DESeq analysis with Biological replicate.
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@Javad_Sadeghi-24656
Last seen 7 months ago

Hello all,

I got my sequence reads table with FeautureCount and now I am doing my gene expression analysis. I have 18 samples with three groups (one groups received probiotics, one group received antibiotics, and one group as a control, and each have 3 samples, then I replicate this explements). But one of the samples was not good so I end up with 6 samples for controls, 5 samples for Antibiotics, and 6 samples for probiotic groups. These samples are fish samples and all my samples are coming from one family. So basically, all 6 samples for each tank are biological replicate except they are from different tanks (tanks 1 three samples, tanks 2 three samples). First I do not know how to combine my biological replicates. Secondly when I did my sequence analysis, I got only few genes as significant, but because I tested many genes (50/000) genes, I think after correcting for P value, I am getting type two error (falsely rejecting because testing many times). Any help or suggestion? I also attached my meta data and below are my commands. please let me know if my design does not make sense to you.

library(DESeq2)
cts<-read.table("counts1.txt",header=T) 

library(ape)

coldata<-read.table("metadata1.txt",header=T)



dds <- DESeqDataSetFromMatrix(countData = cts,
                              colData = coldata,
                              design <- ~ Treatments)


dds <- DESeq(dds)


resultsNames(dds)
![enter image description here][1]


Treatments_C_vs_Anti <- results(dds, contrast=c("Treatments","![enter image description here][1]C","Anti"))

Treatments_C_vs_Pro <- results(dds, contrast=c("Treatments","C","Pro"))

Treatments_Pro_vs_Anti <- results(dds, contrast=c("Treatments","Anti","Pro"))




resOrderedTreatments_C_vs_Anti <- Treatments_C_vs_Anti[order(Treatments_C_vs_Anti$pvalue),]

resOrderedTreatments_C_vs_Pro <- Treatments_C_vs_Pro[order(Treatments_C_vs_Pro$pvalue),]

resOrderedTreatments_Pro_vs_Anti <- Treatments_Pro_vs_Anti[order(Treatments_Pro_vs_Anti$pvalue),]






write.csv(as.data.frame(resOrderedTreatments_C_vs_Anti), 
          file="resOrderedTreatments_C_vs_Anti.csv")






Here is also how my meta data looks like:

sample_Id   Treatments  TreatmentswithBiologicalreplicate   Tank
J12A.sam    C   C   1
J12B.sam    C   C   1
J12C.sam    C   C   1
J35A.sam    C   C_R 2
J35B.sam    C   C_R 2
J35C.sam    C   C_R 2
J67A.sam    Anti    Anti    1
J67B.sam    Anti    Anti    1
J67C.sam    Anti    Anti    1
J91A.sam    Anti    Anti_R  2
J91B.sam    Anti    Anti_R  2
J115A.sam   Pro Pro 1
J115B.sam   Pro Pro 1
J115C.sam   Pro Pro 1
J139A.sam   Pro Pro_R   2
J139B.sam   Pro Pro_R   2
J139C.sam   Pro Pro_R   2




sessionInfo( )
DESeq2 ExpressionData GeneExpression • 272 views
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@mikelove
Last seen 2 days ago
United States

Unfortunately, my time on the support site has to be limited to specific software questions, and I don't have time to review e.g. analysis plans, or look over people's code.

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Hi Michael, Thank you very much for your response, the question is how we deal with Biological replicate?

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This is not a properly formed question for the support site. Please read over the vignette and workflow, all of the examples of DESeq2 usage in all the documentation involves the use of biological replicates.

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