Extract a table with the top-ranked nodes from a DA/DS analysis output
(generated by runDA
or runDS
).
nodeResult(
object,
n = 10,
type = c("DA", "DS"),
adjust_method = "BH",
sort_by = "PValue",
p_value = 1
)
An integer indicating the maximum number of entities to return.
Either "DA" (for object from runDA
) or
"DS" (for object from runDS
).
A character string specifying the method used to adjust
p-values for multiple testing. See p.adjust
for
possible values.
A character string specifying the sorting method. This will
be passed to topTags
.
Possibilities are "PValue" for p-value, "logFC" for absolute log-fold
change or "none" for no sorting.
A numeric cutoff value for adjusted p-values. This will
be passed to topTags
. Only entities
with adjusted p-values equal or lower than specified are returned.
A data frame with results for all nodes passing the imposed
thresholds. The columns logFC, logCPM,
PValue, FDR, F (or LR) are from (the
output table of) topTags
. The node column
stores the node number for each entity. Note: FDR is corrected
over all features and nodes when the specified type = "DS"
.
suppressPackageStartupMessages({
library(TreeSummarizedExperiment)
})
lse <- readRDS(system.file("extdata", "da_sim_100_30_18de.rds",
package = "treeclimbR"))
tse <- aggTSE(lse, rowLevel = showNode(tree = rowTree(lse),
only.leaf = FALSE))
dd <- model.matrix( ~ group, data = colData(tse))
out <- runDA(TSE = tse, feature_on_row = TRUE,
assay = "counts", option = "glmQL",
design = dd, contrast = NULL,
normalize = TRUE)
## Top 10 nodes with DA
nodeResult(out, n = 10)
#> node logFC logCPM F PValue FDR
#> alias_102 102 -0.6706780 18.47290 231.04391 2.567112e-20 2.336072e-18
#> alias_114 114 -0.6164477 17.74557 135.10962 8.813464e-16 4.010126e-14
#> alias_115 115 -0.6363735 17.40596 123.63523 4.384311e-15 1.329908e-13
#> alias_103 103 -0.7519304 17.17217 111.01367 2.912860e-14 6.626757e-13
#> alias_116 116 -0.7205022 16.78934 80.52027 5.717260e-12 1.040541e-10
#> alias_118 118 -0.6862480 16.51284 70.66241 4.142814e-11 6.283268e-10
#> alias_110 110 -0.8660117 16.18212 63.30221 2.032403e-10 2.642123e-09
#> alias_101 101 -0.1640957 19.93063 61.48320 3.054810e-10 3.474847e-09
#> alias_112 112 -0.8746824 15.41939 46.02939 1.349250e-08 1.364241e-07
#> alias_120 120 -0.8760583 15.82848 36.61908 1.863860e-07 1.619594e-06