Are you able to show your full code?

library(cummeRbund) #load cummeRbund packages

 cuff_data <- readCufflinks('Wt_vs_Control_Blind_Dispersion_chr8') #reads diff_out file from cuffdiff

pdf(file="practice.pdf") #name of scatter plot

csScatter(genes(cuff_data), 'S1', 'S2') #creates scatter plot of all gene fpkm values for S1 and S2

dev.off()

This successfully creates a scatter plot for S1 and S2 for all genes , but I want to know how to specify only chromosome 8. I would think there's a line of code to specify that, but Im not sure what that would be and I can't find examples.

I've not done this specifically but look at subsetting the cuff_data

e.g if you have a column (called chromosome) which says where the genes are located you can do something like

cuff_data_sub <- cuff_data[cuff_data$chromosome == 8]

It sounds like you just need to remove rows of genes not on chromosome 8, theres plenty online about how to subset (try dplyr), above is just an example if you had a specific column. Then you can just replace "cuff_data" in your csScatter to "cuff_data_sub"

Have a look at cummeRbund repository on GitHub, they usually have plenty of examples too

You know what, its really a scaling size issue. For one sample I have a fpkm value of 80,000 and the other sample only goes up to about 5,000 fpkm. So cummeRbund creates a log transformed scale for the axis with 80,000 fpkm, but not the other one. Im trying to delete the few points where they are above 20,000 in one sample, but its not working. The readcufflinks command creates a cuffData.db, so I don't know how to get rid of those outliers.