Journal article

Choice of transcripts and software has a large effect on variant annotation

Davis J McCarthy, Peter Humburg, Alexander Kanapin, Manuel A Rivas, Kyle Gaulton, Jean-Baptiste Cazier, Peter Donnelly

GENOME MEDICINE | BMC | Published : 2014

Abstract

BACKGROUND: Variant annotation is a crucial step in the analysis of genome sequencing data. Functional annotation results can have a strong influence on the ultimate conclusions of disease studies. Incorrect or incomplete annotations can cause researchers both to overlook potentially disease-relevant DNA variants and to dilute interesting variants in a pool of false positives. Researchers are aware of these issues in general, but the extent of the dependency of final results on the choice of transcripts and software used for annotation has not been quantified in detail. METHODS: This paper quantifies the extent of differences in annotation of 80 million variants from a whole-genome sequencin..

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University of Melbourne Researchers

Grants

Awarded by Wellcome Trust for the Wellcome Trust Centre for Human Genetics


Awarded by Wellcome Trust


Funding Acknowledgements

The authors wish to thank the patients and their families for participating in this study. We are also grateful to Alistair Pagnamenta for helpful discussions and suggestions to improve the analysis and manuscript, and Gil McVean and Jenny Taylor for their comments on an earlier version of the manuscript. This work was supported by a Wellcome Trust Core Grant for the Wellcome Trust Centre for Human Genetics (090532/Z/09/Z). PD is supported by a Wellcome Trust Senior Investigator Award (095552/Z/11/Z). DJM is supported by a General Sir John Monash Scholarship from the General Sir John Monash Foundation, Australia. MAR is funded by a Clarendon Scholarship, NDM Studentship and Green Templeton College Award from the University of Oxford.