Difference between revisions of "EIGENSOFT"
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EIGENSOFT uses PCA to correct for population stratification in medical association studies (EIGENSTRAT, Price et al. 2006) and to detect and analyze population structure (SMARTPCA, Patterson et al. 2006). | EIGENSOFT uses PCA to correct for population stratification in medical association studies (EIGENSTRAT, Price et al. 2006) and to detect and analyze population structure (SMARTPCA, Patterson et al. 2006). | ||
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| − | == | + | ==Environment Modules== |
| − | + | Run <code>module spider {{#var:app}}</code> to find out what environment modules are available for this application. | |
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==System Variables== | ==System Variables== | ||
| − | * HPC_{{uc:{{#var:app}}}}_DIR | + | * HPC_{{uc:{{#var:app}}}}_DIR - installation directory |
* HPC_{{uc:{{#var:app}}}}_BIN | * HPC_{{uc:{{#var:app}}}}_BIN | ||
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Latest revision as of 14:58, 15 August 2022
Description
EIGENSOFT uses PCA to correct for population stratification in medical association studies (EIGENSTRAT, Price et al. 2006) and to detect and analyze population structure (SMARTPCA, Patterson et al. 2006).
Environment Modules
Run module spider eigensoft to find out what environment modules are available for this application.
System Variables
- HPC_EIGENSOFT_DIR - installation directory
- HPC_EIGENSOFT_BIN
Citation
If you publish research that uses eigensoft you have to cite it as follows:
Price, Alkes L., et al. "Principal components analysis corrects for stratification in genome-wide association studies." Nature genetics 38.8 (2006): 904-909.
and
Patterson, Nick, Alkes L. Price, and David Reich. "Population structure and eigenanalysis." PLoS genetics 2.12 (2006): e190.