Seven common mistakes in population genetics and how to avoid them

As the data resulting from modern genotyping tools are astoundingly complex, genotyping studies require great care in the sampling design, genotyping, data analysis and interpretation. Such care is necessary because, with data sets containing thousands of loci, small biases can easily become strongl...

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Veröffentlicht in:	Molecular ecology 2015-07, Vol.24 (13), p.3223-3231
1. Verfasser:	Meirmans, Patrick G.
Format:	Artikel
Sprache:	eng
Schlagworte:	amova Cluster Analysis clustering Data Interpretation, Statistical Genetic Variation Genetics, Population - methods genome scan Genotype & phenotype Genotyping Techniques - methods Geography Mantel test Population genetics population structure Research Design unicorns
Online-Zugang:	Volltext
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