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ABACUS: an entropy-based cumulative bivariate statistic robust to rare variants and different direction of genotype effect
Author(s) -
Barbara Di Camillo,
Francesco Sambo,
Gianna Toffolo,
Claudio Cobelli
Publication year - 2013
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btt697
Subject(s) - single nucleotide polymorphism , biology , computational biology , snp , genetics , bivariate analysis , genotype , bioinformatics , computer science , gene , machine learning
In the past years, both sequencing and microarray have been widely used to search for relations between genetic variations and predisposition to complex pathologies such as diabetes or neurological disorders. These studies, however, have been able to explain only a small fraction of disease heritability, possibly because complex pathologies cannot be referred to few dysfunctional genes, but are rather heterogeneous and multicausal, as a result of a combination of rare and common variants possibly impairing multiple regulatory pathways. Rare variants, though, are difficult to detect, especially when the effects of causal variants are in different directions, i.e. with protective and detrimental effects.

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