detec_otus: An algrithm for phylogeny-aware differential abundance...
In liudoubletian/eBay: An empirical bayes approach to normalization
Description
Usage
Arguments
Value
Examples
Description
An algrithm for phylogeny-aware differential abundance detection
Usage
1
detec_otus(p.val, tree_table, tree, group, test.method, cutf, adj.m)
Arguments
p.val
the p value for each node
tree_table
a data set
tree
a phylogenetic tree among m taxa
group
a n-vector of group indicators
test.method
t-test or Wilcoxon rank sum test
cutf
level of significance
adj.m
the adjustment methods for p-values
Value
final.p the adjusted p values
dif.otus the set of differentially abundant OTUs
Examples
1
2
3
4
p <- 40
set.seed(1)
tree <- simulate_tree(p)
leaf_ind <- leaf_node_index(tree)
liudoubletian/eBay documentation built on Oct. 10, 2020, 8:43 p.m.
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Description Usage Arguments Value Examples
Description
An algrithm for phylogeny-aware differential abundance detection
Usage
1 | detec_otus(p.val, tree_table, tree, group, test.method, cutf, adj.m)
|
Arguments
p.val |
the p value for each node |
tree_table |
a data set |
tree |
a phylogenetic tree among m taxa |
group |
a n-vector of group indicators |
test.method |
t-test or Wilcoxon rank sum test |
cutf |
level of significance |
adj.m |
the adjustment methods for p-values |
Value
final.p the adjusted p values
dif.otus the set of differentially abundant OTUs
Examples
1 2 3 4 | p <- 40
set.seed(1)
tree <- simulate_tree(p)
leaf_ind <- leaf_node_index(tree)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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