I have SRM data and analysed the data with a mixed model by using the function:

model.linear <- dataProcess(raw = raw,
                            normalization = 'equalizeMedians',
                            summaryMethod = 'linear',
                            censoredInt = NULL,
                            MBimpute = FALSE)

sessionInfo()
R version 4.0.4 (2021-02-15)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 17134)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252   
[3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C                          
[5] LC_TIME=English_United States.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] dplyr_1.0.5    MSstats_3.23.1

The model on the background is: Formula: ABUNDANCE ~ GROUP + (1 | SUBJECT)

I however do not understand the model. I read the suppl material from Chang 2012.

A group variable is created that gets the values 0 for the reference levels (heavy), and 1, 2, 3 for the endogenous levels according to the 3 treatments

A subject variable is created that gets the values 0 for the reference levels (heavy), and 1, 2, 3 for the endogenous levels according to the 3 biological repeats

From the output of the linear model I have to assume that the data for the reference is not taken into account as the intercept is the average estimated log2 abundance for group1, the coeff for group 2 is then the diff in log2 abundance between group 2 and group 1 and the coeff for group 3 is then the diff in log2 abundance between group 3 and group 1.

generated output from testResultOneComparison$fittedmodel[[level]]

Fixed Effects: (Intercept) GROUP2 GROUP3
17.6156 -0.1218 -0.3262