---
title: '[met] NDUF'
author: "Nina-Lydia Kazakou"
date: '2022-06-26'
output: html_document
---

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

# Set-up

### Load libraries

```{r load_libraries}
library(Seurat) # For scRNASeq analysis
library(here) # For reproducible pathways
library(ggsci) # Colour Pallete
library(ggplot2) # For nice plots
library(tidyverse) # For R
library(viridis) # For heatmap colours
library(RColorBrewer) # For treatment colours
```

### Colour Palette

```{r load_palette}
mypal1 <- pal_npg("nrc", alpha = 0.7)(10)
mypal2 <- pal_tron("legacy", alpha = 0.7)(7)
mypal3 <- pal_lancet("lanonc", alpha = 0.7)(9)
mypal4 <- pal_simpsons(palette = c("springfield"), alpha = 0.7)(16)
mypal5 <- pal_rickandmorty(palette = c("schwifty"), alpha = 0.7)(6)
mypal6 <- pal_futurama(palette = c("planetexpress"), alpha = 0.7)(5)
mypal7 <- pal_startrek(palette = c("uniform"), alpha = 0.7)(5)
mycoloursP<- c(mypal1, mypal2, mypal3, mypal4)
```

```{r met_ddH2O_colour}
cp <- brewer.pal(n = 8, name = "Pastel1")
cp_2 <- brewer.pal(n = 12, name = "Set3")
my_cp <- c(cp, cp_2)
```

### Load object

```{r load_object}
srt <- readRDS(here("Data", "Human_R_Analysis", "Metformin_ddH2O", "met_srt_ol.rds"))
```

```{r}
DimPlot(srt, group.by = "Initial_Annotation", pt.size = 1, cols = mycoloursP[5:40], label = TRUE) & NoLegend()

DimPlot(srt, group.by = "Treatment", split.by = "Treatment", pt.size = 1, cols = c(my_cp[2], my_cp[1]), label = FALSE) & NoLegend()
```

```{r}
FeaturePlot(srt, features = "subsets_mt_percent", split.by = "Treatment")

VlnPlot(srt, features = "subsets_mt_percent", group.by = "Treatment", c(my_cp[2], my_cp[1]))
```

### Read in data

```{r}
nduf <- read.csv(here("outs", "filter_70", "Human_R_Analysis", "Metformin_ddH2O", "NDUF", "nduf_genes.csv"))
```

# NDUF: NADH Complex I

Nicotinamide Adenine Dinucleotide: Ubiquinone oxidoreductase

Mitochondrial complex I (CI):

-   Largest discrete enzyme of the oxidative phosphorylation system (OXPHOS)

-   Located in the inner mitochondrial membrane

-   Transports electrons from NADH to ubiquinone

-   Oxidizes NADH generated from the tricorboxylic acid cycle NAD+, which leads to the reduction of the ubiquinone & the transport of protons from thee matrix across the inner membrane to the inter-membrane area --\> the proton-motive force is consumed by ATP synthase to generate ATP or harness ion transport or mRNA or protein transport

-   Consists of 41 sub-units , now fully identified in humans, although there are no functional data available; 7 of them are encoded by mtDNA (ND1-ND6, ND4L) and 34 of them are encoded by nDNA and are divided in 3 fractions: a) Flavoprotein (FP), b) Iron-sulfur protein (IP) and c) Hydrophobic protein (HP)

-   Complex I impairment causes abnormalities in the energy generating systems present in mitochondria and has been associated with chronic metabolite and degenerative disorders, like diabetis, cardiomyopathy, Parkinson's Disease (PD) and Leigh syndrome

### Plots

```{r fig.height=40, fig.width=20}
VlnPlot(srt,features = nduf$Approved.symbol, ncol = 4, group.by = "Treatment", pt.size = 0.1, cols = c(my_cp[2], my_cp[1]))
```

```{r fig.height=10, fig.width=20}
DotPlot(srt, features = nduf$Approved.symbol, group.by = "Treatment") + FontSize(9) +
     theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1))
```

```{r fig.height=10, fig.width=20}
Idents(srt) <- srt@meta.data$Initial_Annotation
DotPlot(srt, features = nduf$Approved.symbol, split.by = "Treatment",  cols = c(my_cp[2], my_cp[1]), dot.scale = 8) + FontSize(9) +
     theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1))
```

```{r fig.height=15, fig.width=15}
DoHeatmap(object = srt, features = nduf$Approved.symbol, label = TRUE, group.by = "Treatment",  group.colors =c(my_cp[2], my_cp[1]), draw.lines = TRUE, size = 5)  + theme(text = element_text(size = 10, face = "bold"), plot.title = element_text(hjust = 0.5)) + scale_fill_viridis(discrete=FALSE)
```

```{r fig.height=15, fig.width=10}
cluster_averages <- AverageExpression(srt, group.by = "Treatment", return.seurat = TRUE)

Idents(srt) <- srt@meta.data$Treatment
lev <- levels(Idents(srt))
cluster_averages@meta.data$cluster <- factor(lev)

library(viridis)

DoHeatmap(object = cluster_averages, features = nduf$Approved.symbol, label = TRUE, group.by = "cluster",  group.colors =c(my_cp[2], my_cp[1]), draw.lines = F, size = 5)  + theme(text = element_text(size = 10, face = "bold"), plot.title = element_text(hjust = 0.5)) + scale_fill_viridis(discrete=FALSE)
```

```{r}
# Upregulated NDUF genes in metformin treated animals 
up_genes <- c("NDUFAB1", "NDUFA10", "NDUFA11", "NDUFB7", "NDUFB10", "NDUFB11", "NDUFS2", "NDUFS3", "NDUFS6", "NDUFS7", "NDUFS8", "NDUFV1")
```

```{r fig.height=15, fig.width=20}
VlnPlot(srt,features = up_genes, ncol = 4, group.by = "Treatment", pt.size = 0.1, cols = c(my_cp[2], my_cp[1]))
```

```{r fig.height=30, fig.width=20}
VlnPlot(srt,features = up_genes, ncol = 2, group.by = "Initial_Annotation", pt.size = 0.1, cols = mycoloursP)
```

## Human data

```{r}
HCA <- readRDS("C:/Users/s1241040/Desktop/SingleCell_MonolayerCultures/MonolayerCultures/data/Processed/Original_Objects/HCA_oligos_opcs_LS.RDS")
```

```{r}
DefaultAssay(HCA) <- "RNA"
```

```{r fig.height=55, fig.width=20, message=FALSE, warning=FALSE}
VlnPlot(HCA, group.by = "ol_clusters_named", features = nduf$Approved.symbol, cols = mycoloursP, ncol = 2)
VlnPlot(HCA, group.by = "ol_clusters_named", features = nduf$Approved.symbol, cols = mycoloursP, ncol = 2, pt.size = 0)
```

#### Upregulated gene in metformin treated cells

```{r fig.height=20, fig.width=20}
VlnPlot(HCA, group.by = "ol_clusters_named", features = up_genes, cols = mycoloursP, ncol = 2)
VlnPlot(HCA, group.by = "ol_clusters_named", features = up_genes, cols = mycoloursP, ncol = 2, pt.size = 0)
```

##### SessionInfo

<details>

<summary>

Click to expand

</summary>

```{r}
sessionInfo()
```

</details>