Estimating population diversity with CatchAll

Bunge, John, Woodard, Linda, Böhning, Dankmar, Foster, James, Connolly, Sean and Allen, Heather (2012) Estimating population diversity with CatchAll. Bioinfomatics, 28, (7), 1045-1047. (doi:10.1093/bioinformatics/bts075). (PMID:22333246).


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Motivation: The massive data produced by next-generation sequencing require advanced statistical tools. We address estimating the total diversity or species richness in a population. To date, only relatively simple methods have been implemented in available software. There is a need for software employing modern, computationally intensive statistical analyses including error, goodness-of-fit and robustness assessments.
Results: We present CatchAll, a fast, easy-to-use, platform-independent program that computes maximum likelihood estimates for finite-mixture models, weighted linear regression-based analyses and coverage-based non-parametric methods, along with outlier diagnostics. Given sample ‘frequency count’ data, CatchAll computes 12 different diversity estimates and applies a model-selection algorithm. CatchAll also derives discounted diversity estimates to adjust for possibly uncertain low-frequency counts. It is accompanied by an Excel-based graphics program.
Availability: Free executable downloads for Linux, Windows and Mac OS, with manual and source code, at

Item Type: Article
Digital Object Identifier (DOI): doi:10.1093/bioinformatics/bts075
ISSNs: 1460-2059 (electronic)
1367-4803 (print)
Subjects: H Social Sciences > HA Statistics
Q Science > QA Mathematics
Q Science > QH Natural history > QH301 Biology
Divisions : Faculty of Medicine > Primary Care and Population Sciences
Faculty of Social and Human Sciences > Mathematical Sciences > Statistics
Faculty of Social and Human Sciences > Southampton Statistical Sciences Research Institute
ePrint ID: 337593
Accepted Date and Publication Date:
15 March 2012Published
13 February 2012Made publicly available
Date Deposited: 30 Apr 2012 09:47
Last Modified: 31 Mar 2016 14:26

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