R Code only

$2$ variety plants $($VarX & VarY$),$ each with $2$ conditions $($stress and control$)$

var$\_$x$\_$all $<-$ read$\_$csv$(\text{'}$all$\_$VarX$\_$TwoTimePoints.csv$\text{'})$

Header: gene$\_$name,VarXCRep$\mathrm{.}1,$VarX$1$Rep$\mathrm{.}1,$VarX$2$Rep$\mathrm{.}1,$ VarXCRep$\mathrm{.}2,$VarX$3$Rep$\mathrm{.}2,$ VarX$1$Rep$\mathrm{.}2,$ VarX$2$Rep$\mathrm{.}2,$VarXCRep$\mathrm{.}3,$VarX$3$Rep$\mathrm{.}3,$VarX$1$Rep$\mathrm{.}3,$VarX$2$Rep$\mathrm{.}3$

var$\_$y$\_$all $<-$ read$\_$csv$(\text{'}$all$\_$VarY$\_$TwoTimePoints.csv$\text{'})$

Each variety has differentially expressed genes $($DEGs$)$

var$\_$x$\_$degs $<-$ read$\_$csv$(\text{'}$Leaf$\_$DEGs$\_$VarX.csv$\text{'})$

Header: gene$\_$name, log$2$FoldChange, padj, Athaliana$\_$gene$\_$nameID, Gene$\_$Function, VarXCRep$\mathrm{.}1,$ VarXCRep$\mathrm{.}2,$ VarXCRep$\mathrm{.}3,$ VarX$1$Rep$\mathrm{.}1,$ VarX$1$Rep$\mathrm{.}2,$ VarX$1$Rep$\mathrm{.}3$

var$\_$y$\_$degs $<-$ read$\_$csv$(\text{'}$Leaf$\_$DEGs$\_$VarY.csv$\text{'})$

#INVESTIGATE THE DISTRIBUTION OF EXPRESSION VALUES FOR ALL GENES IN EACH SAMPLE $($Variety X$).$

var$\_$x$\_$all.long $<-$ pivot$\_$longer$($var$\_$x$\_$all, cols$=$VarXCRep$\mathrm{.}1$:VarX$1$Rep$\mathrm{.}3,$names$\_$to $=$ "sample", values$\_$to $=$ "expression"$)$

var$\_$x$\_$plot $<-$ ggplot$($var$\_$x$\_$all.long, aes$($x $=$ sample, y $=$ expression$))+$ geom$\_$boxplot$()+$

DO SAME for VarY

#INVESTIGATE THE DISTRIBUTION OF EXPRESSION VALUES FOR THE DEGs IN EACH SAMPLE $($Variety X$).$

var$\_$x$\_$degs.long $<-$ pivot$\_$longer$($var$\_$x$\_$degs,cols$=$VarXCRep$\mathrm{.}1$:VarX$1$Rep$\mathrm{.}3,$names$\_$to $=$ "sample", values$\_$to $=$ "expression"$))$

var$\_$x$\_$degs$\_$plot $<-$ ggplot$($var$\_$x$\_$degs.long, aes$($x $=$ sample, y $=$ expression$))+$

geom$\_$boxplot$()$

DO SAME for VarY

#HOW MANY DIFFERENTIALLY EXPRESSED GENES ARE THERE IN EACH VARIETY?

var$\_$x$\_$dup $<-$ CODE HERE

var$\_$y$\_$dup $<-$ CODE HERE

#INVESTIGATE IF THE SAME OR DIFFERENT GENES ARE DIFFERENTIALLY EXPRESSED IN THE TWO VARIETIES. Create a suitable plot to look at the overlap in the DEGs between the two Varieties. CODE HERE

#SEPARATE OUT THE UP$-$ AND DOWN$-$ REGULATED DEGs $($BETWEEN STRESS AND CONTROL CONDITION$).$

By looking at $`$var$\_$x$\_$degs$`$ and $`$var$\_$y$\_$degs$`$ data frames, you can see that some genes have a positive log $2$ fold change and others have a negative log $2$ fold change. $*$ Create a data frame called $`$var$\_$x$\_$degs.up$`$ containing only genes that are upregulated in Stress Treatment compared to control in Variety X$.$ CODE HERE

$*$ Create a data frame called $`$var$\_$x$\_$degs.down$`$ containing only genes that are downregulated in Stress Treatment compared to control in Variety X$.$

$*$ Same for VarY. CODE HERE

#INVESTIGATE THE FOLD CHANGE IN GENE EXPRESSION FOR THE DEGs, BETWEEN STRESS AND CONTROL CONDITION.$*$ Create a box plot to show the distribution of log$2$ fold change for all DEGs by variety. Hint: the base R boxplot$()$ command and the abs$()$ function could be helpful here.

$*$ Create a box plot to show the distribution of log$2$ fold change for upregulated DEGs by variety. Hint: the base R boxplot$()$ command could be helpful here.

$*$ Create a box plot to show the distribution of log$2$ fold change for downregulated DEGs by variety. Hint: the base R boxplot$()$ command could be helpful here.

#INVESTIGATE THE FUNCTIONS OF THE DIFFERENTIALLY EXPRESSED $($UPREGULATED$)$ GENES WITH THE LOWEST FOLD CHANGE $*$ Find out the function of the bottom most upregulated gene in Variety X $($lowest fold change$)$ and assign the result to variable called $`$bottom$\_$gene.x$`.$

$*$ Find out the function of the bottom most upregulated gene in Variety Y $($lowest fold change$)$ and assign the result to variable called $`$bottom$\_$gene.y$`.$

#INVESTIGATE THE BEHAVIOUR OF THE BIOLOGICAL REPLICATES FOR THE DEGs in Variety X IN THE TREATMENT TIME POINT.$*$ Create a set of scatterplots to visually inspect how well the different replicates agree$/$correlate for the DEGs in Variety X in the treatment time point.

#INVESTIGATE THE BEHAVIOUR OF THE BIOLOGICAL REPLICATES FOR THE DEGs in Variety X IN THE CONTROL TIME POINT.$*$ Create a set of scatterplots to visually inspect how well the different replicates agree$/$correlate for the DEGs in Variety X in the control time point.

#COMPARE THE MEAN EXPRESSION IN TREATMENT VERSUS CONTROL REPLICATES FOR EACH DEG. $*$ Modify your data frame $`$var$\_$x$\_$degs$`$ to include two new $($additional$)$ columns as follows:$*$ The first new column should be named $`$control$\_$mean$`$ and contain the mean expression value for the three control replicates.

$*$ The second new column should be named $`$stress$\_$mean$`$ and contain the mean expression value for the three stress treatment replicates.

#PRIORITISE GENES OF INTEREST FOR FURTHER INVESTIGATION.$*$ Create a data frame called $`$var$\_$y$\_$degs.up$.$big$`$ containing only genes in Variety y that are upregulated in Stress Treatment compared to control, have at least an $2$ fold absolute change in expression and have a p value less than $1$e$-06.*$Hint: remember you are dealing with log $2$ fold change.