Puzzles on merging feature-table/seq

[colinbrislawn (Colin J Brislawn)]

Hello @chunri2012,

Welcome to the forums!

Thank you for your detailed description of your pipeline, and the problem you are experiencing when merging ASV tables.

As you have discovered, amplicons from different regions make different ASVs which are not able to merge.

@chunri2012

The feature-table merging was not able to really merge ASVs from the same specie/organism, and may even bring spurious alpha diversity and fake beta diversity on ASVs level, regardless of effects of different primer-sets, sampling methods, library construction, sequencing method/depth & etc.

This is one of the limits of amplicons and ASV. This best-of-the-forums post discusses the challenges of working with different regions. It's a very hard problem with no easy solution.

Even changing the length of amplicon from the same region will create different ASVs!

@chunri2012

but denoising with different deblur parameters, such as one table with --p-trim-length 130 and --p-left-trim-len 0 and the other one with --p-trim-length 120 and --p-left-trim-len 10, will give me the really merged ASVs

Just like you said, reducing the length of your reads will lead to shorter ASVs, which will make their IDs now longer match and make merging feature tables impossible.

@chunri2012

declares that "denoise-single are directly comparable (in this case, the feature id is the md5 hash of the sequence defining the feature).

This means that a specific sequence will always have the same ID:

>c9ff71d91da6c66889497ebbdc743570
AGCGTTATCCGGATTT

but if you trim the sequence shorter, then the ID will change:

>f014496db04789259900e0bef778e0c4
AGCGTTATCCGGAT

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While this is an unsolved problem, there are some ways forward. I like your suggestion here:

@chunri2012

Or I just can go further with table on a taxonomic level (a merged feature-table collapsed on species level under the same silva database assignment).

While the ASV IDs will be different, hopefully the taxonomic classification will be similar and allow for features to be merged! You should totally try this!

If you included any positive controls, you could also choose the region (V4, V3-V4, V4, V4-V5) that does the best job capturing the expected composition of these samples. Did you include any positive controls?

Let us know what you try next!