Working toward precision medicine: Predicting phenotypes from exomes in the Critical Assessment of Genome Interpretation (CAGI) challenges. Issue 9 (7th July 2017)
- Record Type:
- Journal Article
- Title:
- Working toward precision medicine: Predicting phenotypes from exomes in the Critical Assessment of Genome Interpretation (CAGI) challenges. Issue 9 (7th July 2017)
- Main Title:
- Working toward precision medicine: Predicting phenotypes from exomes in the Critical Assessment of Genome Interpretation (CAGI) challenges
- Authors:
- Daneshjou, Roxana
Wang, Yanran
Bromberg, Yana
Bovo, Samuele
Martelli, Pier L
Babbi, Giulia
Lena, Pietro Di
Casadio, Rita
Edwards, Matthew
Gifford, David
Jones, David T
Sundaram, Laksshman
Bhat, Rajendra Rana
Li, Xiaolin
Pal, Lipika R.
Kundu, Kunal
Yin, Yizhou
Moult, John
Jiang, Yuxiang
Pejaver, Vikas
Pagel, Kymberleigh A.
Li, Biao
Mooney, Sean D.
Radivojac, Predrag
Shah, Sohela
Carraro, Marco
Gasparini, Alessandra
Leonardi, Emanuela
Giollo, Manuel
Ferrari, Carlo
Tosatto, Silvio C E
Bachar, Eran
Azaria, Johnathan R.
Ofran, Yanay
Unger, Ron
Niroula, Abhishek
Vihinen, Mauno
Chang, Billy
Wang, Maggie H
Franke, Andre
Petersen, Britt‐Sabina
Pirooznia, Mehdi
Zandi, Peter
McCombie, Richard
Potash, James B.
Altman, Russ B.
Klein, Teri E.
Hoskins, Roger A.
Repo, Susanna
Brenner, Steven E.
Morgan, Alexander A.
… (more) - Abstract:
- Abstract : The Critical Assessment of Genome Interpretation (CAGI) is a community experiment consisting of genotype‐phenotype prediction challenges; participants build models, undergo assessment, and share key findings. For CAGI 4, three challenges involved using exome sequencing data: Crohn's disease, bipolar disorder, and warfarin dosing. We discuss the range of techniques used for phenotype prediction, the methods used for assessing predictive models, and the lessons gleaned from the CAGI exomes challenges. Abstract: Precision medicine aims to predict a patient's disease risk and best therapeutic options by using that individual's genetic sequencing data. The Critical Assessment of Genome Interpretation (CAGI) is a community experiment consisting of genotype–phenotype prediction challenges; participants build models, undergo assessment, and share key findings. For CAGI 4, three challenges involved using exome‐sequencing data: Crohn's disease, bipolar disorder, and warfarin dosing. Previous CAGI challenges included prior versions of the Crohn's disease challenge. Here, we discuss the range of techniques used for phenotype prediction as well as the methods used for assessing predictive models. Additionally, we outline some of the difficulties associated with making predictions and evaluating them. The lessons learned from the exome challenges can be applied to both research and clinical efforts to improve phenotype prediction from genotype. In addition, these challengesAbstract : The Critical Assessment of Genome Interpretation (CAGI) is a community experiment consisting of genotype‐phenotype prediction challenges; participants build models, undergo assessment, and share key findings. For CAGI 4, three challenges involved using exome sequencing data: Crohn's disease, bipolar disorder, and warfarin dosing. We discuss the range of techniques used for phenotype prediction, the methods used for assessing predictive models, and the lessons gleaned from the CAGI exomes challenges. Abstract: Precision medicine aims to predict a patient's disease risk and best therapeutic options by using that individual's genetic sequencing data. The Critical Assessment of Genome Interpretation (CAGI) is a community experiment consisting of genotype–phenotype prediction challenges; participants build models, undergo assessment, and share key findings. For CAGI 4, three challenges involved using exome‐sequencing data: Crohn's disease, bipolar disorder, and warfarin dosing. Previous CAGI challenges included prior versions of the Crohn's disease challenge. Here, we discuss the range of techniques used for phenotype prediction as well as the methods used for assessing predictive models. Additionally, we outline some of the difficulties associated with making predictions and evaluating them. The lessons learned from the exome challenges can be applied to both research and clinical efforts to improve phenotype prediction from genotype. In addition, these challenges serve as a vehicle for sharing clinical and research exome data in a secure manner with scientists who have a broad range of expertise, contributing to a collaborative effort to advance our understanding of genotype–phenotype relationships. … (more)
- Is Part Of:
- Human mutation. Volume 38:Issue 9(2017)
- Journal:
- Human mutation
- Issue:
- Volume 38:Issue 9(2017)
- Issue Display:
- Volume 38, Issue 9 (2017)
- Year:
- 2017
- Volume:
- 38
- Issue:
- 9
- Issue Sort Value:
- 2017-0038-0009-0000
- Page Start:
- 1182
- Page End:
- 1192
- Publication Date:
- 2017-07-07
- Subjects:
- bipolar disorder -- Crohn's disease -- exomes -- machine learning -- phenotype prediction -- warfarin
Human chromosome abnormalities -- Periodicals
Mutation (Biology) -- Periodicals
616.04205 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1098-1004 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/humu.23280 ↗
- Languages:
- English
- ISSNs:
- 1059-7794
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4336.217000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14205.xml