Rcorrector: efficient and accurate error correction for Illumina RNA-seq reads.
Identifieur interne : 001374 ( PubMed/Checkpoint ); précédent : 001373; suivant : 001375Rcorrector: efficient and accurate error correction for Illumina RNA-seq reads.
Auteurs : Li Song [États-Unis] ; Liliana Florea [États-Unis]Source :
- GigaScience [ 2047-217X ] ; 2015.
Descripteurs français
- KwdFr :
- MESH :
- génétique : ARN.
- Analyse de séquence d'ARN.
English descriptors
- KwdEn :
- MESH :
- chemical , genetics : RNA.
- methods : Sequence Analysis, RNA.
Abstract
Next-generation sequencing of cellular RNA (RNA-seq) is rapidly becoming the cornerstone of transcriptomic analysis. However, sequencing errors in the already short RNA-seq reads complicate bioinformatics analyses, in particular alignment and assembly. Error correction methods have been highly effective for whole-genome sequencing (WGS) reads, but are unsuitable for RNA-seq reads, owing to the variation in gene expression levels and alternative splicing.
DOI: 10.1186/s13742-015-0089-y
PubMed: 26500767
Affiliations:
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However, sequencing errors in the already short RNA-seq reads complicate bioinformatics analyses, in particular alignment and assembly. Error correction methods have been highly effective for whole-genome sequencing (WGS) reads, but are unsuitable for RNA-seq reads, owing to the variation in gene expression levels and alternative splicing.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">26500767</PMID><DateCompleted><Year>2016</Year><Month>07</Month><Day>25</Day></DateCompleted><DateRevised><Year>2018</Year><Month>11</Month><Day>13</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Print">2047-217X</ISSN><JournalIssue CitedMedium="Print"><Volume>4</Volume><PubDate><Year>2015</Year></PubDate></JournalIssue><Title>GigaScience</Title><ISOAbbreviation>Gigascience</ISOAbbreviation></Journal><ArticleTitle>Rcorrector: efficient and accurate error correction for Illumina RNA-seq reads.</ArticleTitle><Pagination><MedlinePgn>48</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1186/s13742-015-0089-y</ELocationID><Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">Next-generation sequencing of cellular RNA (RNA-seq) is rapidly becoming the cornerstone of transcriptomic analysis. However, sequencing errors in the already short RNA-seq reads complicate bioinformatics analyses, in particular alignment and assembly. Error correction methods have been highly effective for whole-genome sequencing (WGS) reads, but are unsuitable for RNA-seq reads, owing to the variation in gene expression levels and alternative splicing.</AbstractText><AbstractText Label="FINDINGS" NlmCategory="RESULTS">We developed a k-mer based method, Rcorrector, to correct random sequencing errors in Illumina RNA-seq reads. Rcorrector uses a De Bruijn graph to compactly represent all trusted k-mers in the input reads. Unlike WGS read correctors, which use a global threshold to determine trusted k-mers, Rcorrector computes a local threshold at every position in a read.</AbstractText><AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">Rcorrector has an accuracy higher than or comparable to existing methods, including the only other method (SEECER) designed for RNA-seq reads, and is more time and memory efficient. With a 5 GB memory footprint for 100 million reads, it can be run on virtually any desktop or server. The software is available free of charge under the GNU General Public License from https://github.com/mourisl/Rcorrector/.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Song</LastName><ForeName>Li</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Department of Computer Science, Johns Hopkins University, Baltimore, 21218 USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Florea</LastName><ForeName>Liliana</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Department of Computer Science, Johns Hopkins University, Baltimore, 21218 USA ; McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, 21205 USA.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. 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MajorTopicYN="N">Next-generation sequencing</Keyword><Keyword MajorTopicYN="N">RNA-seq</Keyword><Keyword MajorTopicYN="N">k-mers</Keyword></KeywordList><GeneralNote Owner="NLM">Original DateCompleted: 20151027</GeneralNote></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2015</Year><Month>06</Month><Day>01</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2015</Year><Month>10</Month><Day>09</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2015</Year><Month>10</Month><Day>27</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2015</Year><Month>10</Month><Day>27</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2015</Year><Month>10</Month><Day>27</Day><Hour>6</Hour><Minute>1</Minute></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">26500767</ArticleId><ArticleId 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May;19(5):455-77</Citation><ArticleIdList><ArticleId IdType="pubmed">22506599</ArticleId></ArticleIdList></Reference></ReferenceList></PubmedData></pubmed><affiliations><list><country><li>États-Unis</li></country><region><li>Maryland</li></region><settlement><li>Baltimore</li></settlement></list><tree><country name="États-Unis"><region name="Maryland"><name sortKey="Song, Li" sort="Song, Li" uniqKey="Song L" first="Li" last="Song">Li Song</name></region><name sortKey="Florea, Liliana" sort="Florea, Liliana" uniqKey="Florea L" first="Liliana" last="Florea">Liliana Florea</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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