**10**wrote:

Hi all, I am doing Differential Gene Expression Analysis using DESeq2. I have 8 samples in total (4 treated and 4 untreated) with 3 replicates of each. I am using the the code given below:

```
library(DESeq2)
dds <- DESeqDataSetFromMatrix(countData=countdata, colData=coldata, design=~genotype*treatment)
```

For extracting the results I tried 2 codes: Method A:

```
GO1 <- results(dds, name=c("genotype_B_vs_Col.0"), alpha=0.05, lfcThreshold=2)
GO1 = subset(GO1, padj<0.05)
summary(GO1)
out of 3 with nonzero total read count
adjusted p-value < 0.05
LFC > 2.00 (up) : 3, 100%
LFC < -2.00 (down) : 0, 0%
```

Method B:

```
GO <- results(dds, name=c("genotype_B_vs_Col.0"), alpha=0.05)
GO <- subset(GO, log2FoldChange >1 | log2FoldChange <1)
GO = subset(GO, padj<0.05)
summary(GO)
out of 2287 with nonzero total read count
adjusted p-value < 0.05
LFC > 0 (up) : 1156, 51%
LFC < 0 (down) : 1131, 49%
```

I am sorry this kind of question has been explained here many times but I am still confused. Question1: Which method is correct using lfcThreshold filtering (A) or only alpha value(B) and if its A what should be the lfcThreshold value to be used? Question2: Why there is difference in these 2 results? (log2FC 1 = FC 2 as I understand)

Could anyone help me in this please. Thank you

**5.0k**• written 12 months ago by umeshtanwar2 •

**10**