Dear all,
i’ve performed a sequencing of V3-V4 region using a v2 kit Illumina 150x2 (paired-end) which the original amplicon size is around 630 bp. Theoretically, I could not make contigs with overlapping region, right? since the size of reads is much smaller than the original amplicon.
How can I proceed here in Mothur after applying “make.file” indicating R1 and R2 from each sample?
Initially, I’ve performed the make.contigs which resulted the following output:
I’d suggest only using the first read and running it through the phylotype-based pipeline. With no overlap between the reads, things like alignment won’t make sense. Can you regenerate the data using the V4 region with 2x250 nt reads?
Hi Pat,
thank you for your reply.
Where can I find this phylotype-based pipeline to have a look?
Unfortunately, due a budget lacking we can not obtain new data for v4 region using other sequencing kit. Because of this I’m quite worried for using this data. That is the only information we have.
Thanks once again
In the MiSeq SOP I could find the following sentence ## Phylotype-based analysis Phylotype-based analysis is the same as OTU-based analysis, but at a different taxonomic scale. We will leave you on your own to replicate the OTU-based analyses described above with the phylotype data
So it seems we could use the same steps as described previously for OTU analysis but at a different taxonomic scale. Sorry my lack of knowledge, but how to solve it? Then I can’t perform the overlapping of reads using “make.contigs” and follow with R1 reads to “screen.seqs” removing homopolymers, ambiguous reads, etc?
I’d suggest taking R1 and doing something like using screen.seqs/chop.seqs to trim the sequences to a common length (perhaps 200 nt) in place of make.contigs and then running them through the rest of the pipeline.
in this case, considering only R1 from a 2x150 pb sequencing of V3-V4 region, would you recommend classify.seqs by using OTU (97%) or ASV, and why?
thank you so much
I would recommend classifying your sequences using classify.seqs and then pooling things with the same family or genus. The data will be too low quality to trust them as 97% OTUs or ASVs.
Hey Pat,
thanks for that.
then, I will use only the file “wang.tax.summary” as output of classify.seqs, and not proceeding to the next steps from SOP? The different samples will get different sequences number. Can I make subsample of them for comparisons?