@@ -37,16 +37,20 @@ where counts K ij for gene i, sample j are modeled using a Negative Binomial dis
fitted mean µ ij and a gene-specific dispersion parameter α i . The fitted mean is composed of a
sample-specific size factor s j and a parameter q ij proportional to the expected true concentration of fragments for sample j. The coefficients β i give the log2 fold changes for gene i for each column of the model matrix X. <br/>
### 4) Wald Test H0:
### 4) Wald Test:
Test if Log(FC) = 0 <br/>
H0: Test if Log(FC) = 0 <br/>
With DESeq2, the Wald test is the default used for hypothesis testing when comparing two groups. The Wald test is a test of hypothesis usually performed on parameters that have been estimated by maximum likelihood. The Wald test is also a standard way to extract a P value from a regression fit.
## Investigations
Let µ and alpha constant between samples, replicates and genes
N.B: Don't forget to change your home path in ```src/main.R```
Let µ and alpha constant between samples, replicates and genes (absolutely false IRL)
