batch correction in DESeq2
Hi!
I have performed DESeq2 using below colData:
sample treatment
M24_virus_rep1 treated
M24_virus_rep2 treated
M24_virus_rep3 treated
M0_controlrep1 control
M0_controlrep2 control
M0_controlrep3 control
with code:
colData <- read.delim("colData.csv", header= TRUE,sep = ",")
aqp_counts<- counts[aqps, ]
aqp_dds <- DESeqDataSetFromMatrix(countData = aqp_counts, colData = colData, design = ~ treatment)
aqp_dds <- DESeq(aqp_dds)
aqp_res <- results(aqp_dds)
aqp_res_ordered <- aqp_res[order(aqp_res$padj),]
aqp_de_genes <- rownames(aqp_res_ordered)[which(aqp_res_ordered$padj <= 0.01 & abs(aqp_res_ordered$log2FoldChange) >= 1)]
aqp_vsd <- varianceStabilizingTransformation(aqp_dds, blind=T)
pca <- plotPCA(aqp_vsd, intgroup = "treatment")
pca
But my PCA plot is not cluster separately according to biological differences of interest. Instead some of the control samples got mixed with treated samples. So, before going downstream analysis, I'm thinking about doing batch correction. Can someone help with it please
1 answer
Log in to answer this question.
More posts like this
-
PCA Plotting Differences Before and After Batch Correction in RNA-seq for Meta-Analysis
written by Nelo •
-
Batch Effect Correction in RNA-seq Data Using SVA and DESeq2
written by Nelo •
-
To identify Differentially Expressed Genes and Unraveling Upregulated and Downregulated Genes using…
written by Nelo •
-
Losing a lot of significant genes after removing outliers. Having cell type composition as covariat…
written by Sara •
-
boxplot issue
written by kalyani •
-
Help me do a gene enrichment analysis
written by anasjamshed
-
Design in DESeq2: measruing effects of treatment while adjusting for sample type
written by Ridha •
Please read the vignette which covers this. If you have questions then show plot and what you've tried. Right now "help me please" is open-ended and cannot be answered.
this is the plot here
this plot does not match the metadata from above, having 3 treated vs 3 untreated, here you have 6 treated vs 2 untreated
metadata I provided above was intentionally changed to post here, but later you asked for plot as well. So give you the plot as such. The original colData is as follow: