]
                if size_var%3==0:
                    print("pas de décalage du cadre de lecture")
                    trad_seq_ins=traduction(get_rna(sequence_var))

                    if pos_var%3==0:
                        print("deletion de codons entiers")
                        if "*" in trad_seq_ins:
                            print("disparition d'un codon stop")
                        else:
                            print(f'ancienne sequence : {", ".join(cds_prot)}')
                            print(f'{type_var} de {size_var//3} acides amines {", ".join(trad_seq_ins)} à la position {pos_var//3}')
                    else:
                        print("deletion au milieu d'un codon, changement de certains acides amines")