Cuffdiff output filtering based on significance

Question

[1769mkc]

I have cuffdiff output , i have list of genes which im interested in but also i want to filter out genes that passed the significance test so i have column in my dataframe called "significant" which is either "yes" or "no".

I manged to do that i filtered out the significant genes ,now I want to make a comparison plot across samples what is the best way to show differential expression changes in control vs test sample ,any suggestion ?

Answer 1

[firatuyulur]

expression bar plot is a nice one. lets say your main data from cuffdiff is "cuff_data" and your filtered table is "my_significants_filtered". A warning: if you have a couple of hundred significantly differentially expressed genes, your graph will be too crowded. With using a better threshold for p-value, subsetting your data may results in better graphs. you can draw expr. bar plot with a command like this;

ids_to_be_graphed <- my_significants_filtered$geneids
my_genes_to_be_graphed <- getGenes(cuff_data, ids_to_be_graphed)
exp_b_plot <- expressionBarplot(my_genes_to_be_graphed)
exp_b_plot `

I dont really use cuff for rnaseq, XLOC always gives a hard time. In most cases, when you first draw the graph, you dont see the graph itself but you see gene names that are labeling the x-axis. increasing the width and height will let you see your graph.

[1769mkc]

I can make a subset with gene the common name ,wouldn't that be helpful as there is a column after XLOC which contains the gene name ,commonly used name .

[firatuyulur]

If you have the gene names, forget about the XLOC column and go with gene names.