@inproceedings{0efb8d261f0d4b25ba1dd0efe13bbcd6,
title = "Predicting the Pathogenic Impact of Sequence Variation in the Human Genome",
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, sequence data, variant, annotation, point mutation, indel",
author = "Rogers, {Mark F} and Shihab, {Hashem A} and Michael Ferlaino and Gaunt, {Tom R} and Campbell, {Colin K}",
year = "2017",
month = may,
day = "17",
doi = "10.3233/978-1-61499-753-5-91",
language = "English",
isbn = "9781614997528",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press",
pages = "91--95",
editor = "Rebecca Randell and Ronald Cornet and Colin McCowan and Niels Peek and Scott, {Philip J}",
booktitle = "Informatics for Health",
address = "Netherlands",
note = "Informatics for Health 2017 ; Conference date: 24-04-2017 Through 26-04-2017",
}