Question: qRT-PCR analysis : average triplicates for statistical testing
0
gravatar for Nicolas Rosewick
3.7 years ago by
Belgium, Brussels
Nicolas Rosewick8.0k wrote:

Hi,

I've qRT-PCR data to analyze. Two cell lines, each cell lines treated with 5µL and 10µL treatment. Each treatment was perfomed in each cell lines twice, and triplicates were performed in the qRT-PCR experiments. Thus for each cell line and treatment I have two triplicates. For example for cell line A here are the different sample analyzed in qRT-PCR. ( e.g. 5µL_treatment.1 and 5µL_treatment.2 are the same treatment but done in different tubes)

Sample Treatment
A Mock
A Mock
A Mock
A 5µL_treatment.1
A 5µL_treatment.1
A 5µL_treatment.1
A 5µL_treatment.2
A 5µL_treatment.2
A 5µL_treatment.2
A 10µL_treatment.1
A 10µL_treatment.1
A 10µL_treatment.1
A 10µL_treatment.2
A 10µL_treatment.2
A 10µL_treatment.2

I've performed 2^ddct analysis and now want to perform a stat test (Mann-Whitney). Do I have to average the triplicate before doing the test or should I use all technical replicates in my analysis.

Thanks

 

 

statistics qrt-pcr replicates • 1.7k views
ADD COMMENTlink modified 3.7 years ago by Devon Ryan91k • written 3.7 years ago by Nicolas Rosewick8.0k
0
gravatar for Devon Ryan
3.7 years ago by
Devon Ryan91k
Freiburg, Germany
Devon Ryan91k wrote:

You need to do the averaging before the test. Otherwise you'd be lying to yourself about how much statistical power you had.

BTW, unless you're hitting a ceiling/floor effect you might use a T-test instead (though only having two replicates limits what you'll be able to detect).

ADD COMMENTlink written 3.7 years ago by Devon Ryan91k

Ok thanks that's what I thought

ADD REPLYlink written 3.7 years ago by Nicolas Rosewick8.0k

you recommend a t-test for qRT-PCR analysis ? on 2^ddct, or dCTs ?

ADD REPLYlink written 3.7 years ago by Nicolas Rosewick8.0k

I usually just used the dCt values. The Mann-Whitney test is mostly useful when you start hitting the Ct detection limit. Then you really need a non-parametric, otherwise you'll have better power with a T-test (unless of course the normality assumption is sufficiently violated...but with so few samples you'll have to just assume that).
 

ADD REPLYlink written 3.7 years ago by Devon Ryan91k
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