Accessory function to OTUsummary function
● Data Source:
CranContrib
● Keywords:
● Alias: mcmc.pval
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Symbiodinium sp. ITS2 OTUs from Orbicella franksi and O. faveolata corals at the Flower Garden Banks. Two banks (east and west), two coral species, five OTUs.
● Data Source:
CranContrib
● Keywords:
● Alias: green.data
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Samples are removed if their total counts fall below the specified z-score cutoff (default -2.5); OTUs are removed if their sum of counts is less than specified fraction of total counts (default 0.001), or if they are observed in less than specified fraction of all samples (default 0.2). Samples are removed first, then OTUs.
● Data Source:
CranContrib
● Keywords:
● Alias: purgeOutliers
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This function is called automatically by OTUsummary() and also can be used separately to plot the results produced by OTUsummary() with more plotting options
● Data Source:
CranContrib
● Keywords:
● Alias: summaryPlotOTU
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Trawls otuWise summary tables in the data returned by OTUsummary and returns the names of OTUs that have p-values better than the specified cutoff.
● Data Source:
CranContrib
● Keywords:
● Alias: signifOTU
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Generates a table of model-derived log2-transformed OTU abundances without sample effects (i.e., corresponding to predicted normalized data)
● Data Source:
CranContrib
● Keywords:
● Alias: getNormalizedOTUdata
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Normalizes counts based on total counts per sample, then uses log-linear-hybrid transformation on the data.
● Data Source:
CranContrib
● Keywords:
● Alias: logLin
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This package enables MCMC-based generalized linear mixed model analysis of multivariate counts data, such as common in DNA metabarcoding and community ecology. The results are summarized and plotted using ggplot2 functions.
● Data Source:
CranContrib
● Keywords:
● Alias: MCMC.OTU, MCMC.OTU-package
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works as upper.panel or lower.panel argument of pairs() (package graphics).
● Data Source:
CranContrib
● Keywords:
● Alias: panel.cor
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Looks at autocorrelation among sampled parameter values.
● Data Source:
CranContrib
● Keywords:
● Alias: otuByAutocorr
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