Literature DB >> 28148922

Detecting disease association with rare variants in case-parents studies.

Yu-Mei Li1, Yang Xiang1.   

Abstract

Major advances in DNA sequencing technology have generated large quantities of sequence data that promote the development of statistical methods for rare variant association analyses. Although many population-based case control methods have been well developed for rare variant analysis, little work focuses on family-based studies. In this paper, we extend the existing methods to test for association of rare variants with case-parents data. We investigated the influence of non-variants and effects of causal variants on max-, multi-marker test, and collapsing method, and proposed an adaptive strategy based on a difference vector. Using simulations we show that the collapsing method is affected profoundly by the number of non-causal variants and different direction effects of causal variants and multi-marker test is most robust to non-causal variants and effects of causal variants. Our selective-difference strategy can improve power especially for collapsing method.

Mesh:

Year:  2017        PMID: 28148922     DOI: 10.1038/jhg.2017.1

Source DB:  PubMed          Journal:  J Hum Genet        ISSN: 1434-5161            Impact factor:   3.172


  13 in total

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8.  Testing for an unusual distribution of rare variants.

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9.  A groupwise association test for rare mutations using a weighted sum statistic.

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  1 in total

1.  Rare variant association analysis in case-parents studies by allowing for missing parental genotypes.

Authors:  Yumei Li; Yang Xiang; Chao Xu; Hui Shen; Hongwen Deng
Journal:  BMC Genet       Date:  2018-01-15       Impact factor: 2.797

  1 in total

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