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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