## ----setup, echo=FALSE, results='hide', warning=FALSE, error=FALSE, message=FALSE, cache=FALSE----
library(knitr)
opts_chunk$set(
  cache = FALSE,
  echo = TRUE,
  warning = FALSE,
  error = FALSE,
  message = FALSE
)

## ----libraries, message=FALSE-------------------------------------------------
library(progeny)
library(tibble)
library(tidyr)
library(dplyr)
library(pheatmap)
library(readr)
library(ggplot2)

## ----loadInput, message=FALSE-------------------------------------------------
## We assign the normalised counts and the experimental design 
data("vignette_data")

Normalised_counts <- vignette_data$counts
Experimental_design <- vignette_data$design

## We read the results from the differential analysis. 
ttop_KOvsWT <- vignette_data$limma_ttop

## -----------------------------------------------------------------------------
Normalised_counts_matrix <- Normalised_counts %>% 
    dplyr::mutate_if(~ any(is.na(.x)),~ if_else(is.na(.x),0,.x)) %>% 
    tibble::column_to_rownames(var = "gene") %>% 
    as.matrix()

ttop_KOvsWT_matrix <- ttop_KOvsWT %>% 
    dplyr::select(ID, t) %>% 
    dplyr::filter(!is.na(t)) %>% 
    column_to_rownames(var = "ID") %>%
    as.matrix()

## ----ProgenyCounts, message=FALSE---------------------------------------------
PathwayActivity_counts <- progeny(Normalised_counts_matrix, scale=TRUE, 
    organism="Human", top = 100)
Activity_counts <- as.vector(PathwayActivity_counts)

## ----HeatmapProgeny, dpi=300--------------------------------------------------
paletteLength <- 100
myColor <- 
    colorRampPalette(c("darkblue", "whitesmoke","indianred"))(paletteLength)

progenyBreaks <- c(seq(min(Activity_counts), 0, 
    length.out=ceiling(paletteLength/2) + 1),
    seq(max(Activity_counts)/paletteLength, 
    max(Activity_counts), 
    length.out=floor(paletteLength/2)))

progeny_hmap <- pheatmap(t(PathwayActivity_counts),fontsize=14, 
    fontsize_row = 10, fontsize_col = 10, 
    color=myColor, breaks = progenyBreaks, 
    main = "PROGENy (100)", angle_col = 45,
    treeheight_col = 0,  border_color = NA)

## ----ProgenyStat, message=FALSE-----------------------------------------------
PathwayActivity_zscore <- progeny(ttop_KOvsWT_matrix, 
    scale=TRUE, organism="Human", top = 100, perm = 1000, z_scores = TRUE) %>%
    t()
colnames(PathwayActivity_zscore) <- "NES"

## ----BarplotProgeny, dpi=300--------------------------------------------------
PathwayActivity_zscore_df <- as.data.frame(PathwayActivity_zscore) %>% 
    rownames_to_column(var = "Pathway") %>%
    dplyr::arrange(NES) %>%
    dplyr::mutate(Pathway = factor(Pathway))

ggplot(PathwayActivity_zscore_df,aes(x = reorder(Pathway, NES), y = NES)) + 
    geom_bar(aes(fill = NES), stat = "identity") +
    scale_fill_gradient2(low = "darkblue", high = "indianred", 
        mid = "whitesmoke", midpoint = 0) + 
    theme_minimal() +
    theme(axis.title = element_text(face = "bold", size = 12),
        axis.text.x = 
            element_text(angle = 45, hjust = 1, size =10, face= "bold"),
        axis.text.y = element_text(size =10, face= "bold"),
        panel.grid.major = element_blank(), 
        panel.grid.minor = element_blank()) +
    xlab("Pathways")

## ----ProgenySccater_1, message=FALSE, warning=FALSE---------------------------
prog_matrix <- getModel("Human", top=100) %>% 
    as.data.frame()  %>%
    tibble::rownames_to_column("GeneID")

ttop_KOvsWT_df <- ttop_KOvsWT_matrix %>% 
    as.data.frame() %>% 
    tibble::rownames_to_column("GeneID")

scat_plots <- progeny::progenyScatter(df = ttop_KOvsWT_df, 
    weight_matrix = prog_matrix, 
    statName = "t_values", verbose = FALSE)

## ----ProgenySccater_2, dpi=300------------------------------------------------
plot(scat_plots[[1]]$`MAPK`) 

## ----ProgenyCARNIVAL----------------------------------------------------------
PathwayActivity_CARNIVALinput <- progeny(ttop_KOvsWT_matrix, 
    scale=TRUE, organism="Human", top = 100, perm = 10000, z_scores = FALSE) %>%
    t () %>% 
    as.data.frame() %>% 
    tibble::rownames_to_column(var = "Pathway") 
colnames(PathwayActivity_CARNIVALinput)[2] <- "score"

## ----sessionInfo, echo=FALSE, eval=TRUE---------------------------------------
sessionInfo()