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Predicting the Pathogenic Impact of Sequence Variation in the Human Genome.

Author information

1
Intelligent Systems Laboratory, University of Bristol, Bristol, BS8 1UB, U.K.
2
MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, BS8 2BN, U.K.
3
Nuffield Department of Obstetrics and Gynaecology, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, U.K.

Abstract

Sequencing data will become widely available in clinical practice within the near future. Uptake of sequence data is currently being stimulated within the UK through the government-funded 100,000 genomes project (Genomics England), with many similar initiatives being planned and supported internationally. The analysis of the large volumes of data derived from sequencing programmes poses a major challenge for data analysis. In this paper we outline progress we have made in the development of predictors for estimating the pathogenic impact of single nucleotide variants, indels and haploinsufficiency in the human genome. The accuracy of these methods is enhanced through the development of disease-specific predictors, trained on appropriate data, and used within a specific disease context. We outline current research on the development of disease-specific predictors, specifically in the context of cancer research.

KEYWORDS:

Prediction; annotation; indel; point mutation; sequence data; variant

PMID:
28423762
[Indexed for MEDLINE]

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