README.md

In benliemory/adaptiveHM: Adaptive Hierarchical Model (adaptiveHM)

adaptiveHM

Historical Rank-based Adaptive Hierarchical Model

Quick Installation Guide:

If R package "devtools" has been loaded, adaptiveHM can be easily installed by following:

library(devtools)

install_github(repo = "benliemory/adaptiveHM")

A Simple Example:

library(adaptiveHM)

##### Load Example Data

data(ExampleData)

##### Using stHM with historical information frin IPBT prior ##### IPBT id 35 indicates normal heart data

##### Step I: Use GDM to determine optimal group number (Step I can be omitted if group number has been decided)

GDMs = GDM_stHM_figure(ExampleData$Control, IPBT.prior=TRUE,IPBT.id=35,groupRanges = 1:200)

##### From GDM figure, we use 50 groups in stHM

##### Step II: Obtain DE gene list from Stratified Hierarchial model DE_gene_lists_stHM = adaptiveHM.main.stHM(ExampleData$Control,ExampleData$Treatment, IPBT.prior=TRUE,IPBT.id=35, groupNumber = 50 )

##### Load 10 samples of normal heart data as external historical information

data(history)

##### Using swHM with external data as historical data

##### Step I: Use GDM to determine optimal window size (Step I can be omitted if window size has been decided)

GDMs_swHM = GDM_swHM_figure(ExampleData$Control, IPBT.prior = FALSE,history = history, winSizeRanges = seq(from = 5,to = 200,by = 5) )

##### From GDM figure, we use 10 as window size for swHM

##### Step II: Obtain DE gene list from Stratified Hierarchial model ##### Notice: Window size here refers to one side window size. The whole window is 2*window_size + 1

DE_gene_lists_swHM = adaptiveHM.main.swHM(ExampleData$Control,ExampleData$Treatment, IPBT.prior = FALSE,history = history, winSize = 10)

Reference

Li B, Sun Z, He Q, Zhu Y, Qin ZS (2015) Bayesian inference with historical data-based informative priors improves detection of differentially expressed genes Bioinformatics (Oxford, England) doi:10.1093/bioinformatics/btv631

Li B, Li Y, Qin Z. (2016) Improving hierarchical models using historical data with applications in high throughput genomics data analysis. Statistics in Biosciences. 1-18.

benliemory/adaptiveHM documentation built on May 12, 2019, 12:57 p.m.