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author | rico |
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date | Fri, 06 Apr 2012 10:51:28 -0400 |
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<tool id="gd_population_structure" name="Population" version="1.0.0"> <description>structure</description> <command interpreter="python"> population_structure.py "$input" "${input.extra_files_path}/admix.ped" "$output" "$output.extra_files_path" "$populations" </command> <inputs> <param name="input" type="data" format="wped" label="Dataset" /> <param name="populations" type="integer" min="1" value="2" label="Number of populations" /> </inputs> <outputs> <data name="output" format="html" /> </outputs> <tests> <test> <param name="input" value="fake" ftype="wped" > <metadata name="base_name" value="admix" /> <composite_data value="genome_diversity/test_out/prepare_population_structure/prepare_population_structure.html" /> <composite_data value="genome_diversity/test_out/prepare_population_structure/admix.ped" /> <composite_data value="genome_diversity/test_out/prepare_population_structure/admix.map" /> <edit_attributes type="name" value="fake" /> </param> <param name="populations" value="2" /> <output name="output" file="genome_diversity/test_out/population_structure/population_structure.html" ftype="html" compare="diff" lines_diff="2"> <extra_files type="file" name="numeric.txt" value="genome_diversity/test_out/population_structure/numeric.txt" /> <extra_files type="file" name="graphical.pdf" value="genome_diversity/test_out/population_structure/graphical.pdf" compare="sim_size" delta="1000" /> </output> </test> </tests> <help> **What it does** The users selects a set of data generated by the Galaxy tool to "prepare to look for population structure", and specifies a number, K, of ancestral populations. The tool estimates the proportion of each individual's ancestry coming from each ancestral population. The proportions are shown both as numbers and graphically. **Acknowledgments** We use the program "Admixture", downloaded from http://www.genetics.ucla.edu/software/admixture/ and described in the paper "Fast model-based estimation of ancestry in unrelated individuals" by David H. Alexander, John Novembre and Kenneth Lange, Genome Research 19 (2009), pp. 1655-1664. </help> </tool>