ChimeRScope: a novel alignment-free algorithm for fusion transcript prediction using paired-end RNA-Seq data
Identifieur interne : 000E63 ( Main/Exploration ); précédent : 000E62; suivant : 000E64ChimeRScope: a novel alignment-free algorithm for fusion transcript prediction using paired-end RNA-Seq data
Auteurs : You Li [États-Unis, République populaire de Chine] ; Tayla B. Heavican [États-Unis] ; Neetha N. Vellichirammal [États-Unis] ; Javeed Iqbal [États-Unis] ; Chittibabu Guda [États-Unis]Source :
- Nucleic Acids Research [ 0305-1048 ] ; 2017.
Descripteurs français
- KwdFr :
- ARN (génétique), Algorithmes, Alignement de séquences (), Analyse de profil d'expression de gènes (), Analyse de séquence d'ARN (), Bases de données d'acides nucléiques (), Cellules tueuses naturelles (métabolisme), Fusion oncogène, Humains, Lignée cellulaire, Logiciel, Simulation numérique, Séquençage nucléotidique à haut débit (), Transcriptome.
- MESH :
- génétique : ARN.
- métabolisme : Cellules tueuses naturelles.
- Algorithmes, Alignement de séquences, Analyse de profil d'expression de gènes, Analyse de séquence d'ARN, Bases de données d'acides nucléiques, Fusion oncogène, Humains, Lignée cellulaire, Logiciel, Simulation numérique, Séquençage nucléotidique à haut débit, Transcriptome.
English descriptors
- KwdEn :
- Algorithms, Cell Line, Computer Simulation, Databases, Nucleic Acid (statistics & numerical data), Gene Expression Profiling (statistics & numerical data), High-Throughput Nucleotide Sequencing (statistics & numerical data), Humans, Killer Cells, Natural (metabolism), Oncogene Fusion, RNA (genetics), Sequence Alignment (statistics & numerical data), Sequence Analysis, RNA (statistics & numerical data), Software, Transcriptome.
- MESH :
- chemical , genetics : RNA.
- metabolism : Killer Cells, Natural.
- statistics & numerical data : Databases, Nucleic Acid, Gene Expression Profiling, High-Throughput Nucleotide Sequencing, Sequence Alignment, Sequence Analysis, RNA.
- Algorithms, Cell Line, Computer Simulation, Humans, Oncogene Fusion, Software, Transcriptome.
Abstract
The RNA-Seq technology has revolutionized transcriptome characterization not only by accurately quantifying gene expression, but also by the identification of novel transcripts like chimeric fusion transcripts. The ‘fusion’ or ‘chimeric’ transcripts have improved the diagnosis and prognosis of several tumors, and have led to the development of novel therapeutic regimen. The fusion transcript detection is currently accomplished by several software packages, primarily relying on sequence alignment algorithms. The alignment of sequencing reads from fusion transcript loci in cancer genomes can be highly challenging due to the incorrect mapping induced by genomic alterations, thereby limiting the performance of alignment-based fusion transcript detection methods. Here, we developed a novel alignment-free method, ChimeRScope that accurately predicts fusion transcripts based on the gene fingerprint (as
Url:
DOI: 10.1093/nar/gkx315
PubMed: 28472320
PubMed Central: 5737728
Affiliations:
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Le document en format XML
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Li</name><affiliation wicri:level="2"><nlm:aff id="AFF1">Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198</wicri:regionArea><placeName><region type="state">Nebraska</region></placeName></affiliation><affiliation wicri:level="1"><nlm:aff id="AFF2">The Sichuan Key Laboratory for Human Disease Gene Study, Clinical Laboratory Department, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Chengdu, Sichuan 610072, China</nlm:aff><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>The Sichuan Key Laboratory for Human Disease Gene Study, Clinical Laboratory Department, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Chengdu, Sichuan 610072</wicri:regionArea><wicri:noRegion>Sichuan 610072</wicri:noRegion></affiliation><affiliation wicri:level="1"><nlm:aff id="AFF3">School of Medicine, University of Electronic Science and Technology, Chengdu, Sichuan 610054, China</nlm:aff><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Medicine, University of Electronic Science and Technology, Chengdu, Sichuan 610054</wicri:regionArea><wicri:noRegion>Sichuan 610054</wicri:noRegion></affiliation></author><author><name sortKey="Heavican, Tayla B" sort="Heavican, Tayla B" uniqKey="Heavican T" first="Tayla B." last="Heavican">Tayla B. Heavican</name><affiliation wicri:level="2"><nlm:aff id="AFF4">Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE 68198, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE 68198</wicri:regionArea><placeName><region type="state">Nebraska</region></placeName></affiliation></author><author><name sortKey="Vellichirammal, Neetha N" sort="Vellichirammal, Neetha N" uniqKey="Vellichirammal N" first="Neetha N." last="Vellichirammal">Neetha N. Vellichirammal</name><affiliation wicri:level="2"><nlm:aff id="AFF1">Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198</wicri:regionArea><placeName><region type="state">Nebraska</region></placeName></affiliation></author><author><name sortKey="Iqbal, Javeed" sort="Iqbal, Javeed" uniqKey="Iqbal J" first="Javeed" last="Iqbal">Javeed Iqbal</name><affiliation wicri:level="2"><nlm:aff id="AFF4">Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE 68198, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE 68198</wicri:regionArea><placeName><region type="state">Nebraska</region></placeName></affiliation></author><author><name sortKey="Guda, Chittibabu" sort="Guda, Chittibabu" uniqKey="Guda C" first="Chittibabu" last="Guda">Chittibabu Guda</name><affiliation wicri:level="2"><nlm:aff id="AFF1">Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE 68198</wicri:regionArea><placeName><region type="state">Nebraska</region></placeName></affiliation><affiliation wicri:level="2"><nlm:aff id="AFF5">Bioinformatics and System Biology Core, University of Nebraska Medical Center, Omaha, NE 68198, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Bioinformatics and System Biology Core, University of Nebraska Medical Center, Omaha, NE 68198</wicri:regionArea><placeName><region type="state">Nebraska</region></placeName></affiliation></author></analytic><series><title level="j">Nucleic Acids Research</title><idno type="ISSN">0305-1048</idno><idno type="eISSN">1362-4962</idno><imprint><date when="2017">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>Cell Line</term><term>Computer Simulation</term><term>Databases, Nucleic Acid (statistics & numerical data)</term><term>Gene Expression Profiling (statistics & numerical data)</term><term>High-Throughput Nucleotide Sequencing (statistics & numerical data)</term><term>Humans</term><term>Killer Cells, Natural (metabolism)</term><term>Oncogene Fusion</term><term>RNA (genetics)</term><term>Sequence Alignment (statistics & numerical data)</term><term>Sequence Analysis, RNA (statistics & numerical data)</term><term>Software</term><term>Transcriptome</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>ARN (génétique)</term><term>Algorithmes</term><term>Alignement de séquences ()</term><term>Analyse de profil d'expression de gènes ()</term><term>Analyse de séquence d'ARN ()</term><term>Bases de données d'acides nucléiques ()</term><term>Cellules tueuses naturelles (métabolisme)</term><term>Fusion oncogène</term><term>Humains</term><term>Lignée cellulaire</term><term>Logiciel</term><term>Simulation numérique</term><term>Séquençage nucléotidique à haut débit ()</term><term>Transcriptome</term></keywords><keywords scheme="MESH" type="chemical" qualifier="genetics" xml:lang="en"><term>RNA</term></keywords><keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>ARN</term></keywords><keywords scheme="MESH" qualifier="metabolism" xml:lang="en"><term>Killer Cells, Natural</term></keywords><keywords scheme="MESH" qualifier="métabolisme" xml:lang="fr"><term>Cellules tueuses naturelles</term></keywords><keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>Databases, Nucleic Acid</term><term>Gene Expression Profiling</term><term>High-Throughput Nucleotide Sequencing</term><term>Sequence Alignment</term><term>Sequence Analysis, RNA</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Cell Line</term><term>Computer Simulation</term><term>Humans</term><term>Oncogene Fusion</term><term>Software</term><term>Transcriptome</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Algorithmes</term><term>Alignement de séquences</term><term>Analyse de profil d'expression de gènes</term><term>Analyse de séquence d'ARN</term><term>Bases de données d'acides nucléiques</term><term>Fusion oncogène</term><term>Humains</term><term>Lignée cellulaire</term><term>Logiciel</term><term>Simulation numérique</term><term>Séquençage nucléotidique à haut débit</term><term>Transcriptome</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><title>Abstract</title><p>The RNA-Seq technology has revolutionized transcriptome characterization not only by accurately quantifying gene expression, but also by the identification of novel transcripts like chimeric fusion transcripts. The ‘fusion’ or ‘chimeric’ transcripts have improved the diagnosis and prognosis of several tumors, and have led to the development of novel therapeutic regimen. The fusion transcript detection is currently accomplished by several software packages, primarily relying on sequence alignment algorithms. The alignment of sequencing reads from fusion transcript loci in cancer genomes can be highly challenging due to the incorrect mapping induced by genomic alterations, thereby limiting the performance of alignment-based fusion transcript detection methods. Here, we developed a novel alignment-free method, ChimeRScope that accurately predicts fusion transcripts based on the gene fingerprint (as <italic>k</italic>-mers) profiles of the RNA-Seq paired-end reads. Results on published datasets and in-house cancer cell line datasets followed by experimental validations demonstrate that ChimeRScope consistently outperforms other popular methods irrespective of the read lengths and sequencing depth. More importantly, results on our in-house datasets show that ChimeRScope is a better tool that is capable of identifying novel fusion transcripts with potential oncogenic functions. ChimeRScope is accessible as a standalone software at (<ext-link ext-link-type="uri" xlink:href="https://github.com/ChimeRScope/ChimeRScope/wiki">https://github.com/ChimeRScope/ChimeRScope/wiki</ext-link>) or via the Galaxy web-interface at (<ext-link ext-link-type="uri" xlink:href="https://galaxy.unmc.edu/">https://galaxy.unmc.edu/</ext-link>).</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Mitelman, F" uniqKey="Mitelman F">F. Mitelman</name></author><author><name sortKey="Johansson, B" uniqKey="Johansson B">B. 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Heavican</name><name sortKey="Iqbal, Javeed" sort="Iqbal, Javeed" uniqKey="Iqbal J" first="Javeed" last="Iqbal">Javeed Iqbal</name><name sortKey="Vellichirammal, Neetha N" sort="Vellichirammal, Neetha N" uniqKey="Vellichirammal N" first="Neetha N." last="Vellichirammal">Neetha N. Vellichirammal</name></country><country name="République populaire de Chine"><noRegion><name sortKey="Li, You" sort="Li, You" uniqKey="Li Y" first="You" last="Li">You Li</name></noRegion><name sortKey="Li, You" sort="Li, You" uniqKey="Li Y" first="You" last="Li">You Li</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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