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Very large scale ReliefF for genome-wide association analysis

Margaret J. Eppstein, Paul Haake
2008 2008 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology  
However, the accuracy of ReliefF does not scale up to the sizes needed for truly large genome-scale SNP association studies.  ...  There is thus a pressing need for new computational methods capable of detecting nonlinearly interacting single nucleotide polymorphism (SNPs) that are associated with disease, from amidst up to hundreds  ...  Payne for his previous assistance in modifications to this data generator.  ... 
doi:10.1109/cibcb.2008.4675767 dblp:conf/cibcb/EppsteinH08 fatcat:si4rwpwd6nfphksgkdnd56qaxe

Finding the Epistasis Needles in the Genome-Wide Haystack [chapter]

Marylyn D. Ritchie
2014 Msphere  
Genome-wide association studies (GWAS) have dominated the fi eld of human genetics for the past 10 years.  ...  Part of the challenge for epistasis analysis in GWAS is the sheer magnitude of the search and the computational complexity associated with it.  ...  of epistasis in large-scale genomic analyses including GWAS as well as next-generation sequencing.  ... 
doi:10.1007/978-1-4939-2155-3_2 pmid:25403525 fatcat:zlb6cog4fjhizpeffe75yagfta

Spatially Uniform ReliefF (SURF) for computationally-efficient filtering of gene-gene interactions

Casey S Greene, Nadia M Penrod, Jeff Kiralis, Jason H Moore
2009 BioData Mining  
Genome-wide association studies are becoming the de facto standard in the genetic analysis of common human diseases.  ...  For instance, SURF should be used instead of ReliefF to filter a dataset before an exhaustive MDR analysis. This change increases the ability of a study to detect gene-gene interactions.  ...  Jason Gilmore for his technical assistance.  ... 
doi:10.1186/1756-0381-2-5 pmid:19772641 pmcid:PMC2761303 fatcat:7nq4em7oijb5li53jtcfewsgkm

Bioinformatics challenges for genome-wide association studies

J. H. Moore, F. W. Asselbergs, S. M. Williams
2010 Bioinformatics  
Motivation: The sequencing of the human genome has made it possible to identify an informative set of >1 million single nucleotide polymorphisms (SNPs) across the genome that can be used to carry out genome-wide  ...  association studies (GWASs).  ...  ACKNOWLEDGEMENTS We would like to thank the anonymous reviewers for their very helpful comments and suggestions. Funding: National Institutes of Health (LM010098, LM009012 and AI59694).  ... 
doi:10.1093/bioinformatics/btp713 pmid:20053841 pmcid:PMC2820680 fatcat:hcd25vxlcnacvb7w4xyk2biyka

Using Biological Knowledge to Uncover the Mystery in the Search for Epistasis in Genome-Wide Association Studies

Marylyn D. Ritchie
2010 Annals of Human Genetics  
The search for the missing heritability in genome-wide association studies (GWAS) has become an important focus for the human genetics community.  ...  We discuss a number of these approaches and propose that a comprehensive approach will likely be most fruitful for searching for epistasis in large-scale genomic studies of the current state-of-the-art  ...  detection of epistasis in large-scale genomic analyses including GWAS as well as next-generation sequencing.  ... 
doi:10.1111/j.1469-1809.2010.00630.x pmid:21158748 pmcid:PMC3092784 fatcat:wxdjst2trncr5oqifbymqzqz4i

A survey about methods dedicated to epistasis detection

Clément Niel, Christine Sinoquet, Christian Dina, Ghislain Rocheleau
2015 Frontiers in Genetics  
Statistical analysis typically looks for association between a phenotype and a SNP taken individually via single-locus tests.  ...  During the past decade, findings of genome-wide association studies (GWAS) improved our knowledge and understanding of disease genetics.  ...  We also thank two anonymous reviewers for very helpful comments and valuable improvement of the manuscript.  ... 
doi:10.3389/fgene.2015.00285 pmid:26442103 pmcid:PMC4564769 fatcat:5e5bqfpcbjbchf5n7mhurtejny

Computational intelligence for genetic association study in complex diseases: review of theory and applications

Arpad Kelemen, Athanasios V. Vasilakos, Yulan Liang
2009 International Journal of Computational Intelligence in Bioinformatics and Systems Biology  
Comprehensive evaluation of common genetic variations through association of SNP structure with common complex disease in the genome-wide scale is currently a hot area in human genome research thanks for  ...  This review provides coverage of recent developments of theory and applications in computational intelligence for complex diseases in genetic association study.  ...  They also applied an application to a large-scale case-control study for Type 2 diabetes.  ... 
doi:10.1504/ijcibsb.2009.024041 fatcat:s5qhnexpezgypdsau54nvi365i

Implementing ReliefF filters to extract meaningful features from genetic lifetime datasets

Lorenzo Beretta, Alessandro Santaniello
2011 Journal of Biomedical Informatics  
These tools, such as the survival dimensionality reduction algorithm, may suffer from extreme computational costs in large-scale datasets.  ...  Methods: The ReliefF algorithm was modified and adjusted to compensate for the loss of information due to censoring, introducing reclassification and weighting schemes.  ...  Nonetheless, the efficiency of the SDR method is severely hampered by the combinatorial explosion that can be observed in large-scale datasets.  ... 
doi:10.1016/j.jbi.2010.12.003 pmid:21168527 fatcat:ge4lzjq5ybfjfjnlm6pviuwm6u

Uncovering metabolic pathways relevant to phenotypic traits of microbial genomes

Gabi Kastenmüller, Maria Schenk, Johann Gasteiger, Hans-Werner Mewes
2009 Genome Biology  
Here we present a novel method using multivariate machine learning techniques for comparing automatically derived metabolic reconstructions of sequenced genomes on a large scale.  ...  Microbial metabolic pathways A new machine learning-based method is presented here for the identification of metabolic pathways related to specific phenotypes in multiple microbial genomes.  ...  Acknowledgements We thank Yu Wang, Thorsten Schmidt and Axel Facius for their advice regarding statistical and machine learning issues, Mathias Walter, Martin Münsterkötter and Thomas Rattei for their  ... 
doi:10.1186/gb-2009-10-3-r28 pmid:19284550 pmcid:PMC2690999 fatcat:grn3yolcyjcxzgwuzvlfedhwjy

GenEpi: gene-based epistasis discovery using machine learning

Yu-Chuan Chang, for the Alzheimer's Disease Neuroimaging Initiative, June-Tai Wu, Ming-Yi Hong, Yi-An Tung, Ping-Han Hsieh, Sook Wah Yee, Kathleen M. Giacomini, Yen-Jen Oyang, Chien-Yu Chen
2020 BMC Bioinformatics  
Genome-wide association studies (GWAS) provide a powerful means to identify associations between genetic variants and phenotypes.  ...  However, GWAS techniques for detecting epistasis, the interactions between genetic variants associated with phenotypes, are still limited.  ...  Acknowledgements Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department  ... 
doi:10.1186/s12859-020-3368-2 pmid:32093643 fatcat:65aqttpxxjhx3b5yahyelndynu

Using epigenomics data to predict gene expression in lung cancer

Jeffery Li, Travers Ching, Sijia Huang, Lana X Garmire
2015 BMC Bioinformatics  
Results: A best model comprising 67 features is chosen by ReliefF based feature selection and random forest classification method, with AUC = 0.864 from the 10-fold cross-validation of the training set  ...  This method uses the Illumina Infinium HumanMethylation450K Beadchip CpG methylation array data from paired lung cancer and adjacent normal tissues in The Cancer Genome Atlas (TCGA) and histone modification  ...  Jayson Masaki for reviewing the manuscript. Declarations Publication charges for this article were funded by NIH/NIGMS P20 COBRE GM103457, NIH/NIEHS K01 ES025434-01 and Hawaii Community Foundation.  ... 
doi:10.1186/1471-2105-16-s5-s10 pmid:25861082 pmcid:PMC4402699 fatcat:xmfhnn63snhodlktf5shetfwr4

HARVESTMAN: A framework for hierarchical feature learning and selection from whole genome sequencing data [article]

Trevor S Frisby, Shawn James Baker, Guillaume Marcais, Quang Minh Hoang, Carl Kingsford, Christopher James Langmead
2020 bioRxiv   pre-print
We demonstrate that HARVESTMAN scales to thousands of genomes comprising more than 84 million variants by processing phase 3 data from the 1000 Genomes Project, the largest publicly available collection  ...  Binary releases of HARVESTMAN compatible with Linux, Windows, and Mac are available for download at https://github.com/cmlh-gp/HARVESTMAN-public/releases  ...  To demonstrate the effectiveness of HARVESTMAN at scale, we apply our method to data obtained from the 1000 Genomes Project (The 1000 Genomes Project Consortium , 2015), a large and well-known publicly  ... 
doi:10.1101/2020.03.24.005603 fatcat:bylymmgrirejbocgfpgjwfobxu

GenEpi: Gene-based Epistasis Discovery Using Machine Learning [article]

Yu-Chuan Chang, June-Tai Wu, Ming-Yi Hong, Yi-An Tung, Ping-Han Hsieh, Sook Wah Yee, Kathleen M. Giacomini, Yen-Jen Oyang, Chien-Yu Chen, Alzheimer's Disease Neuroimaging Initiative
2018 biorxiv/medrxiv   pre-print
Genome-wide association studies (GWAS) provide a powerful means to identify associations between genetic variants and phenotypes.  ...  However, GWAS techniques for detecting epistasis, the interactions between genetic variants associated with phenotypes, are still limited.  ...  Acknowledgements Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department  ... 
doi:10.1101/421719 fatcat:lpnll2vcsbcgvhvuspviqklue4

Genomic mining for complex disease traits with "random chemistry"

Margaret J. Eppstein, Joshua L. Payne, Bill C. White, Jason H. Moore
2007 Genetic Programming and Evolvable Machines  
Our rapidly growing knowledge regarding genetic variation in the human genome offers great potential for understanding the genetic etiology of disease.  ...  Here, we employ an approximate and noisy fitness function based on the ReliefF data mining algorithm.  ...  We thank Joshua Gilbert for his aid in creating the synthetic data sets.  ... 
doi:10.1007/s10710-007-9039-5 fatcat:oi7se7cehfgyxbmw4msjbbg3uu

A Markov blanket-based method for detecting causal SNPs in GWAS

Bing Han, Meeyoung Park, Xue-wen Chen
2010 BMC Bioinformatics  
In addition, most methods are not suitable for genome-wide scale studies due to their computational complexity.  ...  With the development of genome-wide association studies (GWAS), designing powerful and robust computational method for identifying epistatic interactions associated with common diseases becomes a great  ...  large-scale datasets.  ... 
doi:10.1186/1471-2105-11-s3-s5 pmid:20438652 pmcid:PMC2863064 fatcat:3rkzxbn2lndn5bvki44s3hg75u
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