View source: R/contribution_interpretation.R
run.trait.association.single | R Documentation |
Computes test statistics for all possible group assignments of samples defined in medecom.set
and rnb.set
and stores
heatmaps of p-values on the given location only for a given CG Subset, K and lambda.
run.trait.association.single(
medecom.set,
pheno.data,
cg_subset = NULL,
K = NULL,
lambda = NULL,
test.fun = t.test
)
medecom.set |
An object of type |
pheno.data |
An object of type |
cg_subset |
The cg_subset of interest |
K |
The selected value for number of LMCs (K) |
lambda |
The selected value of the regularizer (lambda) |
test.fun |
Test statistic used to compute p-values of differences between LMC contributions in pairwise sample comparisons.
Defaults to |
Returns a list with two elements, each a heatmap as a ggplot object for the given medecom.set
, cg_subset
K
and lambda
.
The elements correpond to p-values of correlation ("quantivative") and t-tests ("qualitative") traits.
The p-values are produced by comparing the LMC contributions in all sample comparisons defined by rnb.sample.groups
on rnb.set
. The employed test statistic for pariwise comparison can be specified by test.fun
, for groups defining more than one group kruskal.test
is employed. P-values lower than 0.01 are added to the heatmap.
Michael Scherer
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