Description Usage Arguments Details Value Author(s) References See Also Examples
Welcome to the ALDEx2
package!
The aldex
function is a wrapper that performs logratio transformation
and statistical testing in a single line of code. Specifically, this function:
(a) generates Monte Carlo samples of the Dirichlet distribution for each sample,
(b) converts each instance using a logratio transform, then (c) returns test
results for two sample (Welch's t, Wilcoxon) or multisample (glm, KruskalWallace)
tests. This function also estimates effect size for two sample analyses.
1 2 3 
reads 
A nonnegative, integeronly 
conditions 
A character vector. A description of the data structure used
for testing. Typically, a vector of group labels. For 
mc.samples 
An integer. The number of Monte Carlo samples to use when estimating the underlying distributions. Since we are estimating central tendencies, 128 is usually sufficient. 
test 
A character string. Indicates which tests to perform. "t" runs
Welch's t and Wilcoxon tests. "kw" runs KruskalWallace and glm tests.
"glm" runs a generalized linear model using a 
effect 
A boolean. Toggles whether to calculate abundances and effect sizes.
Applies to 
include.sample.summary 
A boolean. Toggles whether to include median clr
values for each sample. Applies to 
verbose 
A boolean. Toggles whether to print diagnostic information while
running. Useful for debugging errors on large datasets. Applies to

denom 
A character string. Indicates which features to retain as the denominator for the Geometric Mean calculation. Using "iqlr" accounts for data with systematic variation and centers the features on the set features that have variance that is between the lower and upper quartile of variance. Using "zero" is a more extreme case where there are many nonzero features in one condition but many zeros in another. In this case the geometric mean of each group is calculated using the set of pergroup nonzero features. 
iterate 
A boolean. Toggles whether to iteratively perform a test. For example, this will use the results from an initial "t" routine to seed the reference (i.e., denominator of Geometric Mean calculation) for a second "t" routine. 
... 
Arguments to embedded method (e.g., 
See "Examples" below for a description of the sample input.
Returns a number of values that depends on the set of options. See the return values of aldex.ttest, aldex.kw, aldex.glm, and aldex.effect for explanations and examples.
Greg Gloor, Andrew Fernandes, and Matt Links contributed to the original package. Thom Quinn added the "glm" test method, the "corr" test method, and the "iterate" procedure.
Please use the citation given by
citation(package="ALDEx2")
.
aldex
,
aldex.clr
,
aldex.ttest
,
aldex.kw
,
aldex.glm
,
aldex.effect
,
aldex.corr
,
selex
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18  # The 'reads' data.frame should have row
# and column names that are unique, and
# looks like the following:
#
# T1a T1b T2 T3 N1 N2 Nx
# Gene_00001 0 0 2 0 0 1 0
# Gene_00002 20 8 12 5 19 26 14
# Gene_00003 3 0 2 0 0 0 1
# Gene_00004 75 84 241 149 271 257 188
# Gene_00005 10 16 4 0 4 10 10
# Gene_00006 129 126 451 223 243 149 209
# ... many more rows ...
data(selex)
selex < selex[1201:1600,] # subset for efficiency
conds < c(rep("NS", 7), rep("S", 7))
x < aldex(selex, conds, mc.samples=2, denom="all",
test="t", effect=FALSE)

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