Dear all,

I have to test for differential expression some qPCR experiments made for 7
genes. I am using the Delta Cts and I am fitting a linear model to acess if
cell type (2 levels) has a significant effect in gene expression.
I would like to understand the results that I m getting.

When testing the control gene, I am using the Ct values and I am fitting a
linear model lm(Ct~cell_type) this gives me a p-value <0.05, meaning that I
should refuse the null hypothesis and that is being differentially
expressed by cell type, however when fitting the model lm(Ct~0+cell_type),
I get what is supposed, p>0.05, so this gene is not affected by cell type,
what is what I want.

When testing for the target genes, I am getting  for the model
lm(Ct~0+cell_type) p_value<0.05, what is what I expect since my previous
microarray experiment showed this genes are differentially expressed. the
model with the intercept is not significant.

So these results seem to show that qPCR fits should pass into the origin.
Is this true? If it is why is that?

Thanks in advance for the help.
Kind regards,

Andreia

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Andreia J. Amaral, PhD
BioFIG - Center for Biodiversity, Functional and Integrative Genomics
Instituto de Medicina Molecular
University of Lisbon
Tel: +352 217500000 (ext. office: 28253)
email:andreiaamaral@fm.ul.pt ; andreiaamaral@fc.ul.pt

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