



Differential gene expression wordcloud of azacytidine treated AML3 cells treated with azacytidine.  The left panel shows the up-regulated genes and the right panel shows the down-regulated genes.  Font size is proportional to the exponent of the p-value. 

Script used to process data





awk '$6<0 && $8<0.05 {print $1,$8}' DESeq.xls \

| awk '{printf "%4.3e\t%s

", $3 , $2}' \

| sed 's/e-/@/' | cut -d '@' -f2- | awk '{print $2":"$1}' > dns.txt









You have probably seen word clouds before - but have you tried with gene expression data?I used the following bash script to process a DESeq spreadsheet from a a previous RNA-seq post .  The script extracts the gene name and p-value of the genes with differential expression.  I used awk to separate the up and down regulated genes into different files.  The score used to inform the font size is the exponent of the p-value.  So this works best when there are a lot of statistically significant genes p-values.  The data looks like this:AC011899.9:60CAMK1D:54GNG4:44CGNL1:41APCDD1:37HSD11B1:33Now go to the "advanced" tab of the Wordle page and paste in the data.  Experiment, with the colours, layouts and be sure to increase the "maximum words" to get a real appreciation for the number of changes in your experiment.  Here is an example I made using both the up and down regulated gene sets showing the effect of azacytidine on AML3 cells.  The result is pretty amazing.awk '$6>0 && $8<0.05 {print $1,$8}' DESeq.xls \| awk '{printf "%4.3e\t%s

", $3 , $2}' \| sed 's/e-/@/' | cut -d '@' -f2- | awk '{print $2":"$1}' > ups.txt