BRIE: transcriptome-wide splicing quantication in single cells
- Submitting institution
-
University of Edinburgh
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 58517795
- Type
- D - Journal article
- DOI
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10.1186/s13059-017-1248-5
- Title of journal
- Genome Biology
- Article number
- 123
- First page
- -
- Volume
- 18
- Issue
- -
- ISSN
- 1465-6906
- Open access status
- Compliant
- Month of publication
- June
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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1
- Research group(s)
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B - Data Science and Artificial Intelligence
- Citation count
- 24
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper presented the first method to quantify splicing from single cell RNA-seq measurements of gene expression by using a latent variable model to integrate genetic sequence and gene expression data. The work was presented as a poster at the premier conference HiTSeq, where it won the Best Poster Award, and resulted in the invitation to present it at international workshops in Munich and Montpellier. The method has been subsequently independently used by groups in Sweden, Cambridge and Harvard (papers recently published in Nature Medicine, Genome Biology and Nature Communications, respectively).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -