Dear Friends,
I ran DADA2 on Iontorrent sequenced single end cDNA data, and below is the denoising result log:
R version 3.5.1 (2018-07-02)
Loading required package: Rcpp
DADA2: 1.10.0 / Rcpp: 1.0.1 / RcppParallel: 4.4.2
- Filtering ..........
- Learning Error Rates
279982055 total bases in 1191413 reads from 3 samples will be used for learning the error rates.- Denoise samples ..........
- Remove chimeras (method = consensus)
- Report read numbers through the pipeline
- Write output
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_single.R /data/data/NPRP-11-data/qiime-results/qiime-tmp/qiime2-archive-k1k9jgmh/6b3f03d0-f354-465d-935e-1bb073c642d9/data /data/data/NPRP-11-data/qiime-results/qiime-tmp/tmp8zc83ut3/output.tsv.biom /data/data/NPRP-11-data/qiime-results/qiime-tmp/tmp8zc83ut3/track.tsv /data/data/NPRP-11-data/qiime-results/qiime-tmp/tmp8zc83ut3 235 0 2.0 2 Inf consensus 1.0 20 1000000 NULL 16
Saved FeatureTable[Frequency] to: Ionexpress_1to11-dada2-rep-seqs-table2.qza
Saved FeatureData[Sequence] to: Ionexpress_1to11_dada2-rep-seqs2.qza
Saved SampleData[DADA2Stats] to: Ionexpress_1to11_dada2-rep-seqs-stats2.qza
As we see the learning error rates used 3 samples out of 10 samples I have, does it matter? Or I can move on with my analysis.
Thanks!