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Collective feature selection to identify crucial epistatic variants
2018
BioData Mining
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Following this, we applied our proposed collective feature selection approach to select the top 1% of variables to identify potential interacting variables associated with Body Mass Index (BMI) in4 4,000 ...
Conclusions: In this study, we were able to show that selecting variables using a collective feature selection approach could help in selecting true positive epistatic variables more frequently than applying ...
Availability of natural biological data from DiscovEHR cohort may subject to data user agreement. ...
doi:10.1186/s13040-018-0168-6
pmid:29713383
pmcid:PMC5907720
fatcat:blwwuouwfnhi3n3jnzkgckdo74
Collective feature selection to identify crucial epistatic variants
[article]
2018
bioRxiv
pre-print
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Following this, we applied our proposed collective feature selection approach to select the top 1% of variables to identify potential interacting variables associated with Body Mass Index (BMI) in ~44,000 ...
Conclusions: In this study, we were able to show that selecting variables using a collective feature selection approach could help in selecting true positive epistatic variables more frequently than applying ...
Plot A illustrates results for EDM-Number Collective feature selection to select 1758 variables with potential epistatic Best GENN model selected from ATHENA. ...
doi:10.1101/293365
fatcat:jbohpaa3ubdzxkrfarwtl6qghy
Learning the pattern of epistasis linking genotype and phenotype in a protein
2019
Nature Communications
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to examine epistasis up to the 13th order. ...
However, the combinatorial complexity of potential epistatic interactions has severely limited the analysis of this problem. ...
This work was supported by NIH Grant RO1GM12345 (to R.R.), a Robert A. Welch Foundation Grant I-1366 (to R.R.), and the Green Center for Systems Biology at UT Southwestern Medical Center. ...
doi:10.1038/s41467-019-12130-8
pmid:31527666
pmcid:PMC6746860
fatcat:lapysyuwwrbo5pqhnwxytbq45e
Evaporative cooling feature selection for genotypic data involving interactions
2007
Bioinformatics
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Motivation: The development of genome-wide capabilities for genotyping has led to the practical problem of identifying the minimum subset of genetic variants relevant to the classification of a phenotype ...
Methods: Analogous to the physical mechanism of evaporation, we introduce an evaporative cooling (EC) feature selection algorithm that seeks to obtain a subset of attributes with the optimum information ...
The authors would like to thank Alison Motsinger and Scott Dudek for assistance with genomeSIM and Stephen Chanock for genotyping services. ...
doi:10.1093/bioinformatics/btm317
pmid:17586549
pmcid:PMC3988427
fatcat:hkx5oka7lzbtbgxqtaf6qpuswe
Epistatic effects of multiple receptor genes on pathophysiology of asthma – its limits and potential for clinical application
2014
Medical Science Monitor
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To date, genome-wide association studies (GWAS) permit a comprehensive scan of the genome in an unbiased manner, with high sensitivity, and thereby have the potential to identify candidate genes for the ...
The present review highlights a concept of epistasis to overcome traditional genetic studies in humans and provides an update of evidence on epistatic effects on asthma. ...
However, we need to be aware that findings obtained from this approach are unlikely to capture the overall variety of disease features, because this approach limits findings to a specific feature of the ...
doi:10.12659/msm.889754
pmid:24435185
pmcid:PMC3907491
fatcat:ughvjts7e5aa3hk6q4ll5f5zni
SAERMA: Stacked Autoencoder Rule Mining Algorithm for the Interpretation of Epistatic Interactions in GWAS for Extreme Obesity
[article]
2019
arXiv
pre-print
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Our proposed approach extends GWAS by combining deep learning stacked autoencoders (SAEs) and association rule mining (ARM) to identify epistatic interactions between SNPs. ...
Following traditional GWAS quality control and association analysis, the most significant SNPs are selected and used in the subsequent analysis to investigate epistasis. ...
In this paper, only positive correlated rules are of interest (7) Finding measures that can be used with lift to make the best selection of rules is crucial. ...
arXiv:1908.10166v1
fatcat:igwhn5mgbvc4tnevzz7qshokwi
Travelling the world of gene-gene interactions
2011
Briefings in Bioinformatics
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The purpose of this work is to give a perspective view on a selection of currently active analysis strategies and concerns in the context of epistasis detection, and to provide an eye to the future of ...
Over the last few years, main effect genetic association analysis has proven to be a successful tool to unravel genetic risk components to a variety of complex diseases. ...
In this context, two concepts play a crucial role: feature extraction and feature selection. Feature extraction [22] aims to reduce dimensionality by aggregation or projection. ...
doi:10.1093/bib/bbr012
pmid:21441561
fatcat:3kojyhlvfrgjrjbjtrovmg2aaa
SAERMA: Stacked Autoencoder Rule Mining Algorithm for the Interpretation of Epistatic Interactions in GWAS for Extreme Obesity
2020
IEEE Access
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In this paper, only positive correlated rules are of interest (7) Finding measures that can be used with lift to make the best selection of rules is crucial. ...
DISCUSSIONS GWAS can identify common variants with modest to large effects on phenotypes. ...
The current trail involves monitoring and modelling the behaviour of dementia patients to facilitate safe independent living. ...
doi:10.1109/access.2020.3002923
fatcat:gq7njkenpvfwxb5kaywjn5fjya
Exploring the Effects of Genetic Variants on Clinical Profiles of Parkinson's Disease Assessed by the Unified Parkinson's Disease Rating Scale and the Hoehn–Yahr Stage
2016
PLoS ONE
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In a cohort consisting of 2,011 Chinese Han PD patients, we selected 9 representative variants from the 6 above-mentioned common PD genes to analyze their main and epistatic effects on the Unified Parkinson's ...
Many genetic variants have been linked to familial or sporadic Parkinson's disease (PD), among which those identified in PARK16, BST1, SNCA, LRRK2, GBA and MAPT genes have been demonstrated to be the most ...
Therefore, it becomes crucial to understand the basis of clinical symptoms and predict the course of disease progression. ...
doi:10.1371/journal.pone.0155758
pmid:27299523
pmcid:PMC4907455
fatcat:vrbfqcqtuzf3rdowfvnbgrtq6q
Genome‐wide association coupled gene to gene interaction studies unveil novel epistatic targets among major effect loci impacting rice grain chalkiness
2020
Plant Biotechnology Journal
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Promising novel epistatic interactions were found between the loci of chromosomes 6 (PGC6.1) and 7 (PGC7.8) that contributed to lower PGC. ...
The importance of PGC6.1 was validated through multi-parent advanced generation intercrosses and several low-chalk lines possessing superior haplotypes were identified. ...
All authors read and contributed to the revision of manuscript. ...
doi:10.1111/pbi.13516
pmid:33220119
pmcid:PMC8131057
fatcat:jozmqc3wqbcnfnyfcbyvfyqqqy
Identification of epistasis loci underlying rice flowering time by controlling population stratification and polygenic effect
2018
DNA Research
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Bioinformatics analysis showed that 66.55% pairwise genes of the identified interactions (392 out of the 589 interactions) have similarity in various genomic features. ...
Moreover, significant numbers of detected epistatic genes have high expression in different floral tissues. ...
Acknowledgements The authors would like to thank the rice diversity research platform for sharing the data used in this study. We thank to Dr. Imrul Mosaddek Ahmed for helpful discussions. ...
doi:10.1093/dnares/dsy043
pmid:30590457
pmcid:PMC6476725
fatcat:atxemfgptvernktpxlzdp5qimu
Capturing the Spectrum of Interaction Effects in Genetic Association Studies by Simulated Evaporative Cooling Network Analysis
2009
PLoS Genetics
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To overcome the weaknesses of these data mining approaches, we develop Evaporative Cooling (EC) feature selection, a flexible machine learning method that can integrate multiple importance scores while ...
We use simulation analysis to show that EC is able to identify a wide range of interaction effects in genetic association data. ...
We would like to thank the anonymous reviewers for their suggestions that greatly improved the manuscript.
Author Contributions Conceived and designed the experiments: BAM. ...
doi:10.1371/journal.pgen.1000432
pmid:19300503
pmcid:PMC2653647
fatcat:ht3cpr2eabhpdiqjjslet6f5ry
Genetic host specificity of hepatitis E virus
2014
Infection, Genetics and Evolution
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We employed a Bayesian network (BN) analysis of HEV3 and HEV4 to detect epistatic connectivity among protein sites and its association with the host specificity in each genotype. ...
The relevance of HEV genetic diversity to host adaptation is poorly understood. ...
Feature selection (FS)-FS was performed on HEV data to identify and select residue site markers in order to maximize accuracy performance of the classifiers. ...
doi:10.1016/j.meegid.2014.03.011
pmid:24667049
pmcid:PMC5745802
fatcat:ggrrmmbly5avxcecy26qo2m7ii
Mapping complex disease loci in whole-genome association studies
2004
Nature
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Identification of the genetic polymorphisms that contribute to susceptibility for common diseases such as type 2 diabetes and schizophrenia will aid in the development of diagnostics and therapeutics. ...
Thanks to D. Altshuler for helpful input, to G. Jarvik, P. Heagerty and P. Scheet for discussions on epistatic risk models, and to T. Banghale, D. Crawford, B. Livingston, R. Mackelprang and M. ...
Once patterns of LD between common polymorphisms have been described, it will be possible to select optimized subsets of tagSNPs such that all common variants (or a sufficiently large fraction thereof) ...
doi:10.1038/nature02623
pmid:15164069
fatcat:aed7psdokzdanogdhmdq4jv3gm
Epistasis and quantitative traits: using model organisms to study gene–gene interactions
2013
Nature reviews genetics
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identify potentially interacting loci. ...
In modern parlance, genetic canalization refers to suppressing (that is, lessthanadditive) epistatic interactions between naturally segregating variants. ...
doi:10.1038/nrg3627
pmid:24296533
pmcid:PMC3918431
fatcat:s3tqjt3kqfgv7gotv3m7qrib4m
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