numFeatures

numFeatures,aldex.clr-method

A <code>aldex.clr</code> object containing the Monte Carlo Dirochlet instances derived from estimating the technical variance of the raw read count data, along with sample and feature information.
  

.object


  Returns the number of features associated with the data, for an <code>aldex.clr</code> object.


A differential abundance analysis for the comparison of
two or more conditions. For example, single-organism and
meta-RNA-seq high-throughput sequencing assays, or of selected
and unselected values from in-vitro sequence selections. Uses a
Dirichlet-multinomial model to infer abundance from counts,
that has been optimized for three or more experimental
replicates. Infers sampling variation and calculates the
expected false discovery rate given the biological and sampling
variation using the Wilcox rank test or Welches t-test
(aldex.ttest) or the glm and Kruskal Wallis tests (aldex.glm).
Reports both P and fdr values calculated by the Benjamini
Hochberg correction.

Greg Gloor

ALDEx2

Analysis of differential abundance taking sample variation into
account

numFeatures function

A <code>aldex.clr</code> object containing the Monte Carlo Dirochlet instances derived from estimating the technical variance of the raw read count data, along with sample and feature information.

Returns the number of features associated with the data, for an <code>aldex.clr</code> object.

numFeatures: numFeatures

Description

Usage

Arguments

Value

Details

See Also

Examples