Remove duplicate genera in DEseq output?
Entering edit mode
Bretta • 0
Last seen 4 months ago

Hi all,

I successfully ran DESeq2, though I am looking for differential abundance of microbial genera, not gene expression. However, duplicate genera (assigned to different species in my taxa table) are listed out and numbered instead of collapsing. I would like to collapse duplicate genera.

enter image description here

Here is what I ran to generate my figure:

```deg_plus1 <- transform_sample_counts(ds2, function(x) x+1) deg_deseq <- phyloseq_to_deseq2(deg_plus1, ~Sample.Type) DESEQ_deg <- DESeq(deg_deseq) res <- results(DESEQ_deg, tidy=TRUE)

To get table of results

sigASVs <- res %>% filter(padj<0.001 & abs(log2FoldChange)>2) %>% dplyr::rename(ASV=row) View(sigASVs)

Get only asv names

sigASVs_vec <- sigASVs %>% pull(ASV)

Prune phyloseq file

deg_DESeq <- prune_taxa(sigASVs_vec,deg_simple) sigASVs <- tax_table(deg_DESeq) %>% %>% rownames_to_column(var="ASV") %>% right_join(sigASVs) %>% arrange(log2FoldChange) %>% mutate(Genus = make.unique(Genus)) %>% mutate(Genus = factor(Genus, levels=unique(Genus))) ggplot(sigASVs) + geom_bar(aes(x=Genus, y=log2FoldChange), stat="identity",fill=ifelse(sigASVs$log2FoldChange>0,"red","blue"))+ geom_errorbar(aes(x=Genus, ymin=log2FoldChange-lfcSE, ymax=log2FoldChange+lfcSE)) + theme(axis.text.x = element_text(angle=90, hjust=1, vjust=0.5)) ```

Many thanks!

DESeq2 • 311 views
Entering edit mode

How is your data before calculating the deg_DESeq? I see you use phyloseq_to_deseq2 which should work well, but have you double checked that each taxa is correctly summarized? Also note that DESeq2 is meant for low number of samples and raw counts and does many assumptions on the model used. It might be better to use a more general approach to calculate DEG.

Entering edit mode
ATpoint ★ 3.4k
Last seen 1 day ago

This seems to be very specific rather than a general and technical DESeq2 question. See the last point of Can VST-transformed community composition data be expressed as relative abundance? where the DESeq1 author suggests alternative frameworks for microbiome data. I do not think that you will get specific DESeq2+microbiome help here.


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