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<title>software | Statistical Diversity Lab</title>
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<h2>software</h2>
<p>statistical diversity lab</p>
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<p></p>
<p>We are not very good at updating our website. We much prefer working on our projects and software!</p>
<p>That said, you can see what we've been working on lately on <a href="https://github.com/statdivlab/" target="_blank">GitHub</a> and <a href="https://scholar.google.com/citations?hl=en&user=pFlAtDsAAAAJ&view_op=list_works&sortby=pubdate" target="_blank">Google Scholar</a>.</p>
<p>Below you can find an incomplete list of our open-source source.</p>
<p>================================================================================================================</p>
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<p><code>radEmu</code> estimates changes in the abundance of microbial taxa using high-throughput sequencing data. <code>radEmu</code> makes reasonable and empirically validated assumptions to estimate changes in the "absolute abundance" of taxa, where "absolute abundance" could be interpreted on the cell count, cell concentration or DNA concentration scale. Yes! From high-throughput sequencing data! It's true!</p>
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<p><code>breakaway</code> is the premier package for statistical analysis of taxonomic richness. <code>breakaway</code> implements a wide variety of estimates of taxonomic richness, as well as methods for modeling diversity is a function of covariates.</p>
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<p><code>corncob</code> is an <code>R</code> package for modeling relative abundance and testing hypotheses about the effect of covariates on relative abundance. The <code>corncob</code> methodology was specifically developed for modelling microbial abundances based on high throughput sequencing data, such as 16S or whole-genome sequencing. Check out <a href="https://projecteuclid.org/euclid.aoas/1587002666">the paper</a> for more details.</p>
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<p><code>paramedic</code> is a R package for estimating microbial concentration. <code>paramedic</code> uses information from 16S count data (compositional data on all taxa) and absolute data on a subset of taxa (e.g., qPCR or flow cytometry) to estimate the absolute abundance of all taxa. The method accounts for differing taxon detection efficiencies between the two methods, and produces prediction and confidence intervals as well as point estimates of the absolute abundance of all taxa. Check out <a href="https://www.biorxiv.org/content/10.1101/761486v1">the preprint</a> for more details.</p>
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<p><font face="monospace">DivNet</font> is an <code>R</code> package for estimating alpha and beta diversity in ecological communities, including the Shannon, Simpson, Bray-Curtis, and Euclidean indices. Unlike other methods, DivNet utilizes covariate and replicate information ("metadata") and models taxa in the ecosystem interacting and co-occuring. Check out <a href="https://academic.oup.com/biostatistics/advance-article-abstract/doi/10.1093/biostatistics/kxaa015/5841114">the paper</a> for more details.</p>
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