hi, i would kindly ask you for help, because i have been strugling with this issue for few weeks. Basically i would like to know how can i check if my qRT-PCR data has normal distribution so i can know should i use parametric or non-parametric test in my further analysis. I have 23 different clinical isolates of bacteria K.pneumoniae (ertapenem non-susceptible) and 1 control sample (ATCC 13883, which is susceptible to ertapenem), my mentor told me to see if there are any changes in gene expression (ompK35 and ompK36 genes) in clinical isolates compared to control sample (ATCC 13883) by using qRT-PCR. Problem is that i don't know how to determine distribution of data because most of examples are based on tretament vs.non-treatment samples, and i dont have that kind of experiment. Should i put fold change vaules of both genes together when checking distribution or should i do it for each gene per se?
Hi Mia
I have not seen somebody check normal distribution of qPCR data, either relative or absolute. All you need to care is MIQE guide line: doi: 10.1373/clinchem.2008.112797.
Good luck
Basically i would suggest you to do fold change value of genes or else you can do differential expression of gene over control using Log10 ratio in which you can campare the expressivity 23 different clinical isolates of bacteria over control.
For log10 ratio
=Log10 ( 2^(ΔΔCt)).
*represent the LOG10 ratio in a single bar graph.
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