Low sequence counts

User Support
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5

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  1. How many starting sequences do you have? When you run dada2, use the --verbose flag so that filtering summaries are reported (then you will know where the sequences are being dropped)

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I am attaching dada2 summaries.
After removing chimeras, merged sequences seem very low but somebody said it's fine. (Qiime dada2 denoise-paired denoise)
Do you think I should rerun dada2?

(qiime2-2018.2) Jeongsus-MacBook-Pro:SM_raw Jeongsu$ qiime dada2 denoise-paired --verbose --i-demultiplexed-seqs demux-paired-end.qza --p-trunc-len-f 220 --p-trunc-len-r 220 --p-trim-left-f 10 --p-trim-left-r 10 --o-representative-sequences rep-seqs-dada2.qza --o-table table-dada2.qza
Running external command line application(s). This may print messages to stdout and/or stderr.
The command(s) being run are below. These commands cannot be manually re-run as they will depend on temporary files that no longer exist.

Command: run_dada_paired.R /var/folders/vh/l4ckn9311hx8yrvvbfpnh6zh0000gn/T/tmp9isl57vm/forward /var/folders/vh/l4ckn9311hx8yrvvbfpnh6zh0000gn/T/tmp9isl57vm/reverse /var/folders/vh/l4ckn9311hx8yrvvbfpnh6zh0000gn/T/tmp9isl57vm/output.tsv.biom /var/folders/vh/l4ckn9311hx8yrvvbfpnh6zh0000gn/T/tmp9isl57vm/filt_f /var/folders/vh/l4ckn9311hx8yrvvbfpnh6zh0000gn/T/tmp9isl57vm/filt_r 220 220 10 10 2.0 2 consensus 1.0 1 1000000

R version 3.4.1 (2017-06-30)
Loading required package: Rcpp
DADA2 R package version: 1.6.0

  1. Filtering ......................................................................

  2. Learning Error Rates
    2a) Forward Reads
    Initializing error rates to maximum possible estimate.
    Sample 1 - 170760 reads in 40057 unique sequences.
    Sample 2 - 72976 reads in 14057 unique sequences.
    Sample 3 - 80375 reads in 17519 unique sequences.
    Sample 4 - 91867 reads in 19942 unique sequences.
    Sample 5 - 36676 reads in 7725 unique sequences.
    Sample 6 - 40860 reads in 6791 unique sequences.
    Sample 7 - 74639 reads in 16195 unique sequences.
    Sample 8 - 51861 reads in 8882 unique sequences.
    Sample 9 - 57126 reads in 12585 unique sequences.
    Sample 10 - 59322 reads in 13621 unique sequences.
    Sample 11 - 59887 reads in 12912 unique sequences.
    Sample 12 - 53675 reads in 15168 unique sequences.
    Sample 13 - 67513 reads in 14291 unique sequences.
    Sample 14 - 46384 reads in 7620 unique sequences.
    Sample 15 - 91381 reads in 15922 unique sequences.
    selfConsist step 2
    selfConsist step 3
    selfConsist step 4
    selfConsist step 5
    selfConsist step 6
    selfConsist step 7
    Convergence after 7 rounds.
    2b) Reverse Reads
    Initializing error rates to maximum possible estimate.
    Sample 1 - 170760 reads in 41084 unique sequences.
    Sample 2 - 72976 reads in 17249 unique sequences.
    Sample 3 - 80375 reads in 20455 unique sequences.
    Sample 4 - 91867 reads in 22107 unique sequences.
    Sample 5 - 36676 reads in 7559 unique sequences.
    Sample 6 - 40860 reads in 7705 unique sequences.
    Sample 7 - 74639 reads in 17660 unique sequences.
    Sample 8 - 51861 reads in 9785 unique sequences.
    Sample 9 - 57126 reads in 12761 unique sequences.
    Sample 10 - 59322 reads in 14496 unique sequences.
    Sample 11 - 59887 reads in 14477 unique sequences.
    Sample 12 - 53675 reads in 14563 unique sequences.
    Sample 13 - 67513 reads in 15693 unique sequences.
    Sample 14 - 46384 reads in 8816 unique sequences.
    Sample 15 - 91381 reads in 17443 unique sequences.
    selfConsist step 2
    selfConsist step 3
    selfConsist step 4
    selfConsist step 5
    selfConsist step 6
    Convergence after 6 rounds.

  3. Denoise remaining samples .......................................................
    The sequences being tabled vary in length.

  4. Remove chimeras (method = consensus)
    input filtered denoised merged non-chimeric
    A1_S68_L001_R1_001.fastq.gz 199077 170760 170760 128 122
    A10_S3_L001_R1_001.fastq.gz 80574 72976 72976 40 40
    A11_S1_L001_R1_001.fastq.gz 92433 80375 80375 42 42
    A12_S72_L001_R1_001.fastq.gz 103531 91867 91867 69 69
    A14_S75_L001_R1_001.fastq.gz 41777 36676 36676 33 33
    A15_S61_L001_R1_001.fastq.gz 46939 40860 40860 49 49

  5. Write output
    Saved FeatureTable[Frequency] to: table-dada2.qza
    Saved FeatureData[Sequence] to: rep-seqs-dada2.qza

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  1. What marker gene/primers are you using? What is the total length of the amplicon? Since you are using paired reads, you want to make especially sure that the trimmed reads still overlap with at least 20 nt, or you will lose reads that fail to join.

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I am working with demuliplexed paired-end fastq files. So I don't think there's overlapped reads between two paried seqs. Is this right? If so, can this be a matter for that I lose too many sequences while running dada2?

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  1. What does the quality of the demultiplexed sequences look like? Please share your demux quality QZV if you want us to take a look.

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Here's the demux.qzv file.
demux.qzv (289.5 KB)