@@ -28,18 +28,19 @@ Fit a curve to wise gene dispersion estimate
### 3) Fit linear model
The differential expression analysis uses a generalized linear model of the form:
The differential expression analysis uses a generalized linear model of the form:<br/>
Kij ∼ NB(µij , α i )<br/>
µij = s j q ij <br/>
log 2 (q ij ) = x j. β i <br/>
where counts K ij for gene i, sample j are modeled using a Negative Binomial distribution with
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 col-
umn of the model matrix X. The sample-specific size factors can be see as the logFC between condition.
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.
x j. β i can be see as the logFC between condition (for treated condition).
