Hi!
I'm a geochemist doing some microbial analyses, so this may be a silly question. I saw a suggestion to use DESeq2 as a means to normalize my 16S rRNA ASV data rather than using rarefaction via sequencing depth or proportion of total sample to avoid Type I/II errors.
I'm using my ASV counts / sample table (Below; "count_tab") and attempting to make it into a DESeq2 object, and then doing varianceStabilizingTransformation on it to pull out a "normalized" table of ASV counts.
deseq_counts <- DESeqDataSetFromMatrix(count_tab, colData = sample_info_tab, design = ~1)
deseq_counts_vst <- varianceStabilizingTransformation(deseq_counts)
vst_trans_count_tab <- assay(deseq_counts_vst)
write.table(vst_trans_count_tab, file="C:/Users/aflob/Desktop/DADA2/FASTQ/transformed_counts.txt", sep="\t"))
But what I get out doesn't seem to make sense to me; it's showing ASV1 as all the same 'normalized' value. I did test this with putting in random values for ASV1, and got the same output; it's "equal" across all samples. Am I misunderstanding something here? Thanks so much in advance!
