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Sample Planning Optimization Tool for conservation and population Genetics ( SPOTG ): a software for choosing the appropriate number of markers and samples
Author(s) -
Hoban Sean,
Gaggiotti Oscar,
Bertorelle Giorgio
Publication year - 2013
Publication title -
methods in ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.425
H-Index - 105
ISSN - 2041-210X
DOI - 10.1111/2041-210x.12025
Subject(s) - bottleneck , sampling (signal processing) , computer science , sample (material) , software , population , population genetics , sample size determination , documentation , data science , data mining , machine learning , statistics , mathematics , chemistry , demography , filter (signal processing) , chromatography , sociology , programming language , computer vision , embedded system
Summary Genetic data are frequently used to make inferences about evolutionary and ecological processes, but the choice of the number of genetic markers and samples for such studies is usually ad hoc . Unfortunately, suboptimal sampling routinely leads to ambiguous results. spotg is a user‐friendly software for optimizing sampling strategy for five common genetic study topics: hybridization, temporal sampling, bottlenecks, connectivity and assignment. spotg facilitates formal evaluation of the expected statistical power of proposed sampling strategies before project implementation, by using stochastic genetic simulations of realistic population scenarios and various sampling schemes. We demonstrate use of the tool with two example species (lynx and bison) in which demographic history differs; the appropriate sampling strategy for detecting a genetic bottleneck differs dramatically between the two cases, with important implications for sample planning. spotg has an interactive graphical tool for exploring results, and extensive documentation, tips and tutorials to enable use by conservation managers, ecologists beginning to use genetics and students.