Barnacle: detecting and characterizing tandem duplications and fusions in transcriptome assemblies
Background: Chimeric transcripts, including partial and internal tandem duplications (PTDs, ITDs) and gene fusions, are important in the detection, prognosis, and treatment of human cancers. Results: We describe Barnacle, a production-grade analysis tool that detects such chimeras in de novo asse...
Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
BioMed Central Ltd.
2013
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Online Access: | http://hdl.handle.net/1721.1/81361 https://orcid.org/0000-0003-2315-0768 |
Summary: | Background:
Chimeric transcripts, including partial and internal tandem duplications (PTDs, ITDs) and gene fusions, are important in the detection, prognosis, and treatment of human cancers.
Results:
We describe Barnacle, a production-grade analysis tool that detects such chimeras in de novo assemblies of RNA-seq data, and supports prioritizing them for review and validation by reporting the relative coverage of co-occurring chimeric and wild-type transcripts. We demonstrate applications in large-scale disease studies, by identifying PTDs in MLL, ITDs in FLT3, and reciprocal fusions between PML and RARA, in two deeply sequenced acute myeloid leukemia (AML) RNA-seq datasets.
Conclusions:
Our analyses of real and simulated data sets show that, with appropriate filter settings, Barnacle makes highly specific predictions for three types of chimeric transcripts that are important in a range of cancers: PTDs, ITDs, and fusions. High specificity makes manual review and validation efficient, which is necessary in large-scale disease studies. Characterizing an extended range of chimera types will help generate insights into progression, treatment, and outcomes for complex diseases. |
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