Faucet: streaming de novo assembly graph construction.
Identifieur interne : 000B15 ( PubMed/Corpus ); précédent : 000B14; suivant : 000B16Faucet: streaming de novo assembly graph construction.
Auteurs : Roye Rozov ; Gil Goldshlager ; Eran Halperin ; Ron ShamirSource :
- Bioinformatics (Oxford, England) [ 1367-4811 ] ; 2018.
English descriptors
- KwdEn :
- MESH :
- genetics : Microbiota.
- methods : Genomics, Sequence Analysis, DNA.
- Algorithms, Humans, Metagenome, Software.
Abstract
We present Faucet, a two-pass streaming algorithm for assembly graph construction. Faucet builds an assembly graph incrementally as each read is processed. Thus, reads need not be stored locally, as they can be processed while downloading data and then discarded. We demonstrate this functionality by performing streaming graph assembly of publicly available data, and observe that the ratio of disk use to raw data size decreases as coverage is increased.
DOI: 10.1093/bioinformatics/btx471
PubMed: 29036597
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Faucet: streaming de novo assembly graph construction.</title><author><name sortKey="Rozov, Roye" sort="Rozov, Roye" uniqKey="Rozov R" first="Roye" last="Rozov">Roye Rozov</name><affiliation><nlm:affiliation>Blavatnik School of Computer Science, Tel-Aviv University, Tel Aviv, Israel.</nlm:affiliation></affiliation></author><author><name sortKey="Goldshlager, Gil" sort="Goldshlager, Gil" uniqKey="Goldshlager G" first="Gil" last="Goldshlager">Gil Goldshlager</name><affiliation><nlm:affiliation>Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA, USA.</nlm:affiliation></affiliation></author><author><name sortKey="Halperin, Eran" sort="Halperin, Eran" uniqKey="Halperin E" first="Eran" last="Halperin">Eran Halperin</name><affiliation><nlm:affiliation>Departments of Computer Science, Anesthesiology and Perioperative Medicine, University of California Los Angeles, CA, USA.</nlm:affiliation></affiliation></author><author><name sortKey="Shamir, Ron" sort="Shamir, Ron" uniqKey="Shamir R" first="Ron" last="Shamir">Ron Shamir</name><affiliation><nlm:affiliation>Blavatnik School of Computer Science, Tel-Aviv University, Tel Aviv, Israel.</nlm:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2018">2018</date><idno type="RBID">pubmed:29036597</idno><idno type="pmid">29036597</idno><idno type="doi">10.1093/bioinformatics/btx471</idno><idno type="wicri:Area/PubMed/Corpus">000B15</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000B15</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Faucet: streaming de novo assembly graph construction.</title><author><name sortKey="Rozov, Roye" sort="Rozov, Roye" uniqKey="Rozov R" first="Roye" last="Rozov">Roye Rozov</name><affiliation><nlm:affiliation>Blavatnik School of Computer Science, Tel-Aviv University, Tel Aviv, Israel.</nlm:affiliation></affiliation></author><author><name sortKey="Goldshlager, Gil" sort="Goldshlager, Gil" uniqKey="Goldshlager G" first="Gil" last="Goldshlager">Gil Goldshlager</name><affiliation><nlm:affiliation>Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA, USA.</nlm:affiliation></affiliation></author><author><name sortKey="Halperin, Eran" sort="Halperin, Eran" uniqKey="Halperin E" first="Eran" last="Halperin">Eran Halperin</name><affiliation><nlm:affiliation>Departments of Computer Science, Anesthesiology and Perioperative Medicine, University of California Los Angeles, CA, USA.</nlm:affiliation></affiliation></author><author><name sortKey="Shamir, Ron" sort="Shamir, Ron" uniqKey="Shamir R" first="Ron" last="Shamir">Ron Shamir</name><affiliation><nlm:affiliation>Blavatnik School of Computer Science, Tel-Aviv University, Tel Aviv, Israel.</nlm:affiliation></affiliation></author></analytic><series><title level="j">Bioinformatics (Oxford, England)</title><idno type="eISSN">1367-4811</idno><imprint><date when="2018" type="published">2018</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>Genomics (methods)</term><term>Humans</term><term>Metagenome</term><term>Microbiota (genetics)</term><term>Sequence Analysis, DNA (methods)</term><term>Software</term></keywords><keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Microbiota</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Genomics</term><term>Sequence Analysis, DNA</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Humans</term><term>Metagenome</term><term>Software</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">We present Faucet, a two-pass streaming algorithm for assembly graph construction. Faucet builds an assembly graph incrementally as each read is processed. Thus, reads need not be stored locally, as they can be processed while downloading data and then discarded. We demonstrate this functionality by performing streaming graph assembly of publicly available data, and observe that the ratio of disk use to raw data size decreases as coverage is increased.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" IndexingMethod="Curated" Owner="NLM"><PMID Version="1">29036597</PMID><DateCompleted><Year>2018</Year><Month>09</Month><Day>26</Day></DateCompleted><DateRevised><Year>2018</Year><Month>11</Month><Day>13</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Electronic">1367-4811</ISSN><JournalIssue CitedMedium="Internet"><Volume>34</Volume><Issue>1</Issue><PubDate><Year>2018</Year><Month>01</Month><Day>01</Day></PubDate></JournalIssue><Title>Bioinformatics (Oxford, England)</Title><ISOAbbreviation>Bioinformatics</ISOAbbreviation></Journal><ArticleTitle>Faucet: streaming de novo assembly graph construction.</ArticleTitle><Pagination><MedlinePgn>147-154</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1093/bioinformatics/btx471</ELocationID><Abstract><AbstractText Label="Motivation">We present Faucet, a two-pass streaming algorithm for assembly graph construction. Faucet builds an assembly graph incrementally as each read is processed. Thus, reads need not be stored locally, as they can be processed while downloading data and then discarded. We demonstrate this functionality by performing streaming graph assembly of publicly available data, and observe that the ratio of disk use to raw data size decreases as coverage is increased.</AbstractText><AbstractText Label="Results">Faucet pairs the de Bruijn graph obtained from the reads with additional meta-data derived from them. We show these metadata-coverage counts collected at junction k-mers and connections bridging between junction pairs-contain most salient information needed for assembly, and demonstrate they enable cleaning of metagenome assembly graphs, greatly improving contiguity while maintaining accuracy. We compared Fauceted resource use and assembly quality to state of the art metagenome assemblers, as well as leading resource-efficient genome assemblers. Faucet used orders of magnitude less time and disk space than the specialized metagenome assemblers MetaSPAdes and Megahit, while also improving on their memory use; this broadly matched performance of other assemblers optimizing resource efficiency-namely, Minia and LightAssembler. However, on metagenomes tested, Faucet,o outputs had 14-110% higher mean NGA50 lengths compared with Minia, and 2- to 11-fold higher mean NGA50 lengths compared with LightAssembler, the only other streaming assembler available.</AbstractText><AbstractText Label="Availability and implementation">Faucet is available at https://github.com/Shamir-Lab/Faucet.</AbstractText><AbstractText Label="Contact">rshamir@tau.ac.il or eranhalperin@gmail.com.</AbstractText><AbstractText Label="Supplementary information">Supplementary data are available at Bioinformatics online.</AbstractText><CopyrightInformation>© The Author 2017. Published by Oxford University Press.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Rozov</LastName><ForeName>Roye</ForeName><Initials>R</Initials><AffiliationInfo><Affiliation>Blavatnik School of Computer Science, Tel-Aviv University, Tel Aviv, Israel.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Goldshlager</LastName><ForeName>Gil</ForeName><Initials>G</Initials><AffiliationInfo><Affiliation>Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Halperin</LastName><ForeName>Eran</ForeName><Initials>E</Initials><AffiliationInfo><Affiliation>Departments of Computer Science, Anesthesiology and Perioperative Medicine, University of California Los Angeles, CA, USA.</Affiliation></AffiliationInfo></Author><Author 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