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figure_2.Rmd
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---
title: "QPCR Data - Figure 2"
author: "Emily Butka"
date: "2024-06-13"
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
## Load data
```{r}
ProgPreadipGenes <- read.csv("~/OneDrive/MorrisLab/Guillermo_project/data_from_carolynn/Figure 2-selected/APC validation plate 1_data.csv")
```
```{r}
F3posF3neg <- read.csv("~/OneDrive/MorrisLab/Guillermo_project/data_from_carolynn/Figure 2-selected/F3pos_F3neg_3_10_23_CEG_data_processed.csv")
```
```{r}
Preadipocytes <- read.csv("~/OneDrive/MorrisLab/Guillermo_project/data_from_carolynn/Figure 2-selected/CD26_ABC_CD9_ABC_F3_AB_6_15_21_data.csv")
```
## Generate plots
```{r}
ProgPreadipGenes <- ProgPreadipGenes[ProgPreadipGenes$Cell_Type %in% c("CD26", "CD9"), ]
```
```{r}
ProgPreadipGenes$Gene <- factor(ProgPreadipGenes$Gene, levels = c("Akr1c18", "Smpd3", "Gap43", "Dpp4", "Mfap4", "Igfbp7", "Igf1", "Cd9"))
```
```{r}
p2b <- ggplot(ProgPreadipGenes, aes(x=Gene, y=Mean, fill=Cell_Type)) +
geom_bar(stat="identity", color="black", position=position_dodge()) +
scale_fill_manual(values=c("#211E71", "#741112")) +
geom_errorbar(aes(ymin=Mean-Stdev, ymax=Mean+Stdev),
width=.2, position=position_dodge(.9)) +
theme_classic() +
theme(text = element_text(size = 8, family='Helvetica'), plot.margin = margin(0, 0, 0, 0)) +
labs("", y = "Fold change")
p2b
```
Two sample t test
```{r}
# m1, m2: the sample means
# s1, s2: the sample standard deviations
# n1, n2: the same sizes
# m0: the null value for the difference in means to be tested for. Default is 0.
# equal.variance: whether or not to assume equal variance. Default is FALSE.
t.test2 <- function(m1,m2,s1,s2,n1,n2,m0=0,equal.variance=FALSE)
{
if( equal.variance==FALSE )
{
se <- sqrt( (s1^2/n1) + (s2^2/n2) )
# welch-satterthwaite df
df <- ( (s1^2/n1 + s2^2/n2)^2 )/( (s1^2/n1)^2/(n1-1) + (s2^2/n2)^2/(n2-1) )
} else
{
# pooled standard deviation, scaled by the sample sizes
se <- sqrt( (1/n1 + 1/n2) * ((n1-1)*s1^2 + (n2-1)*s2^2)/(n1+n2-2) )
df <- n1+n2-2
}
t <- (m1-m2-m0)/se
dat <- c(m1-m2, se, t, 2*pt(-abs(t),df))
names(dat) <- c("Difference of means", "Std Error", "t", "p-value")
return(dat)
}
```
```{r}
t.test2(ProgPreadipGenes$Mean[which(ProgPreadipGenes$Cell_Type == "CD26" & ProgPreadipGenes$Gene == "Akr1c18")],
ProgPreadipGenes$Mean[which(ProgPreadipGenes$Cell_Type == "CD9" & ProgPreadipGenes$Gene == "Akr1c18")],
ProgPreadipGenes$Stdev[which(ProgPreadipGenes$Cell_Type == "CD26" & ProgPreadipGenes$Gene == "Akr1c18")],
ProgPreadipGenes$Stdev[which(ProgPreadipGenes$Cell_Type == "CD9" & ProgPreadipGenes$Gene == "Akr1c18")],
3,
3)
```
```{r}
t.test2(ProgPreadipGenes$Mean[which(ProgPreadipGenes$Cell_Type == "CD26" & ProgPreadipGenes$Gene == "Smpd3")],
ProgPreadipGenes$Mean[which(ProgPreadipGenes$Cell_Type == "CD9" & ProgPreadipGenes$Gene == "Smpd3")],
ProgPreadipGenes$Stdev[which(ProgPreadipGenes$Cell_Type == "CD26" & ProgPreadipGenes$Gene == "Smpd3")],
ProgPreadipGenes$Stdev[which(ProgPreadipGenes$Cell_Type == "CD9" & ProgPreadipGenes$Gene == "Smpd3")],
3,
3)
```
```{r}
t.test2(ProgPreadipGenes$Mean[which(ProgPreadipGenes$Cell_Type == "CD26" & ProgPreadipGenes$Gene == "Gap43")],
ProgPreadipGenes$Mean[which(ProgPreadipGenes$Cell_Type == "CD9" & ProgPreadipGenes$Gene == "Gap43")],
ProgPreadipGenes$Stdev[which(ProgPreadipGenes$Cell_Type == "CD26" & ProgPreadipGenes$Gene == "Gap43")],
ProgPreadipGenes$Stdev[which(ProgPreadipGenes$Cell_Type == "CD9" & ProgPreadipGenes$Gene == "Gap43")],
3,
3)
```
```{r}
t.test2(ProgPreadipGenes$Mean[which(ProgPreadipGenes$Cell_Type == "CD26" & ProgPreadipGenes$Gene == "Dpp4")],
ProgPreadipGenes$Mean[which(ProgPreadipGenes$Cell_Type == "CD9" & ProgPreadipGenes$Gene == "Dpp4")],
ProgPreadipGenes$Stdev[which(ProgPreadipGenes$Cell_Type == "CD26" & ProgPreadipGenes$Gene == "Dpp4")],
ProgPreadipGenes$Stdev[which(ProgPreadipGenes$Cell_Type == "CD9" & ProgPreadipGenes$Gene == "Dpp4")],
3,
3)
```
```{r}
t.test2(ProgPreadipGenes$Mean[which(ProgPreadipGenes$Cell_Type == "CD26" & ProgPreadipGenes$Gene == "Mfap4")],
ProgPreadipGenes$Mean[which(ProgPreadipGenes$Cell_Type == "CD9" & ProgPreadipGenes$Gene == "Mfap4")],
ProgPreadipGenes$Stdev[which(ProgPreadipGenes$Cell_Type == "CD26" & ProgPreadipGenes$Gene == "Mfap4")],
ProgPreadipGenes$Stdev[which(ProgPreadipGenes$Cell_Type == "CD9" & ProgPreadipGenes$Gene == "Mfap4")],
3,
3)
```
```{r}
t.test2(ProgPreadipGenes$Mean[which(ProgPreadipGenes$Cell_Type == "CD26" & ProgPreadipGenes$Gene == "Igfbp7")],
ProgPreadipGenes$Mean[which(ProgPreadipGenes$Cell_Type == "CD9" & ProgPreadipGenes$Gene == "Igfbp7")],
ProgPreadipGenes$Stdev[which(ProgPreadipGenes$Cell_Type == "CD26" & ProgPreadipGenes$Gene == "Igfbp7")],
ProgPreadipGenes$Stdev[which(ProgPreadipGenes$Cell_Type == "CD9" & ProgPreadipGenes$Gene == "Igfbp7")],
3,
3)
```
```{r}
t.test2(ProgPreadipGenes$Mean[which(ProgPreadipGenes$Cell_Type == "CD26" & ProgPreadipGenes$Gene == "Igf1")],
ProgPreadipGenes$Mean[which(ProgPreadipGenes$Cell_Type == "CD9" & ProgPreadipGenes$Gene == "Igf1")],
ProgPreadipGenes$Stdev[which(ProgPreadipGenes$Cell_Type == "CD26" & ProgPreadipGenes$Gene == "Igf1")],
ProgPreadipGenes$Stdev[which(ProgPreadipGenes$Cell_Type == "CD9" & ProgPreadipGenes$Gene == "Igf1")],
3,
3)
```
```{r}
t.test2(ProgPreadipGenes$Mean[which(ProgPreadipGenes$Cell_Type == "CD26" & ProgPreadipGenes$Gene == "Cd9")],
ProgPreadipGenes$Mean[which(ProgPreadipGenes$Cell_Type == "CD9" & ProgPreadipGenes$Gene == "Cd9")],
ProgPreadipGenes$Stdev[which(ProgPreadipGenes$Cell_Type == "CD26" & ProgPreadipGenes$Gene == "Cd9")],
ProgPreadipGenes$Stdev[which(ProgPreadipGenes$Cell_Type == "CD9" & ProgPreadipGenes$Gene == "Cd9")],
3,
3)
```
```{r}
p2c <- ggplot(F3posF3neg, aes(x=Gene, y=Mean, fill=F3)) +
geom_bar(stat="identity", color="black", position=position_dodge()) +
scale_fill_manual(values=c("#9F0162","#FFB2FD")) +
geom_errorbar(aes(ymin=Mean-Stdev, ymax=Mean+Stdev),
width=.2, position=position_dodge(.9)) +
theme_classic() +
labs(x = "F3 positive markers", y = "Fold change")
p2c
```
Stats:
```{r}
t.test2(F3posF3neg$Mean[which(F3posF3neg$F3 == "Positive" & F3posF3neg$Gene == "Eln")],
F3posF3neg$Mean[which(F3posF3neg$F3 == "Negative" & F3posF3neg$Gene == "Eln")],
F3posF3neg$Stdev[which(F3posF3neg$F3 == "Positive" & F3posF3neg$Gene == "Eln")],
F3posF3neg$Stdev[which(F3posF3neg$F3 == "Negative" & F3posF3neg$Gene == "Eln")],
3,
3)
```
```{r}
t.test2(F3posF3neg$Mean[which(F3posF3neg$F3 == "Positive" & F3posF3neg$Gene == "Igf1")],
F3posF3neg$Mean[which(F3posF3neg$F3 == "Negative" & F3posF3neg$Gene == "Igf1")],
F3posF3neg$Stdev[which(F3posF3neg$F3 == "Positive" & F3posF3neg$Gene == "Igf1")],
F3posF3neg$Stdev[which(F3posF3neg$F3 == "Negative" & F3posF3neg$Gene == "Igf1")],
3,
3)
```
```{r}
t.test2(F3posF3neg$Mean[which(F3posF3neg$F3 == "Positive" & F3posF3neg$Gene == "Lox")],
F3posF3neg$Mean[which(F3posF3neg$F3 == "Negative" & F3posF3neg$Gene == "Lox")],
F3posF3neg$Stdev[which(F3posF3neg$F3 == "Positive" & F3posF3neg$Gene == "Lox")],
F3posF3neg$Stdev[which(F3posF3neg$F3 == "Negative" & F3posF3neg$Gene == "Lox")],
3,
3)
```
```{r}
t.test2(F3posF3neg$Mean[which(F3posF3neg$F3 == "Positive" & F3posF3neg$Gene == "Smoc2")],
F3posF3neg$Mean[which(F3posF3neg$F3 == "Negative" & F3posF3neg$Gene == "Smoc2")],
F3posF3neg$Stdev[which(F3posF3neg$F3 == "Positive" & F3posF3neg$Gene == "Smoc2")],
F3posF3neg$Stdev[which(F3posF3neg$F3 == "Negative" & F3posF3neg$Gene == "Smoc2")],
3,
3)
```
```{r}
Preadipocytes$Cell_Type <- gsub("DPP4\\+", "Progenitors", Preadipocytes$Cell_Type)
Preadipocytes$Cell_Type <- gsub("CD9\\+", "Immature Preadipocytes", Preadipocytes$Cell_Type)
Preadipocytes$Cell_Type <- gsub("CD142\\+", "Committed Preadipocytes", Preadipocytes$Cell_Type)
```
```{r}
Preadipocytes$APC_Type <- rep(c("Progenitors", "Preadipocytes", "Preadipocytes"), 3)
Preadipocytes$Cell_Type <- factor(Preadipocytes$Cell_Type, levels = c("Progenitors", "Immature Preadipocytes", "Committed Preadipocytes"))
```
```{r}
p2d_left <- ggplot(Preadipocytes[Preadipocytes$Gene=="Pparg",], aes(x=Cell_Type, y=Mean, fill=APC_Type)) +
geom_bar(stat="identity", color="black", position=position_dodge()) +
scale_fill_manual(values=c("#741112","#211E71")) +
geom_errorbar(aes(ymin=Mean-Stdev, ymax=Mean+Stdev),
width=.2, position=position_dodge(.9)) +
theme_classic() +
theme(text = element_text(size = 8, family='Helvetica'), plot.margin = margin(0, 0, 0, 0)) +
labs(x = "", y = "Fold change")
p2d_left
```
```{r}
p2d_middle <- ggplot(Preadipocytes[Preadipocytes$Gene=="Adipoq",], aes(x=Cell_Type, y=Mean, fill=APC_Type)) +
geom_bar(stat="identity", color="black", position=position_dodge()) +
scale_fill_manual(values=c("#741112","#211E71")) +
geom_errorbar(aes(ymin=Mean-Stdev, ymax=Mean+Stdev),
width=.2, position=position_dodge(.9)) +
theme_classic() +
theme(text = element_text(size = 8, family='Helvetica'), plot.margin = margin(0, 0, 0, 0)) +
labs(x = "", y = "Fold change")
p2d_middle
```
```{r}
p2d_right <- ggplot(Preadipocytes[Preadipocytes$Gene=="Plin1",], aes(x=Cell_Type, y=Mean, fill=APC_Type)) +
geom_bar(stat="identity", color="black", position=position_dodge()) +
scale_fill_manual(values=c("#741112","#211E71")) +
geom_errorbar(aes(ymin=Mean-Stdev, ymax=Mean+Stdev),
width=.2, position=position_dodge(.9)) +
theme_classic() +
theme(text = element_text(size = 8, family='Helvetica'), plot.margin = margin(0, 0, 0, 0)) +
labs(x = "", y = "Fold change")
p2d_right
```
Stats:
```{r}
t.test2(Preadipocytes$Mean[which(Preadipocytes$Cell_Type == "Progenitors" & Preadipocytes$Gene == "Plin1")],
Preadipocytes$Mean[which(Preadipocytes$Cell_Type == "Immature Preadipocytes" & Preadipocytes$Gene == "Plin1")],
Preadipocytes$Stdev[which(Preadipocytes$Cell_Type == "Progenitors" & Preadipocytes$Gene == "Plin1")],
Preadipocytes$Stdev[which(Preadipocytes$Cell_Type == "Immature Preadipocytes" & Preadipocytes$Gene == "Plin1")],
3,
3)
```
```{r}
t.test2(Preadipocytes$Mean[which(Preadipocytes$Cell_Type == "Progenitors" & Preadipocytes$Gene == "Plin1")],
Preadipocytes$Mean[which(Preadipocytes$Cell_Type == "Committed Preadipocytes" & Preadipocytes$Gene == "Plin1")],
Preadipocytes$Stdev[which(Preadipocytes$Cell_Type == "Progenitors" & Preadipocytes$Gene == "Plin1")],
Preadipocytes$Stdev[which(Preadipocytes$Cell_Type == "Committed Preadipocytes" & Preadipocytes$Gene == "Plin1")],
3,
3)
```
```{r}
t.test2(Preadipocytes$Mean[which(Preadipocytes$Cell_Type == "Progenitors" & Preadipocytes$Gene == "Adipoq")],
Preadipocytes$Mean[which(Preadipocytes$Cell_Type == "Immature Preadipocytes" & Preadipocytes$Gene == "Adipoq")],
Preadipocytes$Stdev[which(Preadipocytes$Cell_Type == "Progenitors" & Preadipocytes$Gene == "Adipoq")],
Preadipocytes$Stdev[which(Preadipocytes$Cell_Type == "Immature Preadipocytes" & Preadipocytes$Gene == "Adipoq")],
3,
3)
```
```{r}
t.test2(Preadipocytes$Mean[which(Preadipocytes$Cell_Type == "Progenitors" & Preadipocytes$Gene == "Adipoq")],
Preadipocytes$Mean[which(Preadipocytes$Cell_Type == "Committed Preadipocytes" & Preadipocytes$Gene == "Adipoq")],
Preadipocytes$Stdev[which(Preadipocytes$Cell_Type == "Progenitors" & Preadipocytes$Gene == "Adipoq")],
Preadipocytes$Stdev[which(Preadipocytes$Cell_Type == "Committed Preadipocytes" & Preadipocytes$Gene == "Adipoq")],
3,
3)
```
```{r}
t.test2(Preadipocytes$Mean[which(Preadipocytes$Cell_Type == "Progenitors" & Preadipocytes$Gene == "Pparg")],
Preadipocytes$Mean[which(Preadipocytes$Cell_Type == "Immature Preadipocytes" & Preadipocytes$Gene == "Pparg")],
Preadipocytes$Stdev[which(Preadipocytes$Cell_Type == "Progenitors" & Preadipocytes$Gene == "Pparg")],
Preadipocytes$Stdev[which(Preadipocytes$Cell_Type == "Immature Preadipocytes" & Preadipocytes$Gene == "Pparg")],
3,
3)
```
```{r}
t.test2(Preadipocytes$Mean[which(Preadipocytes$Cell_Type == "Progenitors" & Preadipocytes$Gene == "Pparg")],
Preadipocytes$Mean[which(Preadipocytes$Cell_Type == "Committed Preadipocytes" & Preadipocytes$Gene == "Pparg")],
Preadipocytes$Stdev[which(Preadipocytes$Cell_Type == "Progenitors" & Preadipocytes$Gene == "Pparg")],
Preadipocytes$Stdev[which(Preadipocytes$Cell_Type == "Committed Preadipocytes" & Preadipocytes$Gene == "Pparg")],
3,
3)
```