Difference between revisions of "CatchAll"
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{{Bioinformatics application | {{Bioinformatics application | ||
|sw summary=Estimate ecological diversity with both parametric and non-parametric estimators. | |sw summary=Estimate ecological diversity with both parametric and non-parametric estimators. | ||
− | |bio domain= | + | |bio domain=Population genetics, pyrotags, Metagenomics, |
− | |bio method=Maximum likelihood, | + | |
+ | |bio method=Maximum likelihood, | ||
|created by=John Bunge | |created by=John Bunge | ||
|created at=Cornell University | |created at=Cornell University |
Revision as of 12:27, 5 September 2011
Application data |
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Created by | John Bunge |
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Biological application domain(s) | Population genetics, pyrotags, Metagenomics |
Principal bioinformatics method(s) | Maximum likelihood |
Created at | Cornell University |
Maintained? | Yes |
Summary: Estimate ecological diversity with both parametric and non-parametric estimators.
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Description
CatchAll is a fast, easy-to-use, platform independent software package which applies optimized numerical searching to compute maximum likelihood estimates for finite-mixture models; linear regression-based models with non-diagonal weight matrices; as well as all existing simple nonparametric methods; while accounting for outlier detection/deletion and other data-analytic considerations. Given sample “frequency count” data, CatchAll computes 12 different diversity estimates and compares the results via a model-selection algorithm, providing the user with a best overall choice, along with close competitors. It is accompanied by an Excel-based graphical display spreadsheet program.
Links
References
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