Unsupervised binning of environmental genomic fragments based on an error robust selection of l-mers.
Identifieur interne : 001F54 ( PubMed/Corpus ); précédent : 001F53; suivant : 001F55Unsupervised binning of environmental genomic fragments based on an error robust selection of l-mers.
Auteurs : Bin Yang ; Yu Peng ; Henry Chi-Ming Leung ; Siu-Ming Yiu ; Jing-Chi Chen ; Francis Yuk-Lun ChinSource :
- BMC bioinformatics [ 1471-2105 ] ; 2010.
English descriptors
- KwdEn :
- MESH :
- chemical , chemistry : DNA.
- genetics : Escherichia coli, Genome, Bacterial, Lactobacillus.
- methods : Data Mining, Metagenomics, Sequence Analysis, DNA.
- Algorithms, Cluster Analysis, Databases, Genetic, Environmental Microbiology.
Abstract
With the rapid development of genome sequencing techniques, traditional research methods based on the isolation and cultivation of microorganisms are being gradually replaced by metagenomics, which is also known as environmental genomics. The first step, which is still a major bottleneck, of metagenomics is the taxonomic characterization of DNA fragments (reads) resulting from sequencing a sample of mixed species. This step is usually referred as "binning". Existing binning methods are based on supervised or semi-supervised approaches which rely heavily on reference genomes of known microorganisms and phylogenetic marker genes. Due to the limited availability of reference genomes and the bias and instability of marker genes, existing binning methods may not be applicable in many cases.
DOI: 10.1186/1471-2105-11-S2-S5
PubMed: 20406503
Links to Exploration step
pubmed:20406503Le document en format XML
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The first step, which is still a major bottleneck, of metagenomics is the taxonomic characterization of DNA fragments (reads) resulting from sequencing a sample of mixed species. This step is usually referred as "binning". Existing binning methods are based on supervised or semi-supervised approaches which rely heavily on reference genomes of known microorganisms and phylogenetic marker genes. Due to the limited availability of reference genomes and the bias and instability of marker genes, existing binning methods may not be applicable in many cases.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">20406503</PMID><DateCompleted><Year>2010</Year><Month>08</Month><Day>02</Day></DateCompleted><DateRevised><Year>2018</Year><Month>11</Month><Day>13</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1471-2105</ISSN><JournalIssue CitedMedium="Internet"><Volume>11 Suppl 2</Volume><PubDate><Year>2010</Year><Month>Apr</Month><Day>16</Day></PubDate></JournalIssue><Title>BMC bioinformatics</Title><ISOAbbreviation>BMC Bioinformatics</ISOAbbreviation></Journal><ArticleTitle>Unsupervised binning of environmental genomic fragments based on an error robust selection of l-mers.</ArticleTitle><Pagination><MedlinePgn>S5</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1186/1471-2105-11-S2-S5</ELocationID><Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">With the rapid development of genome sequencing techniques, traditional research methods based on the isolation and cultivation of microorganisms are being gradually replaced by metagenomics, which is also known as environmental genomics. The first step, which is still a major bottleneck, of metagenomics is the taxonomic characterization of DNA fragments (reads) resulting from sequencing a sample of mixed species. This step is usually referred as "binning". Existing binning methods are based on supervised or semi-supervised approaches which rely heavily on reference genomes of known microorganisms and phylogenetic marker genes. Due to the limited availability of reference genomes and the bias and instability of marker genes, existing binning methods may not be applicable in many cases.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">In this paper, we present an unsupervised binning method based on the distribution of a carefully selected set of l-mers (substrings of length l in DNA fragments). From our experiments, we show that our method can accurately bin DNA fragments with various lengths and relative species abundance ratios without using any reference and training datasets. Another feature of our method is its error robustness. The binning accuracy decreases by less than 1% when the sequencing error rate increases from 0% to 5%. Note that the typical sequencing error rate of existing commercial sequencing platforms is less than 2%.</AbstractText><AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">We provide a new and effective tool to solve the metagenome binning problem without using any reference datasets or markers information of any known reference genomes (species). The source code of our software tool, the reference genomes of the species for generating the test datasets and the corresponding test datasets are available at http://i.cs.hku.hk/~alse/MetaCluster/.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Yang</LastName><ForeName>Bin</ForeName><Initials>B</Initials><AffiliationInfo><Affiliation>State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing, Jiangsu, 210096 PR China. byang@cs.hku.hk</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Peng</LastName><ForeName>Yu</ForeName><Initials>Y</Initials></Author><Author ValidYN="Y"><LastName>Leung</LastName><ForeName>Henry Chi-Ming</ForeName><Initials>HC</Initials></Author><Author ValidYN="Y"><LastName>Yiu</LastName><ForeName>Siu-Ming</ForeName><Initials>SM</Initials></Author><Author ValidYN="Y"><LastName>Chen</LastName><ForeName>Jing-Chi</ForeName><Initials>JC</Initials></Author><Author ValidYN="Y"><LastName>Chin</LastName><ForeName>Francis Yuk-Lun</ForeName><Initials>FY</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2010</Year><Month>04</Month><Day>16</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>BMC Bioinformatics</MedlineTA><NlmUniqueID>100965194</NlmUniqueID><ISSNLinking>1471-2105</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>9007-49-2</RegistryNumber><NameOfSubstance UI="D004247">DNA</NameOfSubstance></Chemical></ChemicalList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000465" 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