Read preparation
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11-Aug-2018 New paper describes octave plots for visualizing alpha diversity.

12-Jun-2018 New paper shows that one in five taxonomy annotations in SILVA and Greengenes are wrong.

18-Apr-2018 New paper shows that taxonomy prediction accuracy is <50% for V4 sequences.

05-Oct-2017 PeerJ paper shows low accuracy of closed- and open-ref. QIIME OTUs.

22-Sep-2017 New paper shows 97% threshold is wrong, OTUs should be 99% full-length 16S, 100% for V4.

24-Nov-2016
UPARSE tutorial video posted on YouTube. Make OTUs from MiSeq reads.

 

USEARCH v11

Read preparation

See also
 
OTU / denoising pipeline

The table below summarizes the read preparation steps that I recommend for an OTU / denoising pipeline. Follow the links for details.

Step   Description
Understand your reads   Investigate your data, don't just copy and follow an example script!
Demultiplex   Assign reads to samples using index reads or barcodes
Merge pairs   Merge paired reads to get consensus sequences and Q scores
Strip primers   Primer-binding sequence should be removed before quality filtering
Orient   If you have reads on both strands, orient before trimming and finding uniques
Strip machine sequences   Remove machine-specific sequences e.g. TCAG for 454
Length trimming   Remove low-quality tails, make sure 3' ends align
Quality filtering   Making OTUs (but not the OTU table) needs high-quality reads
Pool samples   Reads for all samples should be combined
Dereplication   Identify unique sequences and abundances
Discard singletons   Remove low-abundance reads, which often have errors