2018
DOI: 10.1186/s12864-018-4910-8
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Stepwise approach to SNP-set analysis illustrated with the Metabochip and colorectal cancer in Japanese Americans of the Multiethnic Cohort

Abstract: BackgroundCommon variants have explained less than the amount of heritability expected for complex diseases, which has led to interest in less-common variants and more powerful approaches to the analysis of whole-genome scans. Because of low frequency (low statistical power), less-common variants are best analyzed using SNP-set methods such as gene-set or pathway-based analyses. However, there is as yet no clear consensus regarding how to focus in on potential risk variants following set-based analyses. We use… Show more

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Cited by 6 publications
(3 citation statements)
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“…Furthermore, the factor contributing to incorrect localization of the encoded protein, the rs77542170 (c.934-2A>G) variant in MUTYH which is mainly observed in subjects of East Asian descent, and is attributed to main cause of MAP in patients of Asian descent (41).…”
Section: Discussionmentioning
confidence: 99%
“…Furthermore, the factor contributing to incorrect localization of the encoded protein, the rs77542170 (c.934-2A>G) variant in MUTYH which is mainly observed in subjects of East Asian descent, and is attributed to main cause of MAP in patients of Asian descent (41).…”
Section: Discussionmentioning
confidence: 99%
“…2 ) increases the risk of CRC [36] . For example, the number cases of CRC among of CRC first generation of Japanese migrants to Hawaii increased to levels similar to those of local Hawaiians, although traditionally the Japanese have low CRC cases [37] , [38] , [39] . Therefore, this evidence shows that diet is capable of causing gut microbiota dysbiosis and in response to long-term or habitual shift from traditional diet, gut microbiota may change completely.…”
Section: Diet-mediated Changes In the Gut Microbial Communitymentioning
confidence: 99%
“…There are various complex statistical models developed to improve the statistical power for SNP detection. We consider all of these methods as supervised learning methods, which comprises of SNP-set analysis [ 12 13 , 14 , 15 ], Penalized regression approach [ 16 , 17 , 18 ] and Bayesian hierarchical regression models [ 19 , 20 , 21 , 22 ].…”
Section: Statistical Models In Gwasmentioning
confidence: 99%