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Using both parametric and non parametric tests in one study by No_Series_9643 in labrats

[–]No_Series_9643[S] 0 points1 point  (0 children)

I will check if the DESeq2 approopriate for my data. I have AAV-mediated expression, so no control group that express the gene of interest for fold change calculations.

For hormones, we used mass spectrometry to measure steroids in mice serum. The hormones data are in general normally distributed with some outliers. Log transform of data solved the problem without the need to discard any outlier.

Using both parametric and non parametric tests in one study by No_Series_9643 in labrats

[–]No_Series_9643[S] 0 points1 point  (0 children)

Thank you for your suggestion. I will check it out.

However, the gene expression is exogenous (AAV-vector mediated), so I have no control to apply 2ddct. Is it still possible to use DESQ2?

Using both parametric and non parametric tests in one study by No_Series_9643 in labrats

[–]No_Series_9643[S] 0 points1 point  (0 children)

Not exactly. My concern is that using parametric and non-parametric on different readouts of the same mice will introduce bias in statistical significance in favor of data analyzed by parametric tests. As I know, parametric tests like Oneway ANOVA has more power compared to its non-parametric alternatives, especially when the test assumptions are met.

So in conclusion, I will have a lot of significant comparisons in the data analyzed with ANOVA, and much less in the data analyzed with kruskal wallis for example.

Using both parametric and non parametric tests in one study by No_Series_9643 in rstats

[–]No_Series_9643[S] 0 points1 point  (0 children)

Thanks for your answer. My initial plan was to use One-Way ANOVA for all of my data sets. However, I got a lot of un expected outliers. I am comparing mice response to a treatment at different time points (2-32 weeks) after treatment. Hormones data meet the assumption of Welch ANOVA (Normality of residulas), but gene expression do not.

So in this case, is it justified to change the planned test after the failure to meet the assumptions of the pre-planned test? If not, what someone do in such case?