Hello everyone, I'm trying to find the best way to do my analysis - specifically, my contrasts. I have samples nested and grouped, thus I'm afraid I have made some errors here.

My experiment is as follows: I have RNASeq data consisting of the following features for each patient: ID, Age, Sex, and whether he/she has any number of active phenotypes (marked 1..N). From each patient, two samples were taken, lesional and non-lesional (L & N respectively).

Here is a sample table; For simplicity, let's assume only two phenotypes are measured.

   PatientID     Age   Sex  SampleType          Phenotype1    Phenotype2 ,..., PhenotypeN

   1             10    M    L                   FALSE         TRUE
   1             10    M    N                   FALSE         TRUE
   2             20    F    L                   TRUE          TRUE
   2             20    F    N                   TRUE          TRUE
   3             30    M    L                   TRUE          FALSE
   3             30    M    N                   TRUE          FALSE
...

My research questions can be split into these four "prototypes":

1. What are the DEGs between Lesional and Non-Lesional samples, for those with Phenotype1=<FALSE> and phenotype2=<TRUE>, or any other combination of the two (±adjusted for age & sex)
2. What is the "difference of differences" between phenotype1 (TRUE vs FALSE) and SampleType (L vs NL)?
3. What are the DEGs between Lesional and Non-Lesional samples, for those with Phenotype1=<FALSE> regardless of phenotype 2, and vice-versa (±adjusted for age & sex)
4. What are the DEGs between Phenotype1 = <TRUE> and Phenotype1=<FALSE>, within the lesional group and within the non-lesional group?

I have read some posts regarding these questions, but I'm still uncertain:

  mydesign<-model.matrix(~Age + Sex + SampleType*Phenotype1 + SampleType*Phenotype2, data=sample_data)
  colnames(mydesign)<-make.names(colnames(mydesign))

  #colnames(mydesign): "X.Intercept."               "Age"                        "SexM"                       "SampleTypeL"                           
  #                    "Phenotype1TRUE"           "Phenotype2TRUE"             "SampleTypeL.Phenotype1TRUE" "SampleTypeL.Phenotype2TRUE"

  makeContrasts(LvsN_P1FALSE_P2TRUE = SampleTypeL + SampleType.Pheonotype2TRUE
                  LvsN_vs_P1TRUEvsFALSE = SampleTypeL.Pheonotype2TRUE
                  LvsN_P1TRUE_P2dontcare =  SampleTypeL + (SampleTypeL.Phenotype2TRUE/2) + SampleTypeL.Phenotype1TRUE
                  P1TRUEvsFALSE_SampleTypeL = Phenotype1TRUE + SampleTypeL.Phenotype1TRUE
                  levels=mydesign)

Edited: I'll explain the rationale behind "LvsN_P1TRUE_P2dontcare":

LvsN_P1TRUE_P2dontcare = 
(Mean of all samples where [SampleType=L] and [Phenotype1 = TRUE]) - (Mean of all samples where [SampleType=N] and [Phenotype1 = TRUE]) =
((Samples of [SampleType=L], [Phenotype1 = TRUE], [Phenotype1 = FALSE]) + (Samples of [SampleType=L], [Phenotype1 = TRUE], [Phenotype1 = FALSE])) / 2 - 
((Samples of [SampleType=N], [Phenotype1 = TRUE], [Phenotype1 = FALSE]) + (Samples of [SampleType=N], [Phenotype1 = TRUE], [Phenotype1 = FALSE])) / 2 =
(SampleTypeL +  SampleTypeL + SampleTypeL.Phenotype1TRUE + SampleTypeL.Phenotype1TRUE + SampleTypeL.Phenotype2TRUE)/2 = 
(SampleTypeL + (SampleTypeL.Phenotype2TRUE/2) + SampleTypeL.Phenotype1TRUE)

Am I correct here? is that the way to create the contrasts?

Thank you! Jonathan