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Approaches to Handling Incomplete Data in Family‐based Association Testing
Author(s) -
Van Steen K.,
Laird N. M.,
Markel P.,
Molenberghs G.
Publication year - 2007
Publication title -
annals of human genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.537
H-Index - 77
eISSN - 1469-1809
pISSN - 0003-4800
DOI - 10.1111/j.1469-1809.2006.00325.x
Subject(s) - credibility , genetic data , computer science , process (computing) , association (psychology) , genetic association , data mining , biology , genetics , genotype , psychology , medicine , single nucleotide polymorphism , population , environmental health , political science , law , psychotherapist , gene , operating system
Summary The high throughput of data arising from the complete sequence of the human genome has left statistical geneticists with a rich and extensive information source. The wide availability of software and the increase in computing power has improved the possibilities to access and process such data. One problem is incompleteness of the data: unobserved or partially observed data points due to technical reasons or reasons associated with the patient's status or erroneous measurements of phenotype or genotype, to name a few. When not properly accounted for, these sources of incompleteness may seriously jeopardize the credibility of results from analyses. In this paper we provide some perspectives on the occurrence and analysis of different forms of incomplete data in family‐based genetic association testing.