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head results/deseq2_kallisto_C1_vs_C2.csv |
Find the top 10 upregulated genes
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title | Find the top 10 upregulated genes |
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#DESeq2 results
sed 's/,/\t/g' results/deseq2_kallisto_C1_vs_C2.csv|sort -n -r -k3,3|cut -f 1,3|head
#Notice the idiosyncracy with sort
sed 's/,/\t/g' results/deseq2_kallisto_C1_vs_C2.csv|sort -n -r -k3,3|grep -v 'e-0'|cut -f 1,3|head |
Find the top 10 downregulated genes
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title | Find the top 10 upregulated downregulated genes |
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#DESeq2 results
sed 's/,/\t/g' results/deseq2_kallisto_C1_vs_C2.csv|sort -n -k3,3|cut -f 1,3|head
#Notice the idiosyncracy with sort
sed 's/,/\t/g' results/deseq2_kallisto_C1_vs_C2.csv|sort -n -k3,3|grep -v 'e-0'|cut -f 1,3|head |
2. Select DEGs with following cut offs- Fold Change >=2 (or <= -2) (this means log 2 fold change >= 1 or <=-1) and adj p value < 0.05 and count how many DEGs we have
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title | Count the number of DEG |
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#DESeq2 results
sed 's/,/\t/g' results/deseq2_kallisto_C1_vs_C2.csv|awk '{if ((($3>=1)||($3<=-1))&&($7<=0.05)) print $1,$3,$7}'|wc -l
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If you wanted to use DESeq2 for more complicated designs (with multiple factors, multiple levels), you can by adjusting two things: design and contrast.
Advanced options
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