scWBM_DEG_other_clusters.Rmd

---
title: "DE w/in Cluster scWBM"
author: "D. Ford Hannum"
date: "5/27/2020"
output: 
        html_document:
                toc: true
                toc_depth: 3
                number_sections: false
                theme: united
                highlight: tango
---

\newpage

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = F)
library(Seurat)
library(MAST)
library(ggplot2)
```

# Summary

Going to focus on differential expression within all the clusters from Experiment 1 of scWBM with the Sang Lab.

This analysis has already been performed on megakaryocytes which are the primary cell type of interest with regards to primary myelofibrosis. 


```{r lists to include}
# profibrotic factors of interest
pf <- read.table('./data/profibrotic_factors.txt')$V1
pf <- pf[2:length(pf)]


```

```{r loading the data and getting new idents}
wbm <- readRDS('./data/wbm_clustered_filtered_named.rds')

new_levels <- c('Granulocyte','Granulocyte','Granulocyte', 'B-cell','MK', 
        'Granulocyte', 'HSPC','Monocyte','Macrophage','Erythroid','B-cell',
        'T-cell/NK', 'MEP')
names(new_levels)  <- levels(wbm)
new_levels
wbm <- RenameIdents(wbm, new_levels)
wbm@meta.data$condition <- ifelse(wbm@meta.data$condition == 'control', 'Control','Mpl')
```

## Granulocytes

```{r DEG}
gr.markers <- FindMarkers(wbm, ident.1 = 'Control', ident.2 = 'Mpl',
                          group.by = 'condition',
                          verbose = T, subset.ident = "Granulocyte",
                          logfc.threshold = log(2), test.use = "MAST")

gr.markers

gr.cells <- WhichCells(wbm, ident = 'Granulocyte')
DoHeatmap(wbm, features = rownames(gr.markers), group.by = 'condition',
          cells = gr.cells, label = F)


```

```{r hspcs DEG}
hspc.markers <- FindMarkers(wbm, ident.1 = 'Control', ident.2 = 'Mpl',
                          group.by = 'condition',
                          verbose = T, subset.ident = "HSPC",
                          logfc.threshold = log(2),test.use = "MAST")

hspc.markers

hspc.cells = WhichCells(wbm, ident = 'HSPC')
DoHeatmap(wbm, features = rownames(hspc.markers), group.by = 'condition',
          cells = hspc.cells, label = F) +
        theme_minimal() + 
        xlab('MK Cells') + ylab('DE genes') + 
        scale_x_discrete(position = 'top') + 
        theme(text = element_text(size = 10, family = 'sans'),
              axis.text = element_blank(),
              axis.ticks = element_blank())
```