Joined Reads Accuracy with q2-vsearch Plugin

Hi pals,
I already joined reads after demultiplexing step. I am NOT sure what saying the visualization photo! How possible to realize they are correctly joined or not OR how to interpret it?

For more information I put the multiplexed visualization too.

*demultiplexed and joined visualization photos do not match as well as their number of sequences. Is it normal?
Thanks!

Hi @Mehrdad,
These are histograms showing the distribution of sequence counts per sample. Note where the mode is on these plots… looks like you lose a massive number of sequences after joining. Not a good thing! You can try adjusting joining parameters, but more likely your reads are not quite long enough to join. If I recall correctly, you had this same issue with dada2 so it is probably an issue with the length of your reads, not joining parameters. Just use the forward reads and proceed as if you have single-end read data only.

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Thanks! My data is paired end reads, not single end! I used paired end with forward demultiplexing method. I did not use dada1 method I will. But I do not know it would work or not.

I am aware. I am suggesting that you use only the forward reads.

I inserted my reverse sequences in the following the forward barcode sequences. Would it be the case?

@Mehrdad,
I have no clue what you mean. Joining your forward barcode to reverse reads would not make any sense, since those would not overlap.

If your sequences are not overlapping with vsearch, the read pairs are not long enough to join. The solution is as I have already described:

To be clear, I use paired-end method or signal-read method? As you know, there are two methods

https://docs.qiime2.org/2019.1/plugins/available/cutadapt/

You told me I use signal end method but I want to know will not get I error during joining the reads step? cus Qiime2 is sensitive to every manipulation as I realized. In one word, If I try it will not get I error and if I get visualized it the result would be accurate after joining reads?
Thanks

In this part of the test I copied from the tutorial said paired end should be joined so after demultiplexing we have to join them. The step is not out of the the tutorial.

https://docs.qiime2.org/2019.1/tutorials/overview/#demultiplexing

Paired-end reads need to be joined at some point in the analysis. If you followed the Atacama soils tutorial, you will see that this happens automatically during denoising with q2-dada2 . However, if you want to use q2-debur or an OTU clustering method (as described in more detail below), use q2-vsearch to join these reads before proceeding, as shown in the demultiplexing workflow. To learn more about read joining, see the read joining tutorial.:dancing_women:

I want to be sure, does it need to join my reads after demultiplexing/ the visualization of demultiplexing?

Again I used “https://docs.qiime2.org/2019.1/plugins/available/cutadapt/demux-paired/”! I is cutadapt plugin for demultiplexing. I want to know is it necessary to join my reads or it is only for Atacama format?

it is quite important to know!

I have a question in this case. Does dada2 simultaneously trim and join the reads? Or it is only used for trimming? the text was vague to me in the tutorial. It does not state explicitly that!

It depends on what you want to do. As @Nicholas_Bokulich has pointed out several times above though, it might not be possible to join these reads, which is why he has suggested you proceed with only your forward reads.

From the q2-dada2 help text:

  --o-representative-sequences ARTIFACT PATH FeatureData[Sequence]
                                  The resulting feature sequences. Each
                                  feature in the feature table will be
                                  represented by exactly one sequence, and
                                  these sequences will be the joined paired-
                                  end sequences.  [required if not passing
                                  --output-dir]

"these sequences will be the joined paired-end sequences"

I highly recommend you read the DADA2 docs for more details.

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