## ----setup, include = FALSE, echo = FALSE-------------------------------------
knitr::opts_chunk$set(echo = TRUE, 
warning = FALSE, 
message = FALSE, 
fig.height = 7, 
fig.width=7, 
fig.align = "center")
library(knitr)

## ----echo=FALSE---------------------------------------------------------------
library(ggplot2)
library(ggpubr)
library(plotly)

## ----eval=FALSE---------------------------------------------------------------
# library(volcano3D)
# 
# # Basic DESeq2 set up
# library(DESeq2)
# 
# counts <- matrix(rnbinom(n=3000, mu=100, size=1/0.5), ncol=30)
# rownames(counts) <- paste0("gene", 1:100)
# cond <- rep(factor(rep(1:3, each=5), labels = c('A', 'B', 'C')), 2)
# resp <- factor(rep(1:2, each=15), labels = c('non.responder', 'responder'))
# metadata <- data.frame(drug = cond, response = resp)
# 
# # Full dataset object construction
# dds <- DESeqDataSetFromMatrix(counts, metadata, ~response)
# 
# # Perform 3x DESeq2 analyses comparing binary response for each drug
# res <- deseq_2x3(dds, ~response, "drug")

## ----eval=FALSE---------------------------------------------------------------
# library(easylabel)
# df <- as.data.frame(res[[1]])  # results for the first drug
# easyVolcano(df)

## ----eval=FALSE---------------------------------------------------------------
# # Generate polar object
# obj <- deseq_2x3_polar(res)
# 
# # 2d plot
# radial_plotly(obj)
# 
# # 3d plot
# volcano3D(obj)

## ----eval=FALSE---------------------------------------------------------------
# obj <- deseq_2x3_polar(data1)
# labs <- c('MS4A1', 'TNXA', 'FLG2', 'MYBPC1')
# radial_plotly(obj, type=2, label_rows = labs) %>% toWebGL()

## ----radial_2x3_pos, echo = FALSE, message=FALSE, fig.align='center', out.width='70%', out.extra='style="border: 0;"'----
knitr::include_graphics("radial_2x3_pos.png")

## ----volc_2x3, echo = FALSE, message=FALSE, fig.align='center', out.width='70%', out.extra='style="border: 0;"'----
knitr::include_graphics("volc3d_2x3.png")

## ----eval=FALSE---------------------------------------------------------------
# obj <- deseq_2x3_polar(data1, process = "negative")
# labs <- c('MS4A1', 'TNXA', 'FLG2', 'MYBPC1')
# radial_plotly(obj, type=2, label_rows = labs) %>% toWebGL()

## ----radial_2x3_neg, echo = FALSE, message=FALSE, fig.align='center', out.width='70%', out.extra='style="border: 0;"'----
knitr::include_graphics("radial_2x3_neg.png")

## ----eval=FALSE---------------------------------------------------------------
# polar_obj <- polar_coords_2x3(vstdata, metadata, "ACR.response.status",
#                               "Randomised.Medication")
# 
# radial_plotly(polar_obj, type=2)
# volcano3D(polar_obj)

## ----eval=FALSE---------------------------------------------------------------
# forest_ggplot(obj, c("MS4A1", "FLG2", "SFN")

## ----forest, echo = FALSE, message=FALSE, fig.align='center', out.width='70%', out.extra='style="border: 0;"'----
knitr::include_graphics("forest.png")

## -----------------------------------------------------------------------------
citation("volcano3D")