Detecting differential usage of exons from RNA-seq data
RNA-seq is a powerful tool for the study of alternative splicing and other forms of alternative isoform expression. Understanding the regulation of these processes requires sensitive and specific detection of differential isoform abundance in comparisons between conditions, cell types, or tissues. W...
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| Published in | Genome research Vol. 22; no. 10; pp. 2008 - 2017 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Cold Spring Harbor Laboratory Press
01.10.2012
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| Subjects | |
| Online Access | Get full text |
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| Abstract | RNA-seq is a powerful tool for the study of alternative splicing and other forms of alternative isoform expression. Understanding the regulation of these processes requires sensitive and specific detection of differential isoform abundance in comparisons between conditions, cell types, or tissues. We present
DEXSeq
, a statistical method to test for differential exon usage in RNA-seq data.
DEXSeq
uses generalized linear models and offers reliable control of false discoveries by taking biological variation into account.
DEXSeq
detects with high sensitivity genes, and in many cases exons, that are subject to differential exon usage. We demonstrate the versatility of
DEXSeq
by applying it to several data sets. The method facilitates the study of regulation and function of alternative exon usage on a genome-wide scale. An implementation of
DEXSeq
is available as an R/Bioconductor package. |
|---|---|
| AbstractList | RNA-seq is a powerful tool for the study of alternative splicing and other forms of alternative isoform expression. Understanding the regulation of these processes requires sensitive and specific detection of differential isoform abundance in comparisons between conditions, cell types, or tissues. We present
DEXSeq
, a statistical method to test for differential exon usage in RNA-seq data.
DEXSeq
uses generalized linear models and offers reliable control of false discoveries by taking biological variation into account.
DEXSeq
detects with high sensitivity genes, and in many cases exons, that are subject to differential exon usage. We demonstrate the versatility of
DEXSeq
by applying it to several data sets. The method facilitates the study of regulation and function of alternative exon usage on a genome-wide scale. An implementation of
DEXSeq
is available as an R/Bioconductor package. RNA-seq is a powerful tool for the study of alternative splicing and other forms of alternative isoform expression. Understanding the regulation of these processes requires sensitive and specific detection of differential isoform abundance in comparisons between conditions, cell types, or tissues. We present DEXSeq, a statistical method to test for differential exon usage in RNA-seq data. DEXSeq uses generalized linear models and offers reliable control of false discoveries by taking biological variation into account. DEXSeq detects with high sensitivity genes, and in many cases exons, that are subject to differential exon usage. We demonstrate the versatility of DEXSeq by applying it to several data sets. The method facilitates the study of regulation and function of alternative exon usage on a genome-wide scale. An implementation of DEXSeq is available as an R/Bioconductor package. RNA-seq is a powerful tool for the study of alternative splicing and other forms of alternative isoform expression. Understanding the regulation of these processes requires sensitive and specific detection of differential isoform abundance in comparisons between conditions, cell types, or tissues. We present DEXSeq, a statistical method to test for differential exon usage in RNA-seq data. DEXSeq uses generalized linear models and offers reliable control of false discoveries by taking biological variation into account. DEXSeq detects with high sensitivity genes, and in many cases exons, that are subject to differential exon usage. We demonstrate the versatility of DEXSeq by applying it to several data sets. The method facilitates the study of regulation and function of alternative exon usage on a genome-wide scale. An implementation of DEXSeq is available as an R/Bioconductor package.RNA-seq is a powerful tool for the study of alternative splicing and other forms of alternative isoform expression. Understanding the regulation of these processes requires sensitive and specific detection of differential isoform abundance in comparisons between conditions, cell types, or tissues. We present DEXSeq, a statistical method to test for differential exon usage in RNA-seq data. DEXSeq uses generalized linear models and offers reliable control of false discoveries by taking biological variation into account. DEXSeq detects with high sensitivity genes, and in many cases exons, that are subject to differential exon usage. We demonstrate the versatility of DEXSeq by applying it to several data sets. The method facilitates the study of regulation and function of alternative exon usage on a genome-wide scale. An implementation of DEXSeq is available as an R/Bioconductor package. |
| Author | Anders, Simon Huber, Wolfgang Reyes, Alejandro |
| AuthorAffiliation | European Molecular Biology Laboratory, 69111 Heidelberg, Germany |
| AuthorAffiliation_xml | – name: European Molecular Biology Laboratory, 69111 Heidelberg, Germany |
| Author_xml | – sequence: 1 givenname: Simon surname: Anders fullname: Anders, Simon – sequence: 2 givenname: Alejandro surname: Reyes fullname: Reyes, Alejandro – sequence: 3 givenname: Wolfgang surname: Huber fullname: Huber, Wolfgang |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/22722343$$D View this record in MEDLINE/PubMed |
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| Snippet | RNA-seq is a powerful tool for the study of alternative splicing and other forms of alternative isoform expression. Understanding the regulation of these... |
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| SubjectTerms | Algorithms Alternative Splicing Animals Cell Line Computational Biology - methods Databases, Nucleic Acid Exons Genomics - methods Humans Method Models, Genetic Pan troglodytes - genetics RNA - chemistry RNA - genetics |
| Title | Detecting differential usage of exons from RNA-seq data |
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