Sunday, March 15, 2015

Clustering of genes: treatment vs individual

Here I have used DESeq to cluster RNASeq data from top 100 expressed genes in human smooth muscle cells from coronary arteries, from two different individuals, treated 1h or 6 hours with TGF beta.

Interestingly, the clustering has grouped cells from the same individual, and not from the same treatment.

Even though here we have only two samples, we might hypothesize the following.

Transcriptomes (or at least the part that is intensively expressed) are thus highly specific for the individual and resistant to the changes that the highly efficient and perturbing molecule like TGF beta would introduce into the cell, and they would stay in a stable equilibrium i.e. in the intrinsic state of the system that is specific for the each individual.

Only the PCA plot would reveal that the complete transcriptome has begun to shift under the influence of the drug and that the effect of the drug on the variance is almost equal as the effect of the individual. Still, even that the effect of the growth factor is visible, the biggest component of the variance, PC1, remains the individual donor of the cells.

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