Are the results ranked strictly by fold change?
No the results are not ranked strictly by fold change. When a single gene normalizer is selected, gene expression changes are typically ranked by their magnitude of change using the ΔΔCt method, with those genes showing the largest fold changes ranked as most significant. Unfortunately, these large changes in gene expression may mask small, but biologically important changes in gene expression, such as master regulator genes (e.g., transcription factors). In biological systems, however, larger is not always synonymous with importance. The Global Pattern Recognition™ Analysis Tool algorithm is optimally suited to generate a ranked list of significantly changed genes within a Real-Time PCR dataset. This unique algorithm and accompanying software overcomes the problem of identifying invariant normalizers and the pitfalls of producing faulty statistics based merely on magnitude of change. Only after the genes are statistically ranked is the magnitude of the change calculated. Global Patter
