## ----include=FALSE, messages=FALSE, warnings=FALSE----------------------------
knitr::opts_chunk$set(message=FALSE, fig.width=6.75)
devtools::load_all(".")
library(tidyverse)
library(magrittr)
library(dplyr)
library(reactable)

## ---- eval=FALSE--------------------------------------------------------------
#  
#  devtools::install_github("montilab/hypeR")
#  

## ---- eval=FALSE--------------------------------------------------------------
#  
#  BiocManager::install("montilab/hypeR", version="devel")
#  

## ----eval=FALSE---------------------------------------------------------------
#  conda create --name hyper
#  source activate hyper
#  conda install -c r r-devtools
#  R
#  library(devtools)
#  devtools::install_github("montilab/hypeR")

## ----eval=FALSE---------------------------------------------------------------
#  git clone https://github.com/montilab/hypeR
#  nano hypeR/DESCRIPTION
#  # Change Line 8
#  # Depends: R (>= 3.6.0) -> Depends: R (>= 3.5.0)
#  R
#  install.packages("path/to/hypeR", repos=NULL, type="source")

## ---- eval=FALSE--------------------------------------------------------------
#  
#  library(hypeR)
#  

## -----------------------------------------------------------------------------

# Simply a character vector of symbols (hypergeometric)
signature <- c("GENE1", "GENE2", "GENE3")

# A ranked character vector of symbols (kstest)
ranked.signature <- c("GENE2", "GENE1", "GENE3")

# A ranked named numerical vector of symbols with ranking weights (gsea)
weighted.signature <- c("GENE2"=1.22, "GENE1"=0.94, "GENE3"=0.77)


## -----------------------------------------------------------------------------

genesets <- list("GSET1" = c("GENE1", "GENE2", "GENE3"),
                 "GSET2" = c("GENE4", "GENE5", "GENE6"),
                 "GSET3" = c("GENE7", "GENE8", "GENE9"))


## -----------------------------------------------------------------------------

hypdat <- readRDS(file.path(system.file("extdata", package="hypeR"), "hypdat.rds"))


## -----------------------------------------------------------------------------

limma <- hypdat$limma
reactable(limma)


## -----------------------------------------------------------------------------

genesets <- msigdb_gsets("Homo sapiens", "C2", "CP:KEGG")


## -----------------------------------------------------------------------------

signature <- limma %>% filter(t > 0 & fdr < 0.001) %>% use_series(symbol)


## -----------------------------------------------------------------------------

length(signature)
head(signature)


## -----------------------------------------------------------------------------

hyp_obj <- hypeR(signature, genesets, test="hypergeometric", background=50000, fdr=0.01, plotting=TRUE)
hyp_obj$plots[[1]]


## -----------------------------------------------------------------------------

signature <- limma %>% arrange(desc(t)) %>% use_series(symbol)


## -----------------------------------------------------------------------------

length(signature)
head(signature)


## -----------------------------------------------------------------------------

hyp_obj <- hypeR(signature, genesets, test="kstest", fdr=0.05, plotting=TRUE)
hyp_obj$plots[[1]]


## -----------------------------------------------------------------------------

signature <- limma %>% arrange(desc(t)) %>% select(symbol, t) %>% deframe()


## -----------------------------------------------------------------------------

length(signature)
head(signature)


## -----------------------------------------------------------------------------

hyp_obj <- hypeR(signature, genesets, test="kstest", fdr=0.05, plotting=TRUE)
hyp_obj$plots[[1]]


## -----------------------------------------------------------------------------

print(hyp_obj)


## ---- eval=FALSE--------------------------------------------------------------
#  
#  # Show interactive table
#  hyp_show(hyp_obj)
#  
#  # Plot dots plot
#  hyp_dots(hyp_obj)
#  
#  # Plot enrichment map
#  hyp_emap(hyp_obj)
#  
#  # Plot hiearchy map
#  hyp_hmap(hyp_obj)
#  
#  # Save to excel
#  hyp_to_excel(hyp_obj)
#  
#  # Save to table
#  hyp_to_table(hyp_obj)
#  
#  # Generate markdown report
#  hyp_to_rmd(hyp_obj)
#