Convert A for loop in R to apply function

My goal is to iterate over a datamatrix, calculate mean, standard error of the mean, and then have a bar plot representing the 2 groups of my data matrix in R.

My code below works as a for loop. However, my initial goal was to output each 8 plots in one .png file. To that end, I posted the question here.

One of the 'comments' was to use an 'apply' and 'function'. I never wrote a code in R using apply or function.

Here's my input file:

TranscriptID    GeneID  Biotype TranscriptName  CommonNAme  GeneName    TSS-ID  Locus-ID    DNp63D-DMECs-1  DNp63D-DMECs-2  DNp63D-DMECs-3  DNp63WTMECs-1   DNp63WTMECs-2   Fold    2-tailedtest
Test1   TestA   protein_coding  Fun1    Ex1 Ex1 ExA1    ExA1    1.15E-08    2.68E-12    0.005077929 4.99E-07    6.38E-08    6.02E+03    0.495089687
Test2   TestB   protein_coding  Fun2    Ex2 Ex2 ExA2    ExA2    3.69E-08    0.014129129 0.075213367 0.121370367 0.404553833 1.13E-01    0.123434776
Test3   TestC   protein_coding  Fun3    Ex3 Ex3 ExA3    ExA3    4.89E-05    0   0   6.58E-05    1.64E-34    4.96E-01    0.643007583
Test4   TestA   protein_coding  Fun4    Ex4 Ex4 ExA4    ExA4    0.058629449 0   0   0.056200966 0.253314667 1.26E-01    0.180082201
Test5   TestB   protein_coding  Fun5    Ex5 Ex5 ExA5    ExA5    7.80E-06    0   0   1.42E-11    4.20E-36    3.66E+05    0.495026427
Test6   TestC   protein_coding  Fun6    Ex6 Ex6 ExA6    ExA6    0   0   0   0   2.41E-101   0.00E+00    0.272228401
Test7   TestA   protein_coding  Fun7    Ex7 Ex7 ExA7    ExA7    3.77E-08    0.023945749 0.077103517 0.262936167 0.2940195   1.21E-01    0.004479038
Test8   TestB   protein_coding  Fun8    Ex8 Ex8 ExA8    ExA8    9.30E-09    4.82E-14    0.000827853 8.19E-07    7.47E-07    3.52E+02    0.496141526

Here is my for loop code:

input <- read.delim(file="MECs-DNp63IsoformLevels.txt", header=TRUE, sep="\t")
input<-as.matrix(input)

for (i in 1:nrow(input)) {
mean1 <- mean(as.numeric(input[i,12:13]))
mean2 <- mean(as.numeric(input[i,9:11]))
sd1 <- sd(as.numeric(input[i,12:13]))
sd2 <- sd(as.numeric(input[i,9:11]))
sem1 <- sd2/sqrt(length(input[i,12:13]))
sem2 <- sd1/sqrt(length(input[i,9:11]))

mean_sem <- data.frame(mean=c(mean1, mean2), sem=c(sem1, sem2), group=c("WT", "DNp63D-D")) 
mean_sem$group<-factor(mean_sem$group, levels=mean_sem$group, ordered=TRUE) #this prevents ggplot from ordering the x-axis alphabaetically and keeps the order as the input dataframe
theme_set(theme_gray(base_size = 20))
print(i)
p<- ggplot(mean_sem, aes(x=group, y=mean)) + 
  geom_bar(stat='identity', width=.3, colour="black", fill=c("blue", "red")) +
  geom_errorbar(aes(ymin=mean-sem, ymax=mean+sem),
                width=.2) +
  geom_line(aes(colour=group)) +
  scale_colour_manual(values=c("blue", "red")) + 
  xlab('Genotype of MECs') +
  ylab('Quantile Norm FPKM')

q = p +ggtitle(input[i,5])

ggsave(filename=paste(input[i,5],'.png', sep=""), plot=q)

}

Here is my code with the apply function:

input <- read.delim(file="MECs-DNp63IsoformLevels.txt", header=TRUE, sep="\t")
input<-as.matrix(input)
apply(input, 1, function(input) { mean1=mean(as.numeric(input[9:11]))                                  
                                   mean2=mean(as.numeric(input[12:13]))
                                   sd1= sd(as.numeric(input[9:11])) 
                                   sd2 = sd(as.numeric(input[12:13]))

                                  sem1= sd1/sqrt(length(input[9:11]))
                                  sem2= sd2/sqrt(length(input[12:13]))                                  

mean_sem = data.frame(mean=c(mean1, sem1), sem=c(sd1, sem2), group=c("WT", "DNp63D-D")) 

pdf("Test.pdf")
p=ggplot(mean_sem, aes(x=group, y=mean))+ geom_bar(stat='identity', width=.3, colour="black", fill=c("blue", "red"))+ geom_errorbar(aes(ymin=mean-sem, ymax=mean+sem), width=.2)+geom_line(aes(colour=group)) + scale_colour_manual(values=c("blue", "red")) + xlab('Genotype of MECs') + ylab('Quantile Norm FPKM')
q = p +ggtitle(input[1])
ggsave(filename=paste(input[1],'.png', sep=""), plot=q) #plots each figure and gives it a name similar to column 1.
## I need it to plot each 8 figures in 1 png file

})

Can my for loop or function code be optimized? This is literally my first function/apply code I wrote in R and it was more trial and error on the syntax as I saw some people using 'c' with others using multiple {{}{} in each function.