AUCell.Rmd

---
title: "AUCell"
author: "Xue Xiao"
date: "2024-06-20"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

## Install AUCell
```{r eval=FALSE, echo=FALSE, message=FALSE, warning=FALSE}
BiocManager::install("AUCell")
```

## Load Packages
```{r}
library(AUCell)
library(Matrix)
library(SummarizedExperiment)
library(Seurat)
```


## Load Genesets and Datasets
```{r}
setwd("/Users/xuexiao/Library/CloudStorage/GoogleDrive-heinyxiao@gmail.com/My Drive/Lab/Projects/Dedifferentiation/Data")
CC1_markers <- read.csv("CC1_markers.csv", header = T, row.names = 1)
CC1_geneset <- CC1_markers$Genes

CSC_markers_0.007 <- read.csv("filtered_markers_above_0_007.csv", header = T, row.names = 1)
CSC_geneset_0.007 <- CSC_markers_0.007$GENE

CSC_markers_0.006 <- read.csv("filtered_markers_above_0_006.csv", header = T, row.names = 1)
CSC_geneset_0.006 <- CSC_markers_0.006$GENE

CSC_markers_0.005 <- read.csv("filtered_markers_above_0_005.csv", header = T, row.names = 1)
CSC_geneset_0.005 <- CSC_markers_0.005$GENE

gene_sets <- list(
  CC1 = CC1_geneset,
  CSC_0.007 = CSC_geneset_0.007,
  CSC_0.006 = CSC_geneset_0.006,
  CSC_0.005 = CSC_geneset_0.005
)
common_genes <- intersect(CC1_geneset, CSC_geneset_0.005)
```


```{r}
# Open Seurat File
seurat_obj <- readRDS("~/Library/CloudStorage/GoogleDrive-heinyxiao@gmail.com/My Drive/Lab/Projects/Dedifferentiation/Data/Cancer_cell_in_house_magic_cytotrace.rds")

# Extract the expression matrix
expr_matrix <- GetAssayData(seurat_obj, layer = "counts")

```

## Run AUCell
```{r}
# Build the rankings
cells_rankings <- AUCell_buildRankings(expr_matrix, nCores = 1, plotStats = TRUE)

# Calculate the AUCell scores
cells_AUC <- AUCell_calcAUC(gene_sets, cells_rankings)

# Add AUCell scores to Seurat metadata
aucell_scores <- as.data.frame(t(as.data.frame(cells_AUC@assays@data$AUC)))
colnames(aucell_scores) <- paste0("AUCell_", colnames(aucell_scores))
seurat_obj <- AddMetaData(seurat_obj, metadata = aucell_scores)

# View the Seurat object metadata to check if scores were added
head(seurat_obj@meta.data)

```

## Visualization
```{r inline_plot, fig.width=7, fig.height=5}

# Define custom color palette
custom_colors <- scale_color_gradientn(colors = c("gray", "yellow", "red"))

# Visualize the AUCell scores with custom color scheme
FeaturePlot(seurat_obj, features = colnames(aucell_scores), pt.size = 0.2, label = T) & custom_colors

```