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Code Block
titleGet set up
#IF YOU HAVE NOT COPIED THIS OVER ALREADY
cds
cd my_rnaseq_course
cp -r /corral-repl/utexas/BioITeam/rnaseq_course_2015/day_3_partB/cuffdiff_results .

IF YOU HAVE ALREADY COPIED IT OVER
cds
cd my_rnaseq_course
cd day_3_partB/cuffdiff_results
 

#We need the cuffdiff results because that is the input to cummeRbund.

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Code Block
pdf(file="scatterplot.pdf")

csScatter(genes(cuff_data), 'C1', 'C2')

dev.off()

 
#How does this plot look? What is it telling us?

The resultant plot is here.


Exercise 2a:  Pull out from your data, significantly differentially expressed genes and isoforms.

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Code Block
titleTo pull out genes
#Below command is equivalent to looking at the gene_exp.diff file that we spent a lot of time parsing yesterday
gene_diff_data <- diffData(genes(cuff_data))   
#Do gene_diff_data followed by tab to see all the variables in this data object
 
sig_gene_data  <- subset(gene_diff_data, (significant ==  'yes'))
up_gene_data  <- subset(sig_gene_data, (log2_fold_change > 1))
#How many
nrow(up_gene_data)
  
down_gene_data <- subset(sig_gene_data, (log2_fold_change < -1))
nrow(updown_gene_data)


Exercise 3: For a gene, regucalcin, plot gene and isoform level expression.

Code Block
titleTo plot gene level and isoform level expression for gene regucalcin
pdf(file="regucalcin.pdf")
mygene1 <- getGene(cuff_data,'regucalcin')
expressionBarplot(mygene1)
expressionBarplot(isoforms(mygene1))
dev.off()

The resultant plot is here.

 

Exercise 4: For a gene, Rala, plot gene and isoform level expression.

Code Block
titleTo plot gene level and isoform level expression for gene Rala
pdf(file="rala.pdf")
mygene2 <- getGene(cuff_data, 'Rala')
expressionBarplot(mygene2)
expressionBarplot(isoforms(mygene2))
dev.off()

The figure is here.

Take cummeRbund for a spin...

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Expand
Solution
Solution
Code Block
titleR command to generate box plot of gene level fpkms
csBoxplot(genes(cuff_data))
Code Block
titleR command to generate box plot of isoform level fpkms
csBoxplot(isoforms(cuff_data))

The resultant graph is here.

 

Expand
Hint
Hint

Use csBoxplot function on cuff_data object to generate a boxplot of gene or isoform level fpkms.

The resultant plot is here.

Exercise 6: Visualize the significant vs non-significant genes using a volcano plot.

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Expand
Hint
Hint

Use csVolcano function on cuff_data object to generate a volcano plot.

The resultant plot is here.

 

Exercise 7: MORE COMPLICATED! Generate a heatmap for genes that are upregulated and significant.

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Expand
Hint
Hint

Use csHeatmap function on the up_gene_data data structure we created. But its a little tricky.

The resultant plot is here.