Dear all,
I am hoping you can help the correct test for my experimental design which is as follows: I tested the cells of 3 different donors (rotator cuff tears), on 8 different nano fibre scaffolds (different anisotropy; random vs aligned and different fibre diameters; 300nm,1000nm,2000 and 4000).
I wish to compare the effects of each nano scaffold against all other scaffolds e.g. aligned300 vs aligned 1000 or aligned300 vs random4000, creating 56 possible comparisons.
Do do this I have constructed the following data frame:
samplenames<meta_data$SampleID samples < data.frame((samplenames),donor=as.factor(c(rep("1",4),rep("2",4),rep("3",4))), anisotrophy=as.factor(c(rep("aligned",12), rep("random",12))), diameter=as.factor(rep(c("300","1000","2000","4000"),6)))
X.samplenames. <fctr> 
donor <fctr> 
anisotrophy <fctr> 
diameter <fctr> 


i25Healthy1Aligned300  1  aligned  300  
i26Healthy1Aligned1000  1  aligned  1000  
i27Healthy1Aligned2000  1  aligned  2000  
i28Healthy1Aligned4000  1  aligned  4000  
i33Healthy2Aligned300  2  aligned  300  
i34Healthy2Aligned1000  2  aligned  1000  
i35Healthy2Aligned2000  2  aligned  2000  
i36Healthy2Aligned4000  2  aligned  4000  
i41Healthy3Aligned300  3  aligned  300  
i42Healthy3Aligned1000  3  aligned  1000 



Q1: Having read the Deseq2 manual I think that in order to undertake the multiple comparisons, I need to perform the LRT analysis, is this correct?
With this in mind I have undertaken the following:
dds_multi< DESeqDataSetFromMatrix(countData =healthy, colData=samples, design=~donor+anisotrophy+diameter+donor:anisotrophy+donor:diameter+anisotrophy:diameter) keep < rowSums(counts(dds_multi)) >= 10 dds < dds_multi[keep,] dds_multi < DESeq(dds_multi, test="LRT", reduced=~donor + anisotrophy + diameter)
This gives me the following results:
resultsNames(dds_multi)
[1] "Intercept" "donor_2_vs_1" [3] "donor_3_vs_1" "anisotrophy_random_vs_aligned" [5] "diameter_2000_vs_1000" "diameter_300_vs_1000" [7] "diameter_4000_vs_1000" "donor2.anisotrophyrandom" [9] "donor3.anisotrophyrandom" "donor2.diameter2000" [11] "donor3.diameter2000" "donor2.diameter300" [13] "donor3.diameter300" "donor2.diameter4000" [15] "donor3.diameter4000" "anisotrophyrandom.diameter2000" [17] "anisotrophyrandom.diameter300" "anisotrophyrandom.diameter4000"
I then report each comparison in turn until I get results for each of the 56 possible comparisons, for example:
res1< results(dds_multi, alpha = 0.05, name = "diameter_2000_vs_1000", test="Wald") or res2< results(dds_multi, alpha = 0.05, contrast=list(c("diameter_2000_vs_1000","anisotrophyrandom.diameter2000")), test="Wald")
Q2: Is this the correct way to do this?
thanks for any help that can be offered,
Mat