In baj12/idealImmunoTP: Interactive Differential Expression AnaLysis

knitr::opts_chunk$set(echo = TRUE)
library(tidyr)
library(SingleCellExperiment)
library(tibble)
library(ggplot2)
library(dplyr)

Violin plot of raw counts

se = readRDS("~/Downloads/se_ideal_toiSEE.rds")
raw = assays(se)[["counts"]]
raw_long = raw %>% 
           as_tibble() %>% 
           tibble::add_column(gene = rownames(raw)) %>% 
           pivot_longer(!gene,names_to = "sample", values_to = "count") %>% 
           filter(sample %in% c("D4g_O_P_N_f","D4g_O_P_A_f","D4g_O_P_P_f", "D4g_O_P_L_f"))
p <- ggplot(raw_long, aes(x=sample, y=count)) + 
  geom_violin()
p
raw_long$sample = as.factor(raw_long$sample)
raw_long2 = raw_long 
p <- ggplot(raw_long2, aes(x=sample, y=count)) + 
  geom_violin()
p

raw_long2 = raw_long2 %>% filter(count >5)

raw_long2 = raw_long2 %>% filter(count < 1000)
p <- ggplot(raw_long2, aes(x=sample, y=count)) + 
  geom_violin()
p

se = readRDS("~/Downloads/se_ideal_toiSEE.rds")
nCount = assays(se)[["normcounts"]]
nCount_long = nCount %>% 
           as_tibble() %>% 
           tibble::add_column(gene = rownames(raw)) %>% 
           pivot_longer(!gene,names_to = "sample", values_to = "count") %>% 
           filter(sample %in% c("D4g_O_P_N_f","D4g_O_P_A_f","D4g_O_P_P_f", "D4g_O_P_L_f"))
p <- ggplot(nCount_long, aes(x=sample, y=count)) + 
  geom_violin()
p
nCount_long$sample = as.factor(nCount_long$sample)
nCount_long2 = nCount_long 
p <- ggplot(nCount_long2, aes(x=sample, y=count)) + 
  geom_violin()
p

nCount_long2 = nCount_long2 %>% filter(count >5)

nCount_long2 = nCount_long2 %>% filter(count < 1000)
p <- ggplot(nCount_long2, aes(x=sample, y=count)) + 
  geom_violin()
p

cp = load("~/Downloads/idealState_20221122_093219.RData")

dds = r_data$dds_obj

co = coef(dds)
colnames(co)

hist(co[,3], breaks=1000, main="LPS_vs_null", xlab = "coeffient")