Question: What is the exact formula for the calculation of Fold Change (FC), p-val and q-val in Ballgown stattest?
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gravatar for ag1805x
12 months ago by
ag1805x10
University of Allahabad
ag1805x10 wrote:

I am looking for the exact formula for the calculation of Fold Change (FC), p-val and q-val in Ballgown stattest?

By using gexpr I got the gene expression values for the list of genes. For better understanding I tried to calculate the FC for a few genes manually but the values I obtained differed from the values given by stattest. Can you please help regarding this?

ballgown fold change stattest • 247 views
ADD COMMENTlink modified 12 months ago by James W. MacDonald49k • written 12 months ago by ag1805x10
Answer: What is the exact formula for the calculation of Fold Change (FC), p-val and q-v
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gravatar for James W. MacDonald
12 months ago by
United States
James W. MacDonald49k wrote:

From the vignette:

The default statistical test in ballgown is a parametric F-test comparing nested linear models; details are available in the Ballgown manuscript (Frazee et al. (2014)). These models are conceptually simialar to the models used by Smyth (2005) in the limma package. In limma, more sophisticated empirical Bayes shrinkage methods are used, and generally a single linear model is fit per feature instead of doing a nested model comparison, but the flavor is similar (and in fact, limma can easily be run on any of the data matrices in a ballgownobject).

Ballgown's statistical models are implemented with the stattest function. Two models are fit to each feature, using expression as the outcome: one including the covariate of interest (e.g., case/control status or time) and one not including that covariate. An F statistic and p-value are calculated using the fits of the two models. A significant p-value means the model including the covariate of interest fits significantly better than the model without that covariate, indicating differential expression. We adjust for multiple testing by reporting q-values (Storey & Tibshirani (2003)) for each transcript in addition to p-values: reporting features with, say, q < 0.05 means the false discovery rate should be controlled at about 5%.

If you want to know what you are doing, there is no substitute for reading the original manuscript.

ADD COMMENTlink written 12 months ago by James W. MacDonald49k
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