Visualization with CummeRbund - Jeanielmj/bioinformatics-workshop GitHub Wiki
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CummeRbund
Running CummeRbund
Running on MGHPCC
Step 5. Explore differential analysis results with CummeRbund
A) First load R and enter R environment
module load R
R
B) Within R environment, set up cummeRbund
source("http://bioconductor.org/biocLite.R")
biocLite("cummeRbund")
C) Load cummeRbund library and read in the differential expression results.
If you save and exit the R environment and return, these commands must be executed again.
library(cummeRbund)
cuff_data <- readCufflinks('diff_out')
D) Use cummeRbund to visualize the differential expression results. NOTE: Any graphic outputs will be automatically saved as "Rplots.pdf" which can create problems when you want to create multiple plots with different names in the same process. To save different plots with different names, preface any of the commands below with the command:
pdf(file="myPlotName.pdf")
And after executing the necessary commands, add the line:
dev.off()
Thus, to use the csScatter command and save the results in a file called scatterplot.pdf, one would execute the following commands:
pdf(file="scatterplot.pdf")
csScatter(genes(cuff_data), 'C1', 'C2')
dev.off()
To pull out significantly differentially expressed genes and isoforms
gene_diff_data <- diffData(genes(cuff_data))
sig_gene_data <- subset(gene_diff_data, (significant == 'yes'))
nrow(sig_gene_data)
isoform_diff_data <-diffData(isoforms(cuff_data))
sig_isoform_data <- subset(isoform_diff_data, (significant == 'yes'))
nrow(sig_isoform_data)
To draw a scatterplot
csScatter(genes(cuff_data), 'C1', 'C2')
To plot gene level and isoform level expression for gene regucalcin
mygene1 <- getGene(cuff_data,'regucalcin')
expressionBarplot(mygene1)
expressionBarplot(isoforms(mygene1))
To plot gene level and isoform level expression for gene Rala
mygene2 <- getGene(cuff_data, 'Rala')
expressionBarplot(mygene2)
expressionBarplot(isoforms(mygene2))
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