Hello

I am performing differential gene expression using DESeq2 package. The volcano plot showed unequal distribution between upregulated and downregulated genes. The script used for the analysis is as follows

library(DESeq2)

library(tibble)

#Phenodata

Phenodata<- read.csv(" ") # 25 cases and 22 controls

#Reading the raw count matrix

Data<- read.delim(".txt", check.names = F, sep = "")

dds <- DESeqDataSetFromMatrix(Data,
                              Phenodata,
                              design = ~ Diagnosis)

# Create DESeq

dds2 <- DESeq(dds)

#filtering the genes

smallestGroupSize <- 22

keep <- rowSums(counts(dds2) >= 30) >= smallestGroupSize

dds2<- dds2[keep,]

vsd <- vst(dds2, blind=TRUE)

mat <- assay(vsd)

plotPCA(vsd, intgroup=c("Diagnosis"))

# Differential expression analysis

resultsNames(dds2)

res_group_CTR_vs_case <- results(object = dds2, name="Diagnosis_case_vs_CNT", alpha = 0.05)

# Summary of DE analysis

summary(res_group_CTR_vs_case)

# MA plot

DESeq2::plotMA(res_group_CTR_vs_case)

# Volcano plot

library(EnhancedVolcano)

EnhancedVolcano(res_group_CTR_vs_case,
                lab = NA,
                x = 'log2FoldChange',
                y = 'pvalue',
                pCutoff = 0.05,
                FCcutoff = 1.0)  +  ggplot2::coord_cartesian(ylim=c(0, 10))

The MA plot and Volcano plot obtained are as follows:

I want to know whether the volcano plot is correct or if there are any preprocessing issues with the analysis. Also, could you suggest ways to improve the distribution in the volcano plot by changing any step in the analysis?

Thank you