``` r
# Filtering: keep genes that have at least 10 counts across 1/3 of the samples - https://support.bioconductor.org/p/110307/
keep <- rowSums(DESeq2::counts(dds_L.9.5) >= 10) >= ncol(countsub_L.9.5)/3
dds_L.9.5<- dds_L.9.5[keep,]

# Generate Contrasts
contrast_list_L.9.5        <- c("temp_treatment", "5", "9") # order is important: factor, treatment group, control
res_table_L.9.5_noshrink <- results(dds_L.9.5, contrast=contrast_list_L.9.5, alpha = 0.05)

res_table_L.9.5_norm     <- lfcShrink(dds_L.9.5,
                                       coef=2,
                                       type="normal") # lfcThreshold = 0.585)  # a lfc threshold of 1 = 2-fold change, 0.585 = 1.5-fold change
res_table_L.9.5_apeglm   <- lfcShrink(dds_L.9.5,
                                       coef=2, 
                                       type="apeglm") # lfcThreshold = 0.585)  # a lfc threshold of 1 = 2-fold change, 0.585 = 1.5-fold change
res_table_L.9.5_ashr     <- lfcShrink(dds_L.9.5,
                                       coef=2, 
                                       type="ashr")
```