Hi,
could you please suggest me why I am getting error with apeglm shrinkage in the code while the same code is working with normal shrinkage.
resultsNames(dds)
[1] "Intercept" "group_Aman.Leaf.T2_vs_Aman.Leaf.T1"
[3] "group_Aman.Leaf.T3_vs_Aman.Leaf.T1" "group_Aman.Root.T1_vs_Aman.Leaf.T1"
[5] "group_Aman.Root.T2_vs_Aman.Leaf.T1" "group_Aman.Root.T3_vs_Aman.Leaf.T1"
[7] "group_Boro.Leaf.T1_vs_Aman.Leaf.T1" "group_Boro.Leaf.T2_vs_Aman.Leaf.T1"
[9] "group_Boro.Leaf.T3_vs_Aman.Leaf.T1" "group_Boro.Root.T1_vs_Aman.Leaf.T1"
[11] "group_Boro.Root.T2_vs_Aman.Leaf.T1" "group_Boro.Root.T3_vs_Aman.Leaf.T1"
resAmanRootT1vsAmanRootT2<-lfcShrink(dds,contrast=c("group","Aman.Root.T1","Aman.Root.T2"),type="normal") using 'normal' for LFC shrinkage, the Normal prior from Love et al (2014).
Note that type='apeglm' and type='ashr' have shown to have less bias than type='normal'. See ?lfcShrink for more details on shrinkage type, and the DESeq2 vignette. Reference: https://doi.org/10.1093/bioinformatics/bty895
summary(resAmanRootT1vsAmanRootT2)
out of 29097 with nonzero total read count adjusted p-value < 0.1 LFC
> 0 (up) : 10, 0.034% LFC < 0 (down) : 8, 0.027% outliers [1] : 19, 0.065% low counts [2] : 0, 0% (mean count < 0) [1] see 'cooksCutoff' argument of ?results [2] see 'independentFiltering' argument of ?results
resAmanRootT1vsAmanRootT2<-lfcShrink(dds,contrast=c("group","Aman.Root.T1","Aman.Root.T2"),type="apeglm")
Error in lfcShrink(dds, contrast = c("group", "Aman.Root.T1", "Aman.Root.T2"), :
type='apeglm' shrinkage only for use with 'coef'
Thanks in advance for your time and help. nabiyogesh