Bayesian Logic Regression for SNP Data
BeschreibungAdvances in genetic sequencing technology make it possible to study the effect of genetic variations on the risk of developing a complex disease, such as cancer. The most common form of genetic variations are the Single Nucleotide Polymorphisms (SNPs). Logic regression is a powerful statistical tool for identifying interactions of SNPs that might be associated with a disease. Logic regression however only finds a single best fitting model for the data, while usually there are many models that fit almost equally well. The author Arno Fritsch shows how by embedding logic regression in the framework of Bayesian statistics this drawback can be overcome.
The book gives an introduction to both logic regression and Bayesian statistics and shows how the two can be combined. It is demonstrated that considering more than one plausible logic regression model can substantially improve predictions of the disease status. The book is intended for bioinformaticians, epidemiologists and statisticians involved in analyzing SNP data.
PortraitArno Fritsch was born 1979 in Meerbusch/Germany. From 2000 to 2006 he studied Statistics at the Technische Universität Dortmund where he obtained a Diploma (Masters) degree with distinction. Since 2006 he is working as a Research and Teaching Assistant at the Technische Universität Dortmund. He is married and lives in Dortmund.
Untertitel: Paperback. Sprache: Englisch.
Verlag: VDM Verlag
Erscheinungsdatum: Juli 2008
Seitenanzahl: 80 Seiten