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Literature DB >> 24287332

Network analysis of GWAS data.

Mark D M Leiserson¹, Jonathan V Eldridge, Sohini Ramachandran, Benjamin J Raphael.

Abstract

Genome-wide association studies (GWAS) identify genetic variants that distinguish a control population from a population with a specific trait. Two challenges in GWAS are: (1) identification of the causal variant within a longer haplotype that is associated with the trait; (2) identification of causal variants for polygenic traits that are caused by variants in multiple genes within a pathway. We review recent methods that use information in protein-protein and protein-DNA interaction networks to address these two challenges.

Entities: Disease Gene Species

Mesh：

Year: 2013 PMID： 24287332 PMCID： PMC3867794 DOI： 10.1016/j.gde.2013.09.003

Source DB: PubMed Journal: Curr Opin Genet Dev ISSN： 0959-437X Impact factor: 5.578

53 in total

1. Methods for detecting associations with rare variants for common diseases: application to analysis of sequence data.

Authors: Bingshan Li; Suzanne M Leal
Journal: Am J Hum Genet Date: 2008-08-07 Impact factor: 11.025

2. Align human interactome with phenome to identify causative genes and networks underlying disease families.

Authors: Xuebing Wu; Qifang Liu; Rui Jiang
Journal: Bioinformatics Date: 2008-11-13 Impact factor: 6.937

Review 3. Genome-wide association studies for complex traits: consensus, uncertainty and challenges.

Authors: Mark I McCarthy; Gonçalo R Abecasis; Lon R Cardon; David B Goldstein; Julian Little; John P A Ioannidis; Joel N Hirschhorn
Journal: Nat Rev Genet Date: 2008-05 Impact factor: 53.242

4. Variants in exons and in transcription factors affect gene expression in trans.

Authors: Anat Kreimer; Itsik Pe'er
Journal: Genome Biol Date: 2013-07-11 Impact factor: 13.583

5. Human Protein Reference Database--2009 update.

Authors: T S Keshava Prasad; Renu Goel; Kumaran Kandasamy; Shivakumar Keerthikumar; Sameer Kumar; Suresh Mathivanan; Deepthi Telikicherla; Rajesh Raju; Beema Shafreen; Abhilash Venugopal; Lavanya Balakrishnan; Arivusudar Marimuthu; Sutopa Banerjee; Devi S Somanathan; Aimy Sebastian; Sandhya Rani; Somak Ray; C J Harrys Kishore; Sashi Kanth; Mukhtar Ahmed; Manoj K Kashyap; Riaz Mohmood; Y L Ramachandra; V Krishna; B Abdul Rahiman; Sujatha Mohan; Prathibha Ranganathan; Subhashri Ramabadran; Raghothama Chaerkady; Akhilesh Pandey
Journal: Nucleic Acids Res Date: 2008-11-06 Impact factor: 16.971

6. Bridging high-throughput genetic and transcriptional data reveals cellular responses to alpha-synuclein toxicity.

Authors: Esti Yeger-Lotem; Laura Riva; Linhui Julie Su; Aaron D Gitler; Anil G Cashikar; Oliver D King; Pavan K Auluck; Melissa L Geddie; Julie S Valastyan; David R Karger; Susan Lindquist; Ernest Fraenkel
Journal: Nat Genet Date: 2009-02-22 Impact factor: 38.330

7. Pathway and network-based analysis of genome-wide association studies in multiple sclerosis.

Authors: Sergio E Baranzini; Nicholas W Galwey; Joanne Wang; Pouya Khankhanian; Raija Lindberg; Daniel Pelletier; Wen Wu; Bernard M J Uitdehaag; Ludwig Kappos; Chris H Polman; Paul M Matthews; Stephen L Hauser; Rachel A Gibson; Jorge R Oksenberg; Michael R Barnes
Journal: Hum Mol Genet Date: 2009-03-13 Impact factor: 6.150

8. eQED: an efficient method for interpreting eQTL associations using protein networks.

Authors: Silpa Suthram; Andreas Beyer; Richard M Karp; Yonina Eldar; Trey Ideker
Journal: Mol Syst Biol Date: 2008-03-04 Impact factor: 11.429

9. Network-based global inference of human disease genes.

Authors: Xuebing Wu; Rui Jiang; Michael Q Zhang; Shao Li
Journal: Mol Syst Biol Date: 2008-05-06 Impact factor: 11.429

10. iRefIndex: a consolidated protein interaction database with provenance.

Authors: Sabry Razick; George Magklaras; Ian M Donaldson
Journal: BMC Bioinformatics Date: 2008-09-30 Impact factor: 3.169

38 in total

Review 1. Beyond genome-wide significance: integrative approaches to the interpretation and extension of GWAS findings for alcohol use disorder.

Authors: Jessica E Salvatore; Shizhong Han; Sean P Farris; Kristin M Mignogna; Michael F Miles; Arpana Agrawal
Journal: Addict Biol Date: 2018-01-09 Impact factor: 4.280

Network analysis of GWAS data.

1. Methods for detecting associations with rare variants for common diseases: application to analysis of sequence data.

2. Align human interactome with phenome to identify causative genes and networks underlying disease families.

Review 3. Genome-wide association studies for complex traits: consensus, uncertainty and challenges.

4. Variants in exons and in transcription factors affect gene expression in trans.

5. Human Protein Reference Database--2009 update.

6. Bridging high-throughput genetic and transcriptional data reveals cellular responses to alpha-synuclein toxicity.

7. Pathway and network-based analysis of genome-wide association studies in multiple sclerosis.

8. eQED: an efficient method for interpreting eQTL associations using protein networks.

9. Network-based global inference of human disease genes.

10. iRefIndex: a consolidated protein interaction database with provenance.

Review 1. Beyond genome-wide significance: integrative approaches to the interpretation and extension of GWAS findings for alcohol use disorder.

Review 2. Dissecting the Genetics of Osteoporosis using Systems Approaches.

3. GWAB: a web server for the network-based boosting of human genome-wide association data.

Review 4. Genetic background effects in quantitative genetics: gene-by-system interactions.

Review 5. The kidney transcriptome, from single cells to whole organs and back.

6. A Genetic Network Associated With Stress Resistance, Longevity, and Cancer in Humans.

7. Boosting GWAS using biological networks: A study on susceptibility to familial breast cancer.

8. Integrative Structural Brain Network Analysis in Diffusion Tensor Imaging.

9. Visible Machine Learning for Biomedicine.

10. Systems biology and the analysis of genetic variation.