Hi All,

I am having difficulties to make a barplot for  each gene by 2 factors with ggplot2.  I tried to modify my boxplot code but it does not work.

I would like to plot each gene by 2 factors: "cell_type" and "age". x-axis represents "cell type" categories  and inside each "cell type" category should be 5 bars representing the "age" categories. The y axis is the gene expression value  (mean + error bars). 

My code:

mat= t(exprs(eSet))
colnames(mat) = fData(eSet)$Symbol
rownames(mat = pData(eSet)$genotype
GENOTYPE <- rownames(mat)
AGE <- pData(eSet)$age
d.f_all_genes2 <- data.frame(GENOTYPE, AGE, mat)

d.f_all_genes2[1:3,1:10]
  GENOTYPE AGE X1.2.SBSRNA4 A1BG A1BG.AS1 A1CF A2LD1 A2M A2ML1 A2MP1
1 rag_a   54            0    0        0    0     0   0     0     0
2 rag_wt  54            0    0        0    0     0  18     0     0
3 wt_wt   54            0    0        0    0     0   1     0     0

melted <- melt(d.f_all_genes2, id.vars="GENOTYPE")  

> head(melted)
          GENOTYPE   variable value
1           rag_a       AGE     54
2           rag_wt      AGE     54
3            wt_wt      AGE     54

I have not tested this code  yet below:

means <- ddply(melted, c("AGE", "variable"), summarise, mean=mean(value))
means.sem <- ddply(melted, c("AGE", "variable"), summarise, mean=mean(value),sem=sd(value)/sqrt(length(value)))
means.sem <- transform(means.sem, lower=mean-sem, upper=mean+sem)

ggplot(means[means$variable == "GENE of Interest",], aes(x = factor(AGE), y = mean))  + geom_bar(stat= "identity", colour = "blue", outlier.shape = NA)+ facet_grid(~GENOTYPE) + facet_wrap(~variable) +  ylab(expression(paste(Log[2], " Expression Values"))) + theme(axis.text=element_text(size=13, color="black"),axis.title=element_text(size=12, face="bold",color="black"), plot.title=element_text(size=14,face="bold", color="black"), strip.text.x = element_text(colour = "black", face= "bold",angle = 0, size = 20))

Any help is highly appreciated.

Thank you very much in advance.

Anita

My boxplot code that works

mat= t(exprs(eSet))
colnames(mat) = fData(eSet)$Symbol
rownames(mat = pData(eSet)$genotype
GENOTYPE <- rownames(mat)

d.f_all_genes <- data.frame(GENOTYPE, mat_all_genes)
d.f2_all_genes <- melt(d.f_all_genes, id.vars = "GENOTYPE")
colorsg = c("royalblue3","green1", "violetred1", "red1", "blue", "black", "red3","pink","orange")

plot <- ggplot(d.f2_all_genes[d.f2_all_genes$variable == "GENE of Interes",], aes(x = GENOTYPE, y = value))  + geom_boxplot(fill = colorsg, colour = "black", outlier.shape = NA) + geom_jitter(position = position_jitter(height = .5, width = .05), size=3, alpha=1) + facet_wrap(~variable) +  ylab(expression(paste(Log[2], " Expression Values"))) + theme(axis.text=element_text(size=13, color="black"),axis.title=element_text(size=12, face="bold",color="black"), plot.title=element_text(size=14,face="bold", color="black"), strip.text.x = element_text(colour = "black", face= "bold",angle = 0, size = 20)) + coord_flip()

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