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FLAME: long-read bioinformatics tool for comprehensive spliceome characterization

Holmqvist, Isak (author)
Gothenburg University,Göteborgs universitet,Institutionen för biomedicin, avdelningen för infektionssjukdomar,Institute of Biomedicine, Department of Infectious Medicine
Bäckerholm, Alan (author)
Gothenburg University,Göteborgs universitet,Institutionen för biomedicin, avdelningen för infektionssjukdomar,Institute of Biomedicine, Department of Infectious Medicine
Tian, Yarong, 1989 (author)
Gothenburg University,Göteborgs universitet,Institutionen för biomedicin, avdelningen för infektionssjukdomar,Institute of Biomedicine, Department of Infectious Medicine
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Xie, Guojiang (author)
Gothenburg University,Göteborgs universitet,Institutionen för biomedicin, avdelningen för infektionssjukdomar,Institute of Biomedicine, Department of Infectious Medicine
Thorell, Kaisa, 1983 (author)
Gothenburg University,Göteborgs universitet,Institutionen för biomedicin, avdelningen för infektionssjukdomar,Institute of Biomedicine, Department of Infectious Medicine
Tang, Ka-Wei, 1983 (author)
Gothenburg University,Göteborgs universitet,Institutionen för biomedicin, avdelningen för infektionssjukdomar,Wallenberg Centre for Molecular and Translational Medicine,Institute of Biomedicine, Department of Infectious Medicine
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 (creator_code:org_t)
2021-07-12
2021
English.
In: Rna. - : Cold Spring Harbor Laboratory. - 1355-8382 .- 1469-9001. ; 27:10, s. 1127-1139
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Comprehensive characterization of differentially spliced RNA transcripts with nanopore sequencing is limited by bioinformatics tools that are reliant on existing annotations. We have developed FLAME, a bioinformatics pipeline for alternative splicing analysis of gene-specific or transcriptome-wide long-read sequencing data. FLAME is a Python-based tool aimed at providing comprehensible quantification of full-length splice variants, reliable de novo recognition of splice sites and exons, and representation of consecutive exon connectivity in the form of a weighted adjacency matrix. Notably, this work-flow circumvents issues related to inadequate reference annotations and allows for incorporation of short-read sequencing data to improve the confidence of nanopore sequencing reads. In this study, the Epstein-Barr virus long noncoding RNA RPMS1 was used to demonstrate the utility of the pipeline. RPMS1 is ubiquitously expressed in Epstein-Barr virus associated cancer and known to undergo ample differential splicing. To fully resolve the RPMS1 spliceome, we combined gene-specific nanopore sequencing reads from a primary gastric adenocarcinoma and a nasopharyngeal carcinoma cell line with matched publicly available short-read sequencing data sets. All previously reported splice variants, including putative ORFs, were detected using FLAME. In addition, 32 novel exons, including two intron retentions and a cassette exon, were discovered within the RPMS1 gene.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Medicinska och farmaceutiska grundvetenskaper -- Cell- och molekylärbiologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Basic Medicine -- Cell and Molecular Biology (hsv//eng)

Keyword

bioinformatics
Epstein-Barr virus
RNA splicing
RPMS1
barr-virus bamhi
alternative splicing complexity
a rightward
transcripts
gene-expression
rnas
Biochemistry & Molecular Biology

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art (subject category)

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