Hi,

I have rnaseq (some disease) samples from 7 families and my sample info is described below (affected=A, normal=N):

sample,family,condition,sex
AB1,1,A,F
AB2,1,N,F
AB3,2,A,M 
AB4,2,N,F
AB5,3,A,M
AB6,3,N,M
AB7,3,N,F
AB8,4,A,M
AB9,4,N,F
AB10,5,A,F
AB11,5,N,M
AB12,5,N,F
AB13,6,A,M
AB14,6,N,M
AB15,6,N,F
AB16,7,A,M
AB17,7,N,F

I am interested in the following comparisons:

1) condition_A_vs_N

2) All pairwise comparisons between affected samples from different families: A1_vs_A2, A1_vs_A3, .... (16 comparisons/DEGs lists).

3) Comparisons between affected samples from different families vs overall normal: A1_vs_N, A2,_vs_N, ...(7 DEGs lists)

I have tried:

1)

  dds <- DESeqDataSetFromTximport(txi, colData = samples, design = ~ family + condition )  
  dds$group <- factor(paste0(dds$condition,dds$family)) 
  design(dds) <- ~ group 
  dds <- DESeq(dds)
  resultsNames(dds) 
             [1] "Intercept"      "group_N2_vs_N1" "group_N3_vs_N1" "group_N4_vs_N1" "group_N5_vs_N1" "group_N6_vs_N1" "group_A1_vs_N1" "group_A2_vs_N1"
             [9] "group_A3_vs_N1" "group_A4_vs_N1" "group_A5_vs_N1" "group_A6_vs_N1"

If I use contrast option, I can get 2. (one of the comparisons as an example), but not 1 and 3:

   results(dds, contrast=c("group", "A1", "A2")) 

    log2 fold change (MLE): group A1 vs A2 
    Wald test p-value: group A1 vs A2 
....................

2)

dds <- DESeqDataSetFromTximport(txi, colData = samples, design = ~ family + condition + family:condition)    
dds <- DESeq(dds)
resultsNames(dds) 
 [1] "Intercept"     "family_2_vs_1" "family_3_vs_1" "family_4_vs_1" "family_5_vs_1" "family_6_vs_1" "condition_A_vs_N"  
 [8] "family2.conditionA" "family3.conditionA" "family4.conditionA" "family5.conditionA" "family6.conditionA"

Here, I get 1 (condition_A_vs_N), but not 2 and 3.

Do I need to use different design models to get the required comparisons? Please guide how should I proceed so that I can get 1, 2 and 3.

Also, as per manual, "The LRT is therefore useful for testing multiple terms at once, for example testing 3 or more levels of a factor at once, or all interactions between two variables." Here I have more than 3 levels, should I go for LRT?

Thanks.



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