Interval_Plot.Rmd

---
title: "Plot Interval Graph (Prediction Vs Observed inhibitory activities)"
author: Saw Simeon, Nuttapat Anuwongcharoen, Watshara Shoombuatong, Aijaz Ahmad Malik,
  Virapong Prachayasittikul, Jarl E. S. Wikberg and Chanin Nantasenamat
date: "June 16, 2016"
output: pdf_document
---

# Create a predicted and IC50 plot

```{r}

file <- function(x) {
  library(randomForest)
  library(caret)
  library(ranger)
  library(cowplot)
  set.seed(10)
  para <- dplyr::sample_n(x, size = 2570, replace = TRUE)
  set.seed(3)
  in_train_para <- sample(nrow(para),
                          size = as.integer(nrow(para) * 0.8),
                          replace = FALSE)
  set.seed(4)
  Train <- para[in_train_para, ]
  Test  <- para[-in_train_para, ]
  
  model <- ranger::ranger(pIC50~., data = Train, write.forest = TRUE, save.memory = TRUE)
  #actual <- train$Activity
  prediction <- predict(model, Train)
  prediction_Internal <- prediction$predictions
  value <- data.frame(obs = Train$pIC50, pred = prediction_Internal)
  labeling <- c("obs", "pred")
  colnames(value) <- labeling
  value$Label <- c("Internal")
  prediction_External <- predict(model, Test)
  prediction_External <- prediction_External$predictions
  value_external <- data.frame(obs = Test$pIC50, pred = prediction_External)
  colnames(value_external) <- labeling
  value_external$Label <- c("External")
  results <- rbind(value, value_external)
  return(results)
}


get_interval <- function(x) {
  file <- file(x)
  x <- file[, 1]
  y <- file[, 2]
  label <- file[3]
  fit <- lm(y~x)
  pred.int <- predict(fit, interval = "prediction")
  pred.lower = pred.int[,2]
  pred.upper = pred.int[,3]
  df <- cbind(x, y, label, pred.lower, pred.upper)
  return(df)
}

plot_graph_interval <- function(x) {
  library(ggplot2)
  ok <- get_interval(x)
  good <- ggplot(ok, aes(x = x)) +
    geom_point(size = 7, colour = "black", pch = 21, alpha= 0.4,
               aes(y = y, fill = factor(Label))) +
    geom_line(aes(y = pred.lower), size = 1.5, colour = "grey", linetype = 2) +
    geom_line(aes(y = pred.upper), size = 1.5, colour = "grey", linetype = 2) +
    xlab(expression(paste('Predicted ', pIC[50]))) + ylab(expression(paste('Experimental ', pIC[50]))) +
    #geom_abline(intercept = ok$pred.lower[[1]], linetype = 2, size = 1.5, colour = "grey") +
    #geom_abline(intercept = ok$pred.upper[[1]], linetype = 2, size = 1.5, colour = "grey") +
    theme(
      panel.border = element_rect(linetype = "solid", colour = "black",
                                  fill = NA, size = 1),

    axis.text.y = element_text(size = 20, colour = "black"),
    axis.text.x = element_text(size = 20, colour = "black"),
    axis.title.x = element_text(size = 30, color = "black", face = "bold"),
    axis.title.y = element_text(size = 30, color = "black", face = "bold"),
    
      legend.position = ("none")) +
    coord_cartesian(ylim = c(-6, 12), xlim = c(-6, 12))
  return(good)
  
}



```

\pagebreak

# CDK fingerprint

```{r, fig.width = 10, fig.height = 10, error = FALSE, message = FALSE, warning= FALSE}
input <- readRDS("data.Rds")
df <- input$FingerPrinter
plot_graph_interval(df)
```

\pagebreak

# CDK extended fingerprint

```{r, fig.width = 10, fig.height = 10, error = FALSE, message = FALSE, warning= FALSE}
input <- readRDS("data.Rds")
df <- input$Extended_finterPrinter
plot_graph_interval(df)
```

\pagebreak

# CDK graph only fingerprint

```{r, fig.width = 10, fig.height = 10, error = FALSE, message = FALSE, warning= FALSE}
input <- readRDS("data.Rds")
df <- input$GraphOnly_FingerPrinter
plot_graph_interval(df)
```

\pagebreak

# E-state fingerprint

```{r, fig.width = 10, fig.height = 10, error = FALSE, message = FALSE, warning= FALSE}
input <- readRDS("data.Rds")
df <- input$Extended_finterPrinter
plot_graph_interval(df)
```

\pagebreak

# MACCS fingerprint

```{r, fig.width = 10, fig.height = 10, error = FALSE, message = FALSE, warning= FALSE}
input <- readRDS("data.Rds")
df <- input$MACCS_FingerPrinter
plot_graph_interval(df)
```

\pagebreak

# PubChem fingerprint

```{r, fig.width = 10, fig.height = 10, error = FALSE, message = FALSE, warning= FALSE}
input <- readRDS("data.Rds")
df <- input$Pubchem_FingerPrinter
plot_graph_interval(df)
```

\pagebreak

# Substructure fingerprint

```{r, fig.width = 10, fig.height = 10, error = FALSE, message = FALSE, warning= FALSE}
input <- readRDS("data.Rds")
df <- input$Substructure_fingerPrinter
plot_graph_interval(df)
```

\pagebreak

# Substructure count

```{r, fig.width = 10, fig.height = 10, error = FALSE, message = FALSE, warning= FALSE}
input <- readRDS("data.Rds")
df <- input$Substructure_fingerPrintCount
plot_graph_interval(df)
```

\pagebreak

# Klekota-Roth fingerprint

```{r, fig.width = 10, fig.height = 10, error = FALSE, message = FALSE, warning= FALSE}
input <- readRDS("data.Rds")
df <- input$KlekotaRoth_FingerPrinter
plot_graph_interval(df)
```

\pagebreak

# Klekota-Roth count

```{r, fig.width = 10, fig.height = 10, error = FALSE, message = FALSE, warning= FALSE}
input <- readRDS("data.Rds")
df <- input$KlekotaRoth_FingerprintCount
plot_graph_interval(df)
```

\pagebreak

# 2D atom pairs

```{r, fig.width = 10, fig.height = 10, error = FALSE, message = FALSE, warning= FALSE}
input <- readRDS("data.Rds")
df <- input$AtomPairs2D_fingerPrinter
plot_graph_interval(df)
```

\pagebreak

# 2D atom pairs count

```{r, fig.width = 10, fig.height = 10, error = FALSE, message = FALSE, warning= FALSE}
input <- readRDS("data.Rds")
df <- input$AtomPairs2D_fingerPrintCount
plot_graph_interval(df)
```