Estimating population diversity with CatchAll
ABSTRACT 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.
Full-textDOI: · Available from: James Arthur Foster, Jul 31, 2015
- SourceAvailable from: Trista Vick-Majors
[Show abstract] [Hide abstract]
- "Parametric alpha diversity estimates for Bacteria and Archaea were calculated using CatchAll version 3 . 2 ( Bunge et al . , 2012 ) , and eukaryotic nonparametric ( Chao2 ) richness estimates ( Chao , 1987 ) were calcu - lated with the program SPADE ( Chao and Shen , 2010 ) . All calculations were performed on pooled sequences from duplicate samples for bacteria and archaea and separate replicated samples for euka - ryotes . We performed these calculations using f"
ABSTRACT: High-latitude environments, such as the Antarctic McMurdo Dry Valley lakes, are subject to seasonally segregated light-dark cycles, which have important consequences for microbial diversity and function on an annual basis. Owing largely to the logistical difficulties of sampling polar environments during the darkness of winter, little is known about planktonic microbial community responses to the cessation of photosynthetic primary production during the austral sunset, which lingers from approximately February to April. Here, we hypothesized that changes in bacterial, archaeal and eukaryotic community structure, particularly shifts in favor of chemolithotrophs and mixotrophs, would manifest during the transition to polar night. Our work represents the first concurrent molecular characterization, using 454 pyrosequencing of hypervariable regions of the small-subunit ribosomal RNA gene, of bacterial, archaeal and eukaryotic communities in permanently ice-covered lakes Fryxell and Bonney, before and during the polar night transition. We found vertically stratified populations that varied at the community and/or operational taxonomic unit-level between lakes and seasons. Network analysis based on operational taxonomic unit level interactions revealed nonrandomly structured microbial communities organized into modules (groups of taxa) containing key metabolic potential capacities, including photoheterotrophy, mixotrophy and chemolithotrophy, which are likely to be differentially favored during the transition to polar night.The ISME Journal 10/2013; DOI:10.1038/ismej.2013.190 · 9.27 Impact Factor
[Show abstract] [Hide abstract]
- "Analysis of alpha and beta diversity Estimates of alpha diversity were calculated in MOTHUR. These estimates included the observed OTU richness, the Good's coverage (Good, 1953), the parametric 'best fit' richness estimation CatchAll (Bunge et al., 2012) and the Shannon diversity index (Magurran, 2004, Haegeman et al., 2013). As alpha diversity measures are sensitive to differences in sampling effort, estimates were calculated based on data sets that were randomly subsampled to the same number of sequences. "
ABSTRACT: Soil compaction is a major disturbance associated with logging, but we lack a fundamental understanding of how this affects the soil microbiome. We assessed the structural resistance and resilience of the microbiome using a high-throughput pyrosequencing approach in differently compacted soils at two forest sites and correlated these findings with changes in soil physical properties and functions. Alterations in soil porosity after compaction strongly limited the air and water conductivity. Compaction significantly reduced abundance, increased diversity, and persistently altered the structure of the microbiota. Fungi were less resistant and resilient than bacteria; clayey soils were less resistant and resilient than sandy soils. The strongest effects were observed in soils with unfavorable moisture conditions, where air and water conductivities dropped well below 10% of their initial value. Maximum impact was observed around 6-12 months after compaction, and microbial communities showed resilience in lightly but not in severely compacted soils 4 years post disturbance. Bacteria capable of anaerobic respiration, including sulfate, sulfur, and metal reducers of the Proteobacteria and Firmicutes, were significantly associated with compacted soils. Compaction detrimentally affected ectomycorrhizal species, whereas saprobic and parasitic fungi proportionally increased in compacted soils. Structural shifts in the microbiota were accompanied by significant changes in soil processes, resulting in reduced carbon dioxide, and increased methane and nitrous oxide emissions from compacted soils. This study demonstrates that physical soil disturbance during logging induces profound and long-lasting changes in the soil microbiome and associated soil functions, raising awareness regarding sustainable management of economically driven logging operations.The ISME Journal advance online publication, 12 September 2013; doi:10.1038/ismej.2013.141.The ISME Journal 09/2013; DOI:10.1038/ismej.2013.141 · 9.27 Impact Factor
[Show abstract] [Hide abstract]
- "The sequences were grouped into operational taxonomic units (OTUs) based on their distances from each other. The estimation of total diversity was performed using the CatchAll program (Bunge et al., 2012). Taxonomic identification of sequences was performed using the RDP Classifier (Cole et al., 2009). "
ABSTRACT: a b s t r a c t The two alder species, black alder (Alnus glutinosa (L.) Gaertn.) and grey alder (Alnus incana (L.) Moench) are known to be pioneer species in the succession of new land areas, and important tree species in renew-able biomass production, the restoration of post-mining sites and riparian forest ecosystems. We analyzed the influence of soil physico-chemical characteristics (soil water content, pH KCl , total N, soluble P, organic matter content, C and N ratio, and elemental content) on bacterial community structure based on pyrose-quencing analysis of the 16S rRNA gene V2 and partly V3 region in two black and two grey alder stand soils with different management histories. The analyses revealed clear differences in all the measured chemical characteristics of studied soils. All the studied stands also had distinct soil bacterial communi-ties, and the number of shared species was low. In all stands species from phylum Proteobacteria were dominant, and the next phyla by percentage were Bacteroidetes and Actinobacteria. At the family level, Chitinophagaceae and Bradyrhizobiaceae species dominated. The obtained bacterial community Inverted Simpson's diversity indices showed no difference between the studied sites. The alder species did not affect soil bacterial community structure. Distance-based regression analysis indicated that soil pH value, water content, soluble phosphorus concentration and also total boron, cadmium, and aluminium con-tent were related to the variation of soil bacterial community structure in alder stand soils. The results of this study emphasize the importance of soil geomorphological properties in addition to soil physical and chemical characteristics in the formation of soil bacterial community structure during restoration of exhausted open mining areas, management of abandoned agricultural lands, and short rotation forests with different alder species.Ecological Engineering 12/2012; 49:10-17. DOI:10.1016/j.ecoleng.2012.08.034 · 3.04 Impact Factor