Dear all, I am performing a very simple limma voom analysis on 2 groups, but I am getting different results when I use make.contrasts() and when I don't. The aim is simply to find differentially expressed genes between 2 groups. I have read the limma voom guide and edgeR guide but they seem to give different examples (using make.contrasts and not, which gives me different results). I am wondering if you might be able to identify the issue? Thanks very much in advance.

myvec
  [1] 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1
 [38] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
 [75] 1 1 1 1 1 1 1 1 0 1 1 1 1 1 0 0 0 1 1 0 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
[112] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 0 1 1 1 1 1 1
[149] 1 1 1 1 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1
[186] 1 1

d <- DGEList(counts=samples2, group=myvec)
d <- calcNormFactors(d)
group <- d$samples$group
mm <- model.matrix(~0 + group)
y <- voom(d, mm, plot = F)
#### here I try to fit without contrasts
fit <- lmFit(y, mm)
fit2 <- eBayes(temp)

#### here I try to fit with contrasts
contr <- makeContrasts(group1 - group0, levels = colnames(coef(fit)))
temp <- contrasts.fit(fit, contr)
fit3 <- eBayes(temp)

#### topTable(fit2) and topTable(fit3) produce very different results, with p values in the former being 10e-300 and those in the latter being 10e-6


> head(fit3$coefficients)
                    group0     group1
ENSG00000227232  0.9232934  0.7042146
ENSG00000225972 -0.2555306 -1.3402430
ENSG00000225630  6.6519330  6.4041992
ENSG00000237973  4.1737093  4.0783065
ENSG00000229344  1.7111760  1.3761588
ENSG00000248527  8.3435431  8.6294344
> head(fit2$coefficients)
                 Contrasts
                  group1 - group0
  ENSG00000227232     -0.21907877
  ENSG00000225972     -1.08471239
  ENSG00000225630     -0.24773378
  ENSG00000237973     -0.09540285
  ENSG00000229344     -0.33501722
  ENSG00000248527      0.28589126

> sessionInfo( )
R version 4.1.2 (2021-11-01)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

Matrix products: default
BLAS/LAPACK: /gpfs3/apps/eb/2020b/skylake/software/FlexiBLAS/3.0.4-GCC-11.2.0/lib64/libflexiblas.so.3.0

locale:
[1] C

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

other attached packages:
[1] edgeR_3.34.1 limma_3.48.3

loaded via a namespace (and not attached):
[1] MASS_7.3-54     compiler_4.1.2  Rcpp_1.0.7      grid_4.1.2
[5] locfit_1.5-9.4  statmod_1.4.36  lattice_0.20-45

If you don't wish to define a contrast then you must use

mm <- model.matrix(~group)

without the 0+ term. This is explained in the limma User's Guide Section 9.2.