Research areas as disparate as population genetics, systems biology, mathematical modelling of development and transcription profiling rely on quantitative descriptions, and statistical analysis — once a concept foreign to mainstream genetics — is pervading every aspect of the field.
The aim of the four reviews in this Focus issue on Statistical Analysis is to familiarize readers with the current and debated issues in this exciting area of genetics. The dialogue on the best solutions is ongoing, and all authors present their opinion on future trends. The articles are freely available for one month.
In conjunction with the Focus on Statistical Analysis, Nature Reviews Genetics presents an
audio supplement in which experts discuss how advances in statistics will aid genetic analyses.
From the Editors
Audio Supplement
Reviews
A tutorial on statistical methods for population association studies
David J. Balding
doi:10.1038/nrg1916
Nature Reviews Genetics 7, 781-791
Identifying polymorphisms that are overrepresented in disease cases versus controls would seem to be a straightforward process, but genetic association studies are notoriously riddled with complex analysis problems. This article outlines these statistical issues and provides some guidance to overcoming them.
Modern computational approaches for analysing molecular genetic variation data
Paul Marjoram & Simon Tavaré
doi:10.1038/nrg1961
Nature Reviews Genetics 7, 759-770
The vast increase in the amount of molecular genetic data that are being generated, and the scale of their complexity, demand ever more sophisticated statistical analysis methods — this article surveys and compares these approaches, and the growing reliance on computational methodologies.
Computer programs for population genetics data analysis: a survival guide
Laurent Excoffier and Gerald Heckel
doi:10.1038/nrg1904
Nature Reviews Genetics 7, 745-758
The increase in population genetics data has led to a parallel need for sophisticated analysis programs and packages. This article is intended as a guide to many of these statistical programs, to promote their more informed use.
Genetic-relatedness analysis: modern data and new challenges
Bruce S. Weir, Amy D. Anderson and Amanda B. Hepler
doi:10.1038/nrg1960
Nature Reviews Genetics 7, 771-780
The concept of relatedness is central to many fields, from human linkage analysis to forensics to animal and plant breeding. This review covers the statistical framework for studying relatedness, its applications and the challenges that the field faces.
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