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ISO_anno_combine.py
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# -*- coding: utf-8 -*-
"""
Author: Zhang Chengsheng, @2020.03.16
临时性脚本，用于从二代三代独立注释结果中选出最优解。是二三代混装注释最终版的临时替代品。
不排除后期跳票扶正的可能性
"""
import os,sys,pickle
import ISO_anno_V02
import transcript_cluster
sys.setrecursionlimit(100000000)
def pickle_make(dict_in,file_out):
with open(file_out, 'wb') as o:
pickle.dump(dict_in, o)
def main(bed_long,bed_short,output):
long = ISO_anno_V02.bed_read(bed_long) if bed_long else {}
short = ISO_anno_V02.bed_read(bed_short) if bed_short else {}
bed_out = output + '.bed'
stat_out = output + '.stat'
classification_q = {
'FSM':0,
'ISM':1,
'NIC':2,
'NNC':3,
'FUSION': 4,
'Genic':5,
'Intergenic':6,
'UNKNOWN':10,
}
StructureDB = transcript_cluster.structure_save()
Anno_DB = transcript_cluster.structure_save()
Gene2transciptDB = transcript_cluster.structure_save()
ClassificationDB = transcript_cluster.structure_save()
ClusterSM = transcript_cluster.tcluster()
ClusterNC = transcript_cluster.tcluster()
ClusterGENIC = transcript_cluster.tcluster()
ClusterFUSION = transcript_cluster.tcluster()
def add_CLUSTER(A):
StructureDB.saveReadsinfo(A)
ClassificationDB.saveClassification(A)
Anno_DB.saveAnnoDB(A)
if A.classification in ['FSM', 'ISM']:
ClusterSM.add_SM_node(A.CHROMS[0], A.best_gene, A.best_transcript, id)
Gene2transciptDB.saveGene2transcript(A)
elif A.classification in ['NIC', 'NNC']:
ClusterNC.add_NSM_node(A.CHROMS[0], [min(A.REF_START), max(A.REF_END)], A.loc_format(), id, A.best_gene,A.classification,node=0)
elif A.classification in ['Genic', 'Intergenic']:
ClusterGENIC.add_NSM_node(A.CHROMS[0], [min(A.REF_START), max(A.REF_END)], A.loc_format(), id, A.best_gene,A.classification,node=0)
elif A.classification in ['FUSION']:
ClusterFUSION.add_FUSION_node(A)
with open(bed_out,'w') as bed, open(stat_out,'w') as stat:
stat.write('ID\tType\tSubtype\tGene\tTranscript\tChrom\tStrand\tSeq_length\tSeq_exon_num\tRef_length\tRef_exon_num\tdiff_to_gene_start\tdiff_to_gene_end\tdiff_to_transcript_start\tdiff_to_transcript_end\n')
count = 0
t = 10
for id in sorted(list(set(list(long) + list(short)))):
count += 1
print('\r{}\t{}'.format(count,id),end='',flush=1),
if id in long:
A = ISO_anno_V02.Isoform_bed_read(id, long[id])
A1 = A._break_point_cluster()
A.annotation(db, A1)
classificationA = A.classification
_23A = 1 if [i for i in A.EXONS_TYPE if i < 40] else 0
else:
classificationA = 0
_23A = 0
if id in short:
B = ISO_anno_V02.Isoform_bed_read(id, short[id])
B1 = B._break_point_cluster()
B.annotation(db, B1)
classificationB = B.classification
_23B = 1 if [i for i in B.EXONS_TYPE if i < 40] else 0
else:
classificationB = 0
_23B = 0
if classificationA and classificationB:
fA = 8 if classification_q[classificationA] == 3 and not _23A else classification_q[classificationA]
fB = 8 if classification_q[classificationB] == 3 and not _23B else classification_q[classificationB]
C,C1,_23 = [A,B,2] if fA < fB else [B,A,3]
add_CLUSTER(C)
txt1 = C.stat_format()
txt2 = C.bed_format(t=t)
bed.write(txt2)
if classification_q[classificationA] != classification_q[classificationB]:
stat.write(txt1.strip('\n')+'\t{}\t{}\t{}\n'.format(_23,C1.classification,C1.subtype))
else:
stat.write(txt1)
elif classificationA:
add_CLUSTER(A)
txt1 = A.stat_format()
txt2 = A.bed_format(t=t)
bed.write(txt2)
stat.write(txt1)
elif classificationB:
add_CLUSTER(B)
txt1 = B.stat_format()
txt2 = B.bed_format(t=t)
bed.write(txt2)
stat.write(txt1)
else:
#info = [0,0,0,0,0,0,0,0,0,0,0,0,0]
txt1 = B.stat_format()
txt2 = B.bed_format(t=t)
bed.write(txt2)
stat.write(txt1)
txt3 = ClusterFUSION.tree_FUSION_view()
ClusterFUSION.txt_write(txt3,output+'.FUSION.cluster')
txt0 = ClusterSM.tree_SM_view()
ClusterSM.txt_write(txt0,output+'.SM.cluster')
txt1 = ClusterNC.tree_NSM_view(ClusterNC.tree)
ClusterNC.txt_write(txt1,output+'.NC.cluster')
txt2 = ClusterGENIC.tree_NSM_view(ClusterGENIC.tree)
ClusterGENIC.txt_write(txt2, output + '.GENIC.cluster')
Gene2transciptDB.addGene2transcript(ClusterNC.NSM)
Gene2transciptDB.addGene2transcript(ClusterGENIC.NSM)
PaintDB = {'reads':StructureDB.d,'gene2transcript':Gene2transciptDB.d,'annotation':Anno_DB.d,'classification':ClassificationDB.d,'fusion':ClusterFUSION.FUSION}
pickle_make(PaintDB,output+'.db.pickle')
def option(argv):
from argparse import ArgumentParser as AP
usages = "python3 {} -d db_in -2 short_reads_bed -3 long_reads_bed -o output".format(argv[0])
p = AP(usage=usages)
p.add_argument("-d", dest="db_in", metavar="sam_dict", help="gtf_dict file.")
p.add_argument("-2", dest="short", metavar="short_reads_bed", help="short reads bed format file",default=0)
p.add_argument("-3", dest="long", metavar="long_reads_bed", help="long reads bed format file",default=0)
p.add_argument("-o", dest="out_preffix", metavar="output_file", help="bed&stat file out.")
p.add_argument("-p", dest="process", metavar="[int]", help="process, default: 1", type=int,default=1)
if len(argv) == 1:
p.print_help()
exit(1)
return p.parse_args(argv[1:])
if __name__ == '__main__':
#gtf = r'/public/source/share/zcs/data/GTF/hg38.ensembl.v20200306.1.pickle'
args = option(sys.argv)
gtf = args.db_in
db = ISO_anno_V02.load_pickle(gtf)
bed_long = args.long
bed_short = args.short
output = args.out_preffix
main(bed_long, bed_short, output)