Is their a particular fold difference or any statistical method to find whether the q pcr result for a treated sample and untreated sample are significant or not?
The answer to this question depends on the experimental design. If you have sufficient replication of your treated and untreated (minimum of 3 reps) then you can use ANOVA with a post hoc test such as Tukey's test to assess significance.
The answer to this question depends on the experimental design. If you have sufficient replication of your treated and untreated (minimum of 3 reps) then you can use ANOVA with a post hoc test such as Tukey's test to assess significance.
Or you can use this program:
http://rest-2009.gene-quantification.info/
Dear Nithin
as indicated by Andrew, a statistical test like ANOVA would establish significance or not between treated and untreated samples
In essence, based on fundamental statistical considerations if your two sets of samples differ by more than 2 x standard deviations from each others mean (based on N+/> 3) then they fall outside each others 95% confidence interval and are thus likely to be statistically different with a p value of 0.05
You cannot perform statistical significance tests on n=1. If you only have one sample per "group," your best bet is to arbitrarily choose a fold-change cutoff (usually a FC>2). Obviously a very large difference in expression (i.e., large FC) is more likely to be of biological significance, but you would still need to validate this result with more replicates.
Even if you had more replicates per groups, not certain that you would want to use ANOVA with a post hoc test when a simple student t-test would suffice.
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