FusionSeq: A modular framework for finding gene fusions by analyzing paired-end RNA-sequencing data

Andrea Sboner; Lukas Habegger; Dorothee Pflueger; Stephane Terry; David Z. Chen; Joel S. Rozowsky; Ashutosh K. Tewari; Naoki Kitabayashi; Benjamin J. Moss; Mark S. Chee; Francesca Demichelis; Mark A. Rubin; Mark B. Gerstein

doi:10.1186/gb-2010-11-10-r104

FusionSeq: A modular framework for finding gene fusions by analyzing paired-end RNA-sequencing data

Andrea Sboner
, Lukas Habegger
, Dorothee Pflueger
, Stephane Terry
, David Z. Chen
, Joel S. Rozowsky
, Ashutosh K. Tewari
, Naoki Kitabayashi
, Benjamin J. Moss
, Mark S. Chee
, Francesca Demichelis
, Mark A. Rubin
, Mark B. Gerstein

Research output: Contribution to journal › Article › peer-review

136 Scopus citations

Abstract

We have developed FusionSeq to identify fusion transcripts from paired-end RNA-sequencing. FusionSeq includes filters to remove spurious candidate fusions with artifacts, such as misalignment or random pairing of transcript fragments, and it ranks candidates according to several statistics. It also has a module to identify exact sequences at breakpoint junctions. FusionSeq detected known and novel fusions in a specially sequenced calibration data set, including eight cancers with and without known rearrangements.

Original language	English
Article number	R104
Journal	Genome Biology
Volume	11
Issue number	10
DOIs	https://doi.org/10.1186/gb-2010-11-10-r104
State	Published - 21 Oct 2010
Externally published	Yes

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10.1186/gb-2010-11-10-r104

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Sboner, A., Habegger, L., Pflueger, D., Terry, S., Chen, D. Z., Rozowsky, J. S., Tewari, A. K., Kitabayashi, N., Moss, B. J., Chee, M. S., Demichelis, F., Rubin, M. A., & Gerstein, M. B. (2010). FusionSeq: A modular framework for finding gene fusions by analyzing paired-end RNA-sequencing data. Genome Biology, 11(10), Article R104. https://doi.org/10.1186/gb-2010-11-10-r104

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title = "FusionSeq: A modular framework for finding gene fusions by analyzing paired-end RNA-sequencing data",

abstract = "We have developed FusionSeq to identify fusion transcripts from paired-end RNA-sequencing. FusionSeq includes filters to remove spurious candidate fusions with artifacts, such as misalignment or random pairing of transcript fragments, and it ranks candidates according to several statistics. It also has a module to identify exact sequences at breakpoint junctions. FusionSeq detected known and novel fusions in a specially sequenced calibration data set, including eight cancers with and without known rearrangements.",

author = "Andrea Sboner and Lukas Habegger and Dorothee Pflueger and Stephane Terry and Chen, \{David Z.\} and Rozowsky, \{Joel S.\} and Tewari, \{Ashutosh K.\} and Naoki Kitabayashi and Moss, \{Benjamin J.\} and Chee, \{Mark S.\} and Francesca Demichelis and Rubin, \{Mark A.\} and Gerstein, \{Mark B.\}",

note = "Funding Information: We would like to acknowledge the support of the {\textquoteleft}Yale University Biomedical High Performance Computing Center{\textquoteright} and NIH grant no. RR19895, which funded the computer cluster instrumentation where the analysis has been performed, National Cancer Institute grant R01CA125612 to MAR and FD, National Human Genome Research Institute grant 5R44HG004237 to MC, the Prostate Cancer Foundation, and the Breslin Foundation.",

year = "2010",

month = oct,

day = "21",

doi = "10.1186/gb-2010-11-10-r104",

language = "English",

volume = "11",

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T2 - A modular framework for finding gene fusions by analyzing paired-end RNA-sequencing data

AU - Sboner, Andrea

AU - Habegger, Lukas

AU - Pflueger, Dorothee

AU - Terry, Stephane

AU - Chen, David Z.

AU - Rozowsky, Joel S.

AU - Tewari, Ashutosh K.

AU - Kitabayashi, Naoki

AU - Moss, Benjamin J.

AU - Chee, Mark S.

AU - Demichelis, Francesca

AU - Rubin, Mark A.

AU - Gerstein, Mark B.

N1 - Funding Information: We would like to acknowledge the support of the ‘Yale University Biomedical High Performance Computing Center’ and NIH grant no. RR19895, which funded the computer cluster instrumentation where the analysis has been performed, National Cancer Institute grant R01CA125612 to MAR and FD, National Human Genome Research Institute grant 5R44HG004237 to MC, the Prostate Cancer Foundation, and the Breslin Foundation.

PY - 2010/10/21

Y1 - 2010/10/21

N2 - We have developed FusionSeq to identify fusion transcripts from paired-end RNA-sequencing. FusionSeq includes filters to remove spurious candidate fusions with artifacts, such as misalignment or random pairing of transcript fragments, and it ranks candidates according to several statistics. It also has a module to identify exact sequences at breakpoint junctions. FusionSeq detected known and novel fusions in a specially sequenced calibration data set, including eight cancers with and without known rearrangements.

AB - We have developed FusionSeq to identify fusion transcripts from paired-end RNA-sequencing. FusionSeq includes filters to remove spurious candidate fusions with artifacts, such as misalignment or random pairing of transcript fragments, and it ranks candidates according to several statistics. It also has a module to identify exact sequences at breakpoint junctions. FusionSeq detected known and novel fusions in a specially sequenced calibration data set, including eight cancers with and without known rearrangements.

UR - https://www.scopus.com/pages/publications/77958040520

U2 - 10.1186/gb-2010-11-10-r104

DO - 10.1186/gb-2010-11-10-r104

M3 - Article

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AN - SCOPUS:77958040520

SN - 1474-7596

VL - 11

JO - Genome Biology

JF - Genome Biology

IS - 10

M1 - R104

ER -

FusionSeq: A modular framework for finding gene fusions by analyzing paired-end RNA-sequencing data

Abstract

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