View source: R/fitDistribution.R
Fit a truncated gaussian hurdle model for each taxon of the count data. The
hurdle model estimation procedure is performed by MAST
function without assuming the presence of any group in the samples (design
matrix equal to a column of ones.)
fitHURDLE(object, assay_name = "counts", scale = "default", verbose = TRUE)
a phyloseq object, a TreeSummarizedExperiment object, or a matrix of counts.
the name of the assay to extract from the
TreeSummarizedExperiment object (default
Character vector, either
an optional logical value. If
A data frame containing the continuity corrected logarithms of the
average fitted values for each row of the matrix of counts in the
column, and the estimated probability to observe a zero in the
# Generate some random counts counts = matrix(rnbinom(n = 60, size = 3, prob = 0.5), nrow = 10, ncol = 6) # Fit model on the counts matrix HURDLE <- fitHURDLE(counts, scale = "median") head(HURDLE)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.