Multifactor dimensionality reduction: An analysis strategy for modelling and detecting gene - gene interactions in human genetics and pharmacogenomics studies
The detection of gene - gene and gene - environment interactions associated with complex human disease or pharmacogenomic endpoints is a difficult challenge for human geneticists. Unlike rare, Mendelian diseases that are associated with a single gene, most common diseases are caused by the non-linea...
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| Format: | Online |
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BioMed Central
2006
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3500181/ |
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pubmed-3500181 |
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pubmed-35001812012-11-17 Multifactor dimensionality reduction: An analysis strategy for modelling and detecting gene - gene interactions in human genetics and pharmacogenomics studies Motsinger, Alison A Ritchie, Marylyn D Review The detection of gene - gene and gene - environment interactions associated with complex human disease or pharmacogenomic endpoints is a difficult challenge for human geneticists. Unlike rare, Mendelian diseases that are associated with a single gene, most common diseases are caused by the non-linear interaction of numerous genetic and environmental variables. The dimensionality involved in the evaluation of combinations of many such variables quickly diminishes the usefulness of traditional, parametric statistical methods. Multifactor dimensionality reduction (MDR) is a novel and powerful statistical tool for detecting and modelling epistasis. MDR is a non-parametric and model-free approach that has been shown to have reasonable power to detect epistasis in both theoretical and empirical studies. MDR has detected interactions in diseases such as sporadic breast cancer, multiple sclerosis and essential hypertension. BioMed Central 2006-03-01 /pmc/articles/PMC3500181/ /pubmed/16595076 http://dx.doi.org/10.1186/1479-7364-2-5-318 Text en Copyright ©2006 Henry Stewart Publications |
| repository_type |
Open Access Journal |
| institution_category |
Foreign Institution |
| institution |
US National Center for Biotechnology Information |
| building |
NCBI PubMed |
| collection |
Online Access |
| language |
English |
| format |
Online |
| author |
Motsinger, Alison A Ritchie, Marylyn D |
| spellingShingle |
Motsinger, Alison A Ritchie, Marylyn D Multifactor dimensionality reduction: An analysis strategy for modelling and detecting gene - gene interactions in human genetics and pharmacogenomics studies |
| author_facet |
Motsinger, Alison A Ritchie, Marylyn D |
| author_sort |
Motsinger, Alison A |
| title |
Multifactor dimensionality reduction: An analysis strategy for modelling and detecting gene - gene interactions in human genetics and pharmacogenomics studies |
| title_short |
Multifactor dimensionality reduction: An analysis strategy for modelling and detecting gene - gene interactions in human genetics and pharmacogenomics studies |
| title_full |
Multifactor dimensionality reduction: An analysis strategy for modelling and detecting gene - gene interactions in human genetics and pharmacogenomics studies |
| title_fullStr |
Multifactor dimensionality reduction: An analysis strategy for modelling and detecting gene - gene interactions in human genetics and pharmacogenomics studies |
| title_full_unstemmed |
Multifactor dimensionality reduction: An analysis strategy for modelling and detecting gene - gene interactions in human genetics and pharmacogenomics studies |
| title_sort |
multifactor dimensionality reduction: an analysis strategy for modelling and detecting gene - gene interactions in human genetics and pharmacogenomics studies |
| description |
The detection of gene - gene and gene - environment interactions associated with complex human disease or pharmacogenomic endpoints is a difficult challenge for human geneticists. Unlike rare, Mendelian diseases that are associated with a single gene, most common diseases are caused by the non-linear interaction of numerous genetic and environmental variables. The dimensionality involved in the evaluation of combinations of many such variables quickly diminishes the usefulness of traditional, parametric statistical methods. Multifactor dimensionality reduction (MDR) is a novel and powerful statistical tool for detecting and modelling epistasis. MDR is a non-parametric and model-free approach that has been shown to have reasonable power to detect epistasis in both theoretical and empirical studies. MDR has detected interactions in diseases such as sporadic breast cancer, multiple sclerosis and essential hypertension. |
| publisher |
BioMed Central |
| publishDate |
2006 |
| url |
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3500181/ |
| _version_ |
1611924830555209728 |