Hi good day,

This is my first time working on differential gene expression analysis using DeSeq2. I am having a problem to construct my model matrix for DeSeq2 since I have a very complex experimental design (3 factors design) with the following information;

ID Ewed Lambd Sex 1768 HIGH CONV M 1774 HIGH CONV F 1778 HIGH CONV F 1788 HIGH CONV F 1796 HIGH CONV M 1766 LOW CONV F 1772 LOW CONV M 1784 LOW CONV M 1810 LOW CONV F 1816 LOW CONV M 1818 LOW CONV F 1822 LOW CONV M 1826 LOW CONV F 1828 LOW CONV F 1764 NORM CONV F 1770 NORM CONV F 1782 NORM CONV M 1792 NORM CONV M 1802 NORM CONV F 1804 NORM CONV F 1755 HIGH HCHF M 1767 HIGH HCHF F 1777 HIGH HCHF F 1787 HIGH HCHF M 1799 HIGH HCHF M 1823 HIGH HCHF F 1759 LOW HCHF M 1775 LOW HCHF F 1783 LOW HCHF M 1785 LOW HCHF M 1807 LOW HCHF F 1821 LOW HCHF M 1827 LOW HCHF F 1761 NORM HCHF F 1763 NORM HCHF F 1769 NORM HCHF M 1789 NORM HCHF M

I would like to construct the model matrix for three way interaction effects (Ewed:Lambd:Sex) but could not do so in which I got this error "the model matrix is not full rank".

Ewed: Maternal diet Lambd: offspring diet

Could anyone suggest me what can or should I do? I read the DeSeq2 vigenette about this kind of problem but could not really understand it.

Your help is much appreciated.

Best, Mila

For users with complex designs involving many interactions, and who are not very familiar with the terms in R’s linear models, I recommend to collaborate with a statistician. I don’t have much time this semester to answer questions that go beyond the DESeq2 software and are more statistical consulting.