OTU clustering
The OTU clustering tool clusters a collection of reads to operational taxonomic units.
To run the tool, go to
Metagenomics (
) | Amplicon-Based Analysis (
) | OTU clustering (
).
The tool aligns the reads to reference OTU sequences (e.g. the reference database) to create an "alignment score" for each OTU. If the input sequence is shorter, the unaligned ends of the reference are ignored. For example, if a shorter sequence has 100% identity to a fragment of a longer reference sequence, the tool will assign 100% identity and assign the read to the OTU. In the opposite case (longer read mapping to short database reference), the unaligned ends will count as indels, and the percentage identity will be lower.
When the input consists of paired reads, the OTU clustering tool will initially group them into pairs, and align both reads of a pair to the same OTUs. Both reads of a pair will be assigned to the one OTU where they BOTH align with the highest identity possible. Finally, the tool merges both reads of the pair using a stretch of N to the fragments so that the paired read looks as much as possible like the OTU they have been assigned to. For example, the forward-reverse pair (ACGACGACG, GTAGTAGTA) will be turned into ACGACGACGnnnnnnnnnnnnnnnnnnnnTACTACTAC. Reads that cannot be merged will be independently aligned to reference OTUs.
If a read cannot be put into an already existing OTU (because there is no single OTU that is similar enough, i.e., within 97% similarity), the algorithm tries to optimize the alignment score by allowing to "crossover" from one database reference to another at a cost (the chimera crossover cost). To speed up the chimera crossover detection algorithm, the read is not aligned to all OTUs but only to some "promising candidates" found via a k-mer search. If the best match that can be constructed has at least one crossover and the "constructed alignment" is at least as good as the "similarity percentage", then the read is being considered chimeric.
By default, the similarity percentage parameter is set to 97% in the OTU Clustering tool. Therefore without the chimera crossover cost, the constructed alignments difference score can only be 3% at most. The smaller the chimeric cost, the more likely it is that a read is deemed chimeric; setting it too high decreases the chimeric detection.
The OTU clustering tool produces several outputs:
- a sequence list of the OTU centroids
- abundance tables with the newly created OTUs and the chimeras. Each table gives abundance of the OTU or chimeras at each site, as well as the total abundance for all samples.
- a report that summarizes the results of the OTU clustering
- if the input data is paired-end, a report about the merging of overlapping reads
Subsections
- OTU clustering parameters
- OTU clustering tool outputs
- Visualization of OTU abundance tables
- Create taxonomic level subtables for heat maps
- Importing and exporting OTU abundance tables