barcode

Biopython으로 시퀀스 레코드 생성하고 만져보기

Coding/Python

오늘껀 근데 하면서 나도 이해 못했음... 

SeqRecord를 만들려면 뭘 또 모셔와야 하는데 바로 

from Bio.SeqRecord import SeqRecord

이놈이다. 

이정도면 복잡한 거 돌리려면 아주 모셔오는데만 열댓줄 쓰게 생겼는데??? 텐서플로우나 저기 그 넘파이 판다스처럼 합쳐버리지 그러냐... (걔네는 일단 한 번 데려오면 다 써먹을 수 있음) 

레코드 생성하기

이모지 넣고싶은데 이거 리눅스라 이모지 넣는 법을 모름... 아무튼 레코드는 이렇게 생성하면 된다. 

from Bio.SeqRecord import SeqRecord
from Bio.Seq import Seq
EcoRI=Seq("GAATTC") # ECoRI sequence
ECoRI_r=SeqRecord(EcoRI) #로 레코드를 만들어보겠습니다 
print(EcoRI)
print(ECoRI_r)

그러면 어떻게 나오느냐 

GAATTC # 시퀀스
ID: <unknown id> # 여기서부터 레코드
Name: <unknown name>
Description: <unknown description>
Number of features: 0
Seq('GAATTC')

이렇게 나온다. 뭐가 많이 빠졌지만 일단 레코드 맞다. 여기다 넣고싶으면 일단 다음 문단으로 가시고... 아니 그럼 생성할 때 넣을 수 있나요? 예. 됩니다. 

HaeIII_r=SeqRecord(HaeIII,id="RES_HAEIII",name="HaeIII restriction site",description="Restriction of HaeIII, cuts GG/CC")

노션도 되는 wrap이 안되는 코드블록... 네이버 니네 점검하면 대체 뭐하냐... 아무튼 이렇게 만들 때 넣으면  

ID: RES_HAEIII
Name: HaeIII restriction site
Description: Restriction of HaeIII, cuts GG/CC
Number of features: 0
Seq('GGCC')

이렇게 생성된다. 

 

레코드에 뭔가 넣기

아니 아까 만든거에 뭐 좀 어떻게 넣어주면 안됩니까? 아뇨 됩니다. 

# 레코드에 정보를 추가해보자
ECoRI_r.id="RES_ECORI"
ECoRI_r.name="ECoRI restriction site"
ECoRI_r.description="Restriction site of ECoRI, cuts G/AATTC"
# ID랑 이름, description 정보를 추가했다.

이렇게 필요한 정보를 넣어줄 수 있다. (참고: EcoRI이 맞는 표기다) 

ID: RES_ECORI
Name: ECoRI restriction site
Description: Restriction site of ECoRI, cuts G/AATTC
Number of features: 0
Seq('GAATTC')

제가 된다고 했잖아여... 

HaeIII_r.annotations["notes"]="갑자기 해삼이 먹고싶다. " # annotation
HaeIII_r.letter_annotations['letter annotations']=['G','G/','C','C'] # letter annotations
/notes=갑자기 해삼이 먹고싶다. 
Per letter annotation for: letter annotations

주석도 넣을 수 있다. 참고로 HaeIII은 Haemophilus influenzae biogroup aegyptius에서 유래한 제한효소. 본인은 해삼 혹은 해쓰리로 읽는다. (자매품 XbaI...)

 

FASTA에서 긁어오기

FASTA와 Genbank 파일에서 레코드를 긁어올 수도 있다. 후자쪽이 정보는 많음. 

from Bio import SeqIO
record=SeqIO.read('/home/koreanraichu/rcsb_pdb_7PNN.fasta','fasta')
print(record)
record=SeqIO.parse('/home/koreanraichu/rcsb_pdb_2B10.fasta','fasta')

FASTA 파일에 하나 들어있으면 read, 두 개 이상이면 parse로 긁어야 한다. (두 개 이상인데 read로 긁으면 ValueError: More than one record found in handle가 당신을 반길 것이다)

 

print(record.id)
7PNN_1|Chain
for record2 in SeqIO.parse("/home/koreanraichu/rcsb_pdb_2B10.fasta","fasta"):
    print(record2.id)
2B10_1|Chains
2B10_2|Chains

긁는 난이도치고 접근은 되게 쉽다. 근데 parse로 긁어오면 for문 써야 나온다... 

 

Genbank에서 긁어오기

record=SeqIO.read("/home/koreanraichu/sequence.gb",'genbank')
print(record)
print(record.description)
Homo sapiens hemoglobin subunit alpha 2 (HBA2), mRNA

얘는 리드로 파스고 없이 걍 긁어오면 접근이 바로 된다. 편한데? 

 

Feature

시퀀스 레코드의 정보를 담고 있다고 하는데 뭔지 모르겠는 건 기분탓이 아니다. 여기서 볼 것은 .type와 .location, .qualifiers이다. 

 

.type

for feature in record.features:
    print(feature.type)
source
gene
CDS
sig_peptide
mat_peptide
mat_peptide
mat_peptide
regulatory
polyA_site

얘도 for문 돌려야 나온다. 타입은 말 그대로 타입. 

​

.location

for feature in record.features:
    print(feature.location)
[0:432](+)
[0:432](+)
[41:371](+)
[41:113](+)
[113:200](+)
[206:293](+)
[299:368](+)
[413:419](+)
[431:432](+)

Feature의 위치 정보. +는 뭐임? 

 

.qualifiers

for feature in record.features:
    print(feature.qualifiers)
OrderedDict([('organism', ['Octodon degus']), ('mol_type', ['mRNA']), ('db_xref', ['taxon:10160']), ('tissue_type', ['pancreas'])])
OrderedDict([('gene', ['insulin'])])
OrderedDict([('gene', ['insulin']), ('codon_start', ['1']), ('product', ['insulin']), ('protein_id', ['AAA40590.1']), ('translation', ['MAPWMHLLTVLALLALWGPNSVQAYSSQHLCGSNLVEALYMTCGRSGFYRPHDRRELEDLQVEQAELGLEAGGLQPSALEMILQKRGIVDQCCNNICTFNQLQNYCNVP'])])
OrderedDict([('gene', ['insulin'])])
OrderedDict([('gene', ['insulin']), ('product', ['insulin B-chain'])])
OrderedDict([('gene', ['insulin']), ('product', ['insulin C-peptide'])])
OrderedDict([('gene', ['insulin']), ('product', ['insulin A-chain'])])
OrderedDict([('regulatory_class', ['polyA_signal_sequence']), ('gene', ['insulin'])])
OrderedDict([('gene', ['insulin'])])

Feature를 딕셔너리 형태로 저장해둔 것. Octodon degus는 데덴네의 모티브가 되기도 한 데구의 학명이다. 

 

Position과 location

Feature의 위치 정보. Position은 0차원(점)이고 Location은 1차원(선)이다.

location은 포지션 두 개가 있어야된다. 여부터 여까지라는 얘기니께...

from Bio import SeqFeature
start_pos=SeqFeature.ExactPosition(15)
end_pos=SeqFeature.ExactPosition(30)
location=SeqFeature.FeatureLocation(start_pos, end_pos)
print(start_pos,end_pos,location)
15 30 [15:30]
start_pos2 = SeqFeature.AfterPosition(1)
end_pos2 = SeqFeature.BetweenPosition(9, left=8, right=9)
my_location = SeqFeature.FeatureLocation(start_pos2, end_pos2)
print(start_pos2,end_pos2,my_location)
>1 (8^9) [>1:(8^9)]

30쓰니까 에러뜸... 

 

포지션이 명확할 때도 있고 명확하지 않을 때도 있다. 무슨 양자역학이냐... 슈뢰딩거의 포지션

 

start_pos2 = SeqFeature.AfterPosition(1)
end_pos2 = SeqFeature.BeforePosition(8)
my_location = SeqFeature.FeatureLocation(start_pos2, end_pos2)
print(start_pos2,end_pos2,my_location)
>1 <8 [>1:<8]

참고로 애프터가 있다는 것은 비포가 있다는 얘기이기도 하다. (대충 펀쿨섹좌 짤)

 

실제 파일에 적용해보기

ID: NM_000517.6
Name: NM_000517
Description: Homo sapiens hemoglobin subunit alpha 2 (HBA2), mRNA
Number of features: 44
/molecule_type=mRNA
/topology=linear
/data_file_division=PRI
/date=06-SEP-2021
/accessions=['NM_000517']
/sequence_version=6
/keywords=['RefSeq', 'MANE Select']
/source=Homo sapiens (human)
/organism=Homo sapiens
/taxonomy=['Eukaryota', 'Metazoa', 'Chordata', 'Craniata', 'Vertebrata', 'Euteleostomi', 'Mammalia', 'Eutheria', 'Euarchontoglires', 'Primates', 'Haplorrhini', 'Catarrhini', 'Hominidae', 'Homo']
/references=[Reference(title='Molecular and Hematological Analysis of Alpha- and Beta-Thalassemia in a Cohort of Mexican Patients', ...), Reference(title='Molecular Characterization and Hematological Aspects of Hb E-Myanmar [beta26(B8)Glu-->Lys and beta65(E9)Lys-->Asn, HBB: c.[79G>A;198G>C]): A Novel beta-Thalassemic Hemoglobin Variant', ...), Reference(title='delta-Globin Chain Variants Associated with Decreased Hb A2 Levels: A National Reference Laboratory Experience', ...), Reference(title='Heterozygosity for the Novel HBA2: c.*91_*92delTA Polyadenylation Site Variant on the alpha2-Globin Gene Expanding the Genetic Spectrum of alpha-Thalassemia in Iran', ...), Reference(title='Identification and characterization of two novel and differentially expressed isoforms of human alpha2- and alpha1-globin genes', ...), Reference(title='Alpha-Thalassemia', ...), Reference(title="Cloning and complete nucleotide sequence of human 5'-alpha-globin gene", ...), Reference(title='A new abnormal human hemoglobin: Hb Prato (alpha 2 31 (B12) Arg leads to Ser beta 2)', ...), Reference(title='Hemoglobin Suan-Dok (alpha 2 109 (G16) Leu replaced by Arg beta 2): an unstable variant associated with alpha-thalassemia', ...), Reference(title='Hemoglobin Tarrant: alpha126(H9) Asp leads to Asn. A new hemoglobin variant in the alpha1beta1 contact region showing high oxygen affinity and reduced cooperativity', ...)]
/comment=REVIEWED REFSEQ: This record has been curated by NCBI staff. The
reference sequence was derived from V00493.1, Z84721.1 and
AI016696.1.
This sequence is a reference standard in the RefSeqGene project.
On Aug 3, 2018 this sequence version replaced NM_000517.5.
Summary: The human alpha globin gene cluster located on chromosome
16 spans about 30 kb and includes seven loci: 5'- zeta - pseudozeta
- mu - pseudoalpha-1 - alpha-2 - alpha-1 - theta - 3'. The alpha-2
(HBA2) and alpha-1 (HBA1) coding sequences are identical. These
genes differ slightly over the 5' untranslated regions and the
introns, but they differ significantly over the 3' untranslated
regions. Two alpha chains plus two beta chains constitute HbA,
which in normal adult life comprises about 97% of the total
hemoglobin; alpha chains combine with delta chains to constitute
HbA-2, which with HbF (fetal hemoglobin) makes up the remaining 3%
of adult hemoglobin. Alpha thalassemias result from deletions of
each of the alpha genes as well as deletions of both HBA2 and HBA1;
some nondeletion alpha thalassemias have also been reported.
[provided by RefSeq, Jul 2008].
Publication Note:  This RefSeq record includes a subset of the
publications that are available for this gene. Please see the Gene
record to access additional publications.
COMPLETENESS: full length.
/structured_comment=OrderedDict([('Evidence-Data', OrderedDict([('Transcript exon combination', 'AI816040.1, AI815806.1 [ECO:0000332]'), ('RNAseq introns', 'single sample supports all introns SAMEA1965299, SAMEA1966682 [ECO:0000348]')])), ('RefSeq-Attributes', OrderedDict([('MANE Ensembl match', 'ENST00000251595.11/ ENSP00000251595.6'), ('RefSeq Select criteria', 'based on single protein-coding transcript')]))])
Seq('ACTCTTCTGGTCCCCACAGACTCAGAGAGAACCCACCATGGTGCTGTCTCCTGC...GCA')

오늘의 시범조교. 뭐야 wrap 돌려줘요.

 

record=SeqIO.read("/home/koreanraichu/sequence.gb",'genbank') # 여기서 뭘 뽑아봅시다
index=575
for feature in record.features:
    if index in feature:
        print("%s, %s, %s" %(feature.type,feature.location,feature.qualifiers.get("db_xref")))

여기서 575가 들어가는 feature를 찾아보자. 

 

source, [0:576](+), ['taxon:9606']
gene, [0:576](+), ['GeneID:3040', 'HGNC:HGNC:4824', 'MIM:141850']
exon, [337:576](+), None

아 그래서 이렇게 나온건가... (아직도 이해 못함) 

 

SeqFeature로 시퀀스의 특정 부분만 잘라서 보기

from Bio.Seq import Seq
from Bio.SeqFeature import SeqFeature, FeatureLocation
at5g40780=Seq("MVAQAPHDDHQDDEKLAAARQKEIEDWLPITSSRNAKWWYSAFHNVTAMVGAGVLGLPYAMSQLGWGPGIAVLVLSWVITLYTLWQMVEMHEMVPGKRFDRYHELGQHAFGEKLGLYIVVPQQLIVEIGVCIVYMVTGGKSLKKFHELVCDDCKPIKLTYFIMIFASVHFVLSHLPNFNSISGVSLAAAVMSLSYSTIAWASSASKGVQEDVQYGYKAKTTAGTVFNFFSGLGDVAFAYAGHNVVLEIQATIPSTPEKPSKGPMWRGVIVAYIVVALCYFPVALVGYYIFGNGVEDNILMSLKKPAWLIATANIFVVIHVIGSYQIYAMPVFDMMETLLVKKLNFRPTTTLRFFVRNFYVAATMFVGMTFPFFGGLLAFFGGFAFAPTTYFLPCVIWLAIYKPKKYSLSWWANWVCIVFGLFLMVLSPIGGLRTIVIQAKGYKFYS")
# 단백질 시퀀스 왜 이렇게 길어 이거
feature = SeqFeature(FeatureLocation(0, 30), type="protein", strand=1)
feature_seq = at5g40780[feature.location.start:feature.location.end]
print(feature_seq)

TAIR에서 돌아온 시범조교, LHT1의 단백질 시퀀스다. 뭐요. 파이참 wrap 일일이 켜기도 귀찮은데 걍 혀... 아무튼 feature라는 변수를 통해 30번째까지 볼 거라는 얘기다. strand가 -1이면 상보적인 시퀀스를 추출한다는데 저거 단백질이라 의미 없음. 

 

feature_seq2 = feature.extract(at5g40780)
print(feature_seq2)

Feature 변수 주고 extract해도 된다. 

 

레코드 비교하기

from Bio.Seq import Seq
from Bio.SeqRecord import SeqRecord
record1=SeqRecord(Seq("GAATTC"), id="ECoR1",description="sticky")
record2=SeqRecord(Seq("GGCC"), id="HaeIII",description="blunt")
record3=SeqRecord(Seq("CTCGAG"), id="XhoI",description="sticky")
record4=SeqRecord(Seq("GATC"), id="DpnII",description="sticky")

이번 시범조교는 얘네들이다. 

레코드 비교? 그럼 다이렉트로 비교 되나요? 그러면 NotImplementedError: SeqRecord comparison is deliberately not implemented. Explicitly compare the attributes of interest. 에러가 당신을 반겨줄 것이다. 레코드 비교는 안에 든 걸 비교하는거지 레코드를 쌩으로 비교하라는 얘기가 아니다. 

 

print(record1.description==record3.description)
True

EcoRI과 XhoI의 description이 같으므로 참이다. 

print(len(record1.seq)==len(record2.seq))
False

EcoRI과 HaeIII의 시퀀스 길이는 다르므로 false. 

 

포맷 만들기

아니 컴퓨터 포맷 아님. 

 

from Bio.Seq import Seq
from Bio.SeqRecord import SeqRecord
record=SeqRecord(
    Seq(
        "ATGGTAGCTCAAGCTCCTCATGATGATCATCAGGATGATGAGAAATTAGCAGCAGCGAGACAAAAAGAGATCGAAGATTGGTTACCAATTACTTCATCAAGAAATGCAAAGTGGTGGTACTCTGCTTTTCACAATGTCACCGCCATGGTCGGTGCCGGAGTTCTTGGACTCCCTTACGCCATGTCTCAGCTCGGATGGGGACCGGGAATTGCAGTGTTGGTTTTGTCATGGGTCATAACACTATACACATTATGGCAAATGGTGGAAATGCATGAAATGGTTCCTGGAAAGCGTTTTGATCGTTACCATGAGCTCGGACAACACGCGTTTGGAGAAAAACTCGGTCTTTATATCGTTGTGCCGCAACAATTGATCGTTGAAATCGGTGTTTGCATCGTTTATATGGTCACTGGAGGCAAATCTTTAAAGAAATTTCATGAGCTTGTTTGTGATGATTGTAAACCAATCAAGCTTACTTATTTCATCATGATCTTTGCTTCGGTTCACTTCGTCCTCTCTCATCTTCCTAATTTCAATTCCATCTCCGGCGTTTCTCTTGCTGCTGCCGTTATGTCTCTCAGCTACTCAACAATCGCATGGGCATCATCAGCAAGCAAAGGTGTTCAAGAAGACGTTCAATACGGTTACAAAGCGAAAACAACAGCCGGTACGGTTTTCAATTTCTTCAGCGGTTTAGGTGATGTGGCATTTGCTTACGCGGGTCATAATGTGGTCCTTGAGATCCAAGCAACTATCCCTTCAACGCCTGAGAAACCCTCAAAAGGTCCCATGTGGAGAGGAGTCATCGTTGCTTACATCGTCGTAGCGCTCTGTTATTTCCCCGTGGCTCTCGTTGGATACTACATTTTCGGGAACGGAGTCGAAGATAATATTCTCATGTCACTTAAGAAACCGGCGTGGTTAATCGCCACGGCGAACATCTTCGTCGTGATCCATGTCATTGGTAGTTACCAGATATATGCAATGCCGGTATTTGATATGATGGAGACTTTATTGGTCAAGAAGCTAAATTTCAGACCAACCACAACTCTTCGGTTCTTTGTCCGTAATTTCTACGTTGCTGCAACTATGTTTGTTGGTATGACGTTTCCGTTCTTCGGTGGGCTTTTGGCGTTCTTTGGTGGATTCGCGTTTGCCCCAACCACATACTTCCTCCCTTGCGTCATTTGGTTAGCCATCTACAAACCCAAGAAATACAGCTTGTCTTGGTGGGCCAACTGGGTATGCATCGTGTTTGGTCTTTTCTTGATGGTCCTATCGCCAATTGGAGGGCTAAGGACAATCGTTATTCAAGCAAAAGGATACAAGTTTTACTCATAA"),
id="at5g40780|LHT1",
description="Lysine-histidine transporter 1|Arabidopsis thaliana")
print(record.format("fasta"))

이런 식으로 입력하면 

 

>at5g40780|LHT1 Lysine-histidine transporter 1|Arabidopsis thaliana
ATGGTAGCTCAAGCTCCTCATGATGATCATCAGGATGATGAGAAATTAGCAGCAGCGAGA
CAAAAAGAGATCGAAGATTGGTTACCAATTACTTCATCAAGAAATGCAAAGTGGTGGTAC
TCTGCTTTTCACAATGTCACCGCCATGGTCGGTGCCGGAGTTCTTGGACTCCCTTACGCC
ATGTCTCAGCTCGGATGGGGACCGGGAATTGCAGTGTTGGTTTTGTCATGGGTCATAACA
CTATACACATTATGGCAAATGGTGGAAATGCATGAAATGGTTCCTGGAAAGCGTTTTGAT
CGTTACCATGAGCTCGGACAACACGCGTTTGGAGAAAAACTCGGTCTTTATATCGTTGTG
CCGCAACAATTGATCGTTGAAATCGGTGTTTGCATCGTTTATATGGTCACTGGAGGCAAA
TCTTTAAAGAAATTTCATGAGCTTGTTTGTGATGATTGTAAACCAATCAAGCTTACTTAT
TTCATCATGATCTTTGCTTCGGTTCACTTCGTCCTCTCTCATCTTCCTAATTTCAATTCC
ATCTCCGGCGTTTCTCTTGCTGCTGCCGTTATGTCTCTCAGCTACTCAACAATCGCATGG
GCATCATCAGCAAGCAAAGGTGTTCAAGAAGACGTTCAATACGGTTACAAAGCGAAAACA
ACAGCCGGTACGGTTTTCAATTTCTTCAGCGGTTTAGGTGATGTGGCATTTGCTTACGCG
GGTCATAATGTGGTCCTTGAGATCCAAGCAACTATCCCTTCAACGCCTGAGAAACCCTCA
AAAGGTCCCATGTGGAGAGGAGTCATCGTTGCTTACATCGTCGTAGCGCTCTGTTATTTC
CCCGTGGCTCTCGTTGGATACTACATTTTCGGGAACGGAGTCGAAGATAATATTCTCATG
TCACTTAAGAAACCGGCGTGGTTAATCGCCACGGCGAACATCTTCGTCGTGATCCATGTC
ATTGGTAGTTACCAGATATATGCAATGCCGGTATTTGATATGATGGAGACTTTATTGGTC
AAGAAGCTAAATTTCAGACCAACCACAACTCTTCGGTTCTTTGTCCGTAATTTCTACGTT
GCTGCAACTATGTTTGTTGGTATGACGTTTCCGTTCTTCGGTGGGCTTTTGGCGTTCTTT
GGTGGATTCGCGTTTGCCCCAACCACATACTTCCTCCCTTGCGTCATTTGGTTAGCCATC
TACAAACCCAAGAAATACAGCTTGTCTTGGTGGGCCAACTGGGTATGCATCGTGTTTGGT
CTTTTCTTGATGGTCCTATCGCCAATTGGAGGGCTAAGGACAATCGTTATTCAAGCAAAA
GGATACAAGTTTTACTCATAA

이렇게 FASTA 포맷이 된다. 

 

슬라이싱

feature도 slicing이 된다. 어째서인지는 모르겠으나... 

 

from Bio import SeqIO
record = SeqIO.read("/home/koreanraichu/sequence.gb", "genbank")
print(record.features[20])

이건 근데 인덱싱 아니냐. 

 

sub_record = record[0:5]
print(sub_record)
ID: NM_000517.6
Name: NM_000517
Description: Homo sapiens hemoglobin subunit alpha 2 (HBA2), mRNA
Number of features: 0
/molecule_type=mRNA
Seq('ACTCT')

아무튼 레코드에서 0부터 5까지 뽑아보았다. 염기 6개가 나온다. 

 

record = SeqIO.read("/home/koreanraichu/sequence.gb", "genbank")
sub_record = record[0:576]
print(sub_record.features[0])

범위를 풀로 바꾸고 0번째 feature를 봤다. 

 

type: source
location: [0:576](+)
qualifiers:
    Key: chromosome, Value: ['16']
    Key: db_xref, Value: ['taxon:9606']
    Key: map, Value: ['16p13.3']
    Key: mol_type, Value: ['mRNA']
    Key: organism, Value: ['Homo sapiens']

그러면 이렇게 나옵니다.

 

print(sub_record.format("genbank"))
print(sub_record.format("fasta"))

위 코드를 이용해 출력 포맷을 바꿀 수도 있다. 

>NM_000517.6 Homo sapiens hemoglobin subunit alpha 2 (HBA2), mRNA
ACTCTTCTGGTCCCCACAGA
# FASTA
LOCUS       NM_000517                 20 bp    mRNA             UNK 01-JAN-1980
DEFINITION  Homo sapiens hemoglobin subunit alpha 2 (HBA2), mRNA.
ACCESSION   NM_000517
VERSION     NM_000517.6
KEYWORDS    .
SOURCE      .
  ORGANISM  .
            .
FEATURES             Location/Qualifiers
ORIGIN
        1 actcttctgg tccccacaga
//
# Genbank

위는 FASTA, 아래는 Genbank 포맷. 

 

저작자표시

'Coding > Python' 카테고리의 다른 글

번외편-코딩테스트 풀이  (0) 2022.08.20
Biopython으로 MSA 해보기  (0) 2022.08.20
Biopython SeqIO 써보기  (0) 2022.08.20
Biopython으로 시퀀스 다뤄보기  (0) 2022.08.20
Biopython으로 시퀀스 가져오기  (0) 2022.08.20
2022. 8. 20. 02:30

티스토리툴바