Commit a5b81aa5 authored by Venkat Malladi's avatar Venkat Malladi

Add figures for just TCGA data.

parent 36e7a4e3
......@@ -182,6 +182,7 @@ df_et_tcag_gtex$Type[df_et_tcag_gtex$Type == 'Metastatic'] <- 'Primary Tumor'
df_et_tcag_gtex_er <- df_et_tcag_gtex[complete.cases(df_et_tcag_gtex[ , 3]),]
df_et_tcag_gtex_er_type <- df_et_tcag_gtex_er[complete.cases(df_et_tcag_gtex_er[ , 4]),]
df_et_tcag_gtex_er_type_com <- df_et_tcag_gtex_er_type[which(df_et_tcag_gtex_er_type$ER %in% c('Negative','Positive','Normal')),]
df_et_tcag_gtex_type <- df_et_tcag_gtex[complete.cases(df_et_tcag_gtex[ , 4]),]
# Seperate into PAM and type for different genes
df_et_tcag_gtex_er_type_com$PARP1 <- log2(df_et_tcag_gtex_er_type_com$PARP1)
......@@ -222,3 +223,43 @@ dev.off()
ddx21_et.aov = aov(DDX21 ~ ER + Type, data=df_ddx21_et_tcag_gtex_er_type_summary)
summary(ddx21_et.aov)
### Type
df_et_tcag_type <- df_et_tcag_gtex_type[which(df_et_tcag_gtex_type$Type %in% c('Primary Tumor','Solid Tissue Normal')),]
df_et_tcag_type$PARP1 <- log(df_et_tcag_type$PARP1,2)
df_et_tcag_type$DDX21 <- log(df_et_tcag_type$DDX21,2)
## PARP1 and Type
df_et_tcag_gtex_type_summary <- summarySE(df_et_tcag_type, measurevar="PARP1", groupvars=c("Type"))
p <- ggplot(df_et_tcag_gtex_type_summary, aes(x = as.factor(Type), fill= Type)) +
geom_boxplot(aes(
lower = PARP1 - se,
upper = PARP1 + se,
middle = PARP1,
ymin = PARP1 - 2*se,
ymax = PARP1 + 2*se),
stat = "identity",lwd=1.5) + geom_hline(yintercept = mean(df_et_tcag_type$PARP1), linetype = 2) + labs(y="RPKM",x="PARP1") + theme_bw() + theme(panel.grid.major = element_blank(),panel.grid.minor = element_blank(),axis.ticks=element_line(size=1))
jpeg('figures/PARP1_breast_correlation_nvc_boxplot.jpg')
p
dev.off()
parp1_type.aov = aov(PARP1 ~ Type,data=df_et_tcag_type)
summary(parp1_type.aov)
## DDX21 and Type
df_ddx21_et_tcag_gtex_type_summary <- summarySE(df_et_tcag_type, measurevar="DDX21", groupvars=c("Type"))
p <- ggplot(df_ddx21_et_tcag_gtex_type_summary, aes(x = as.factor(Type), fill= Type)) +
geom_boxplot(aes(
lower = DDX21 - se,
upper = DDX21 + se,
middle = DDX21,
ymin = DDX21 - 2*se,
ymax = DDX21 + 2*se),
stat = "identity",lwd=1.5) + geom_hline(yintercept = mean(df_et_tcag_type$DDX21), linetype = 2) + labs(y="RPKM",x="DDX21") + theme_bw() + theme(panel.grid.major = element_blank(),panel.grid.minor = element_blank(),axis.ticks=element_line(size=1)) + scale_y_continuous(limits=c(3.8,4.9))
jpeg('figures/DDX21_breast_correlation_nvc_boxplot.jpg')
p
dev.off()
ddx21_type.aov = aov(DDX21 ~ Type,data=df_et_tcag_type)
summary(ddx21_type.aov)
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