permutation_test {tna} | R Documentation |
Compare Two Networks from Sequence Data using a Permutation Test
Description
This function compares two networks built from sequence data using permutation tests. The function builds Markov models for two sequence objects, computes the transition probabilities, and compares them by performing permutation tests. It returns the differences in transition probabilities, effect sizes, estimated p-values, and confidence intervals.
Usage
permutation_test(x, ...)
## S3 method for class 'tna'
permutation_test(
x,
y,
adjust = "none",
iter = 1000,
paired = FALSE,
level = 0.05,
measures = character(0),
...
)
Arguments
x |
A |
... |
Additional arguments passed to |
y |
A |
adjust |
A |
iter |
An |
paired |
A |
level |
A |
measures |
A |
Value
A tna_permutation
object which is a list
with two elements:
edges
and centralities
, both containing the following elements:
-
stats
: Adata.frame
of original differences, effect sizes, and estimated p-values for each edge or centrality measure. The effect size is computed as the observed difference divided by the standard deviation of the differences of the permuted samples. -
diffs_true
: Amatrix
of differences in the data. -
diffs_sig
: Amatrix
showing the significant differences.
See Also
Validation functions
bootstrap()
,
deprune()
,
estimate_cs()
,
permutation_test.group_tna()
,
plot.group_tna_bootstrap()
,
plot.group_tna_permutation()
,
plot.group_tna_stability()
,
plot.tna_bootstrap()
,
plot.tna_permutation()
,
plot.tna_stability()
,
print.group_tna_bootstrap()
,
print.group_tna_permutation()
,
print.group_tna_stability()
,
print.summary.group_tna_bootstrap()
,
print.summary.tna_bootstrap()
,
print.tna_bootstrap()
,
print.tna_permutation()
,
print.tna_stability()
,
prune()
,
pruning_details()
,
reprune()
,
summary.group_tna_bootstrap()
,
summary.tna_bootstrap()
Examples
model_x <- tna(group_regulation[1:200, ])
model_y <- tna(group_regulation[1001:1200, ])
# Small number of iterations for CRAN
permutation_test(model_x, model_y, iter = 20)