A general framework for predicting the transcriptomic consequences of non-coding variation

Moustafa Abdalla; Mohamed Abdalla; Mark I. McCarthy; Chris C. Holmes

doi:10.1101/279323

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A general framework for predicting the transcriptomic consequences of non-coding variation

Moustafa Abdalla, Mohamed Abdalla, Mark I. McCarthy, Chris C. Holmes

doi: https://doi.org/10.1101/279323

Moustafa Abdalla

1Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, United Kingdom

2Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, United Kingdom

3Computational Statistics and Machine Learning, Department of Statistics, University of Oxford, United Kingdom

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Mohamed Abdalla

4Department of Computer Science, University of Toronto, Canada

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Mark I. McCarthy

1Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, United Kingdom

2Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, United Kingdom

5Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, United Kingdom

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For correspondence: mark.mccarthy@drl.ox.ac.uk cholmes@stats.ox.ac.uk

Chris C. Holmes

1Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, United Kingdom

3Computational Statistics and Machine Learning, Department of Statistics, University of Oxford, United Kingdom

6Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, United Kingdom

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For correspondence: mark.mccarthy@drl.ox.ac.uk cholmes@stats.ox.ac.uk

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Posted March 10, 2018.

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A general framework for predicting the transcriptomic consequences of non-coding variation

Moustafa Abdalla, Mohamed Abdalla, Mark I. McCarthy, Chris C. Holmes

bioRxiv 279323; doi: https://doi.org/10.1101/279323

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A general framework for predicting the transcriptomic consequences of non-coding variation

Moustafa Abdalla, Mohamed Abdalla, Mark I. McCarthy, Chris C. Holmes

bioRxiv 279323; doi: https://doi.org/10.1101/279323

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