README.md

In markrobinsonuzh/treeAGG: Tree Aggregation

treeAGG

The arrangement of hypotheses in a hierarchical structure appears in many research fields and often indicates different resolutions at which data can be viewed. On which resolution level should the signal be intepreted has arisen researchers' interest. A flexible method to select resolution level, instead of cutting the tree structure at arbitary levels, is desired. Our package treeAGG, which uses minP algorithm, is a such tool. It does a bottom-up search for the optimal level of a tree to interpret signal by combining with current available tools, such as edgeR or DESeq2.

Installing

To install treeAGG package, you could run the code below in R

devtools::install_github("markrobinsonuzh/treeAGG")

How to use it

• Introduction to leafSummarizedExperiment and treeSummarizedExperiment
• Example of data analysis
• Example of simulations

markrobinsonuzh/treeAGG documentation built on May 26, 2019, 9:32 a.m.