Abstract:
:After an association between genetic variants and a phenotype has been established, further study goals comprise the classification of patients according to disease risk or the estimation of disease probability. To accomplish this, different statistical methods are required, and specifically machine-learning approaches may offer advantages over classical techniques. In this paper, we describe methods for the construction and evaluation of classification and probability estimation rules. We review the use of machine-learning approaches in this context and explain some of the machine-learning algorithms in detail. Finally, we illustrate the methodology through application to a genome-wide association analysis on rheumatoid arthritis.
journal_name
Hum Genetjournal_title
Human geneticsauthors
Kruppa J,Ziegler A,König IRdoi
10.1007/s00439-012-1194-ysubject
Has Abstractpub_date
2012-10-01 00:00:00pages
1639-54issue
10eissn
0340-6717issn
1432-1203journal_volume
131pub_type
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