scholarly journals The importance of replication in gene-gene interaction studies: multifactor dimensionality reduction applied to a two-stage breast cancer case-control study

2008 ◽  
Vol 29 (6) ◽  
pp. 1215-1218 ◽  
Author(s):  
R. L. Milne ◽  
R. Fagerholm ◽  
H. Nevanlinna ◽  
J. Benitez
Keyword(s):  
Breast Cancer ◽  
Dimensionality Reduction ◽  
Multifactor Dimensionality Reduction ◽  
Case Control Study ◽  
Breast Cancer Case ◽  
Gene Interaction ◽  
Case Control ◽  
Cancer Case ◽  
Two Stage ◽  
Control Study

scholarly journals Identification of High-Order Single-Nucleotide Polymorphism Barcodes in Breast Cancer Using a Hybrid Taguchi-Genetic Algorithm: Case-Control Study

10.2196/16886 ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. e16886
Author(s):  
Li-Yeh Chuang ◽  
Cheng-San Yang ◽  
Huai-Shuo Yang ◽  
Cheng-Hong Yang
Keyword(s):  
Breast Cancer ◽  
Genetic Algorithm ◽  
Taguchi Method ◽  
Case Control Study ◽  
Breast Cancer Case ◽  
Case Control ◽  
High Order ◽  
Cancer Case ◽  
Single Nucleotide ◽  
Control Study

Background Breast cancer has a major disease burden in the female population, and it is a highly genome-associated human disease. However, in genetic studies of complex diseases, modern geneticists face challenges in detecting interactions among loci. Objective This study aimed to investigate whether variations of single-nucleotide polymorphisms (SNPs) are associated with histopathological tumor characteristics in breast cancer patients. Methods A hybrid Taguchi-genetic algorithm (HTGA) was proposed to identify the high-order SNP barcodes in a breast cancer case-control study. A Taguchi method was used to enhance a genetic algorithm (GA) for identifying high-order SNP barcodes. The Taguchi method was integrated into the GA after the crossover operations in order to optimize the generated offspring systematically for enhancing the GA search ability. Results The proposed HTGA effectively converged to a promising region within the problem space and provided excellent SNP barcode identification. Regression analysis was used to validate the association between breast cancer and the identified high-order SNP barcodes. The maximum OR was less than 1 (range 0.870-0.755) for two- to seven-order SNP barcodes. Conclusions We systematically evaluated the interaction effects of 26 SNPs within growth factor–related genes for breast carcinogenesis pathways. The HTGA could successfully identify relevant high-order SNP barcodes by evaluating the differences between cases and controls. The validation results showed that the HTGA can provide better fitness values as compared with other methods for the identification of high-order SNP barcodes using breast cancer case-control data sets.

scholarly journals A multi-ethnic breast cancer case–control study in New Zealand: evidence of differential risk patterns

2012 ◽  
Vol 24 (1) ◽  
pp. 135-152 ◽  
Author(s):  
Mona Jeffreys ◽  
Fiona McKenzie ◽  
Ridvan Firestone ◽  
Michelle Gray ◽  
Soo Cheng ◽  
...  
Keyword(s):  
Breast Cancer ◽  
New Zealand ◽  
Case Control Study ◽  
Breast Cancer Case ◽  
Case Control ◽  
Cancer Case ◽  
Control Study ◽  
Differential Risk

scholarly journals Identification of High-Order Single-Nucleotide Polymorphism Barcodes in Breast Cancer Using a Hybrid Taguchi-Genetic Algorithm: Case-Control Study (Preprint)

2019 ◽  
Author(s):  
Li-Yeh Chuang ◽  
Cheng-San Yang ◽  
Huai-Shuo Yang ◽  
Cheng-Hong Yang
Keyword(s):  
Breast Cancer ◽  
Genetic Algorithm ◽  
Taguchi Method ◽  
Case Control Study ◽  
Breast Cancer Case ◽  
Case Control ◽  
High Order ◽  
Cancer Case ◽  
Single Nucleotide ◽  
Control Study

BACKGROUND Breast cancer has a major disease burden in the female population, and it is a highly genome-associated human disease. However, in genetic studies of complex diseases, modern geneticists face challenges in detecting interactions among loci. OBJECTIVE This study aimed to investigate whether variations of single-nucleotide polymorphisms (SNPs) are associated with histopathological tumor characteristics in breast cancer patients. METHODS A hybrid Taguchi-genetic algorithm (HTGA) was proposed to identify the high-order SNP barcodes in a breast cancer case-control study. A Taguchi method was used to enhance a genetic algorithm (GA) for identifying high-order SNP barcodes. The Taguchi method was integrated into the GA after the crossover operations in order to optimize the generated offspring systematically for enhancing the GA search ability. RESULTS The proposed HTGA effectively converged to a promising region within the problem space and provided excellent SNP barcode identification. Regression analysis was used to validate the association between breast cancer and the identified high-order SNP barcodes. The maximum OR was less than 1 (range 0.870-0.755) for two- to seven-order SNP barcodes. CONCLUSIONS We systematically evaluated the interaction effects of 26 SNPs within growth factor–related genes for breast carcinogenesis pathways. The HTGA could successfully identify relevant high-order SNP barcodes by evaluating the differences between cases and controls. The validation results showed that the HTGA can provide better fitness values as compared with other methods for the identification of high-order SNP barcodes using breast cancer case-control data sets.

Evaluation of molecular markers GSTM1 and GSTT1 and clinical factors in breast cancer: case-control study and literature review

Xenobiotica ◽  
2021 ◽  
pp. 1-27
Author(s):  
Stéphanie Piacenti dos Santos ◽  
Sabrina Sayuri Morissugui ◽  
Ana Paula D’Alarme Gimenez Martins ◽  
Glaucia Maria de Mendonça Fernandes ◽  
Anelise Russo ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Molecular Markers ◽  
Literature Review ◽  
Case Control Study ◽  
Breast Cancer Case ◽  
Case Control ◽  
Cancer Case ◽  
Clinical Factors ◽  
Control Study
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