"degPatterns" showed 6 clusters, but why no genes in cluster 1-4, but all clustering genes in cluster 5 and 6
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lqsdau ▴ 10
@lqsdau-20427
Last seen 5.7 years ago

Hi, I identified DEGs with LRT test in DESeq2 and clustered them with degPatterns. There were 78 DEGs but 48 genes were clustered by degPatterns. And all 48 DEGs were clustered into cluster 5 and 6. But why there was no gene in cluster 1-4? And the plots only shows cluster 5 and 6. If the 48 genes can only clustered into 2 clusters, why there were total 6 clusters? Thanks

The R script was follow: ddsfullgtt <- DESeqDataSetFromMatrix(countData = countData, colData= coldata, design = ~ ge+ti+tim) ddsLRTtt <- DESeq(ddsfullgtt,test = "LRT", reduced = ~ti + tim) resultsNames(ddsLRTtt) results(ddsLRTtt) resLRTgtt <- results(ddsLRTtt)

# mcols(resLRTgtt, use.names = TRUE) resLRTgtt = resLRTgtt[order(resLRTgtt$pvalue),] head(resLRTgtt) summary(resLRTgtt)

Subset the LRT results to return genes with padj < 0.05

library("tibble") library("dplyr") library("tidyr") library("DEGreport") library("ggplot2") sigresLRT <- resLRTgtt %>% data.frame() %>% rownamestocolumn(var="gene") %>% as_tibble() %>% filter(padj < 0.05)

Get sig gene lists

sigLRTgenes <- sigresLRT %>% pull(gene) length(sigLRTgenes)

Subset results for faster cluster finding (for classroom demo purposes)

clusteringsiggenes <- sigresLRT %>% arrange(padj)

Obtain rlog values for those significant genes

Input is a matrix of log transformed values

rld <- rlog(ddsLRTtt, blind=T) rldmat <- assay(rld) clusterrlog <- rldmat[clusteringsig_genes$gene, ]

Use the degPatterns function from the 'DEGreport' package to show gene clusters across sample groups

coldata$titi <- factor(coldata$titi, levels=unique(coldata$titi)) clusters <- degPatterns(cluster_rlog, metadata = coldata, time = "titi", col="genotype", reduce = TRUE)

Extract the Group 1 genes

cluster_groups <- clusters$df group1 <- clusters$df %>% filter(cluster == 1)

DEGreport deseq2 • 1.9k views
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@lorena-pantano-6001
Last seen 6 months ago
Boston

Hi,

Thanks for the question.

There is a parameter that is minc, by default = 15 that will remove clusters with less than those genes. Can you try to set up that value to 1 or less and see if you get more clusters.

This is an arbitrary value to remove isolated genes and it has to be set up accordingly the user expectation.

I hope this helps.

Cheers

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