OTU clustering parameters

After having selected the sequences you would like to cluster, the wizard offers to set some general parameters (see figure 5.2).

Image otuclusteringsettings
Figure 5.2: Settings for the OTU clustering tool.

You can choose to perform a De novo OTU clustering, or you can perform a Reference based OTU clustering.

The following parameters can then be set:

Chimera detection is performed as follows: The read being processed is split into fragments. Each fragment is then queried for matches against the database with a k-mer search. Database references that match at least one query fragment are then selected and the read is then aligned to each selected references while allowing "cross overs". Chimera detection is performed in order to identify any chimeric sequences, i.e., amplicons formed by joining two sequences during PCR. These are artifacts that will be excluded from the regular OTU clustering, and presented in a different abundance table labeled as being chimera-specific.

In order to use the highest quality sequences for clustering, it is recommended to merge paired read data. If the read length is smaller than the amplicon size, forward and reverse reads are expected to overlap in most of their 3' regions. Therefore, one can merge the forward and reverse reads to yield one high quality representative according to some pre-selected merge parameters: the overlap region and the quality of the sequences. For example, for a designed 150 bp overlap, a maximum score of 150 is achievable, but as the real length of the overlap is unknown, a lower minimum score should be chosen. Also, some mismatches and indels should be allowed, especially if the sequence quality is not perfect. You can also set penalties for mismatch, gap and unaligned ends.

In the Merge Overlapping Pairs dialog, you can set the parameters as seen in figure 5.3.

Image mergepairedreads
Figure 5.3: Alignment parameters.

In order to understand how these parameters should be set, an explanation of the merging algorithm is needed: Because the fragment size is not an exact number of base pairs and is different from fragment to fragment, an alignment of the two reads has to be performed. If the alignment is good and long enough, the reads will be merged. Good enough in this context means that the alignment has to satisfy some user-specified score criteria (details below). Because of sequencing errors that typically are more abundant towards the end of the read, the alignment is not expected always to be perfect, and the user can decide how many errors are acceptable. Long enough in this context means that the overlap between the reads has to be non-coincidental. Merging two reads that do not really overlap leads to errors in the downstream analysis, thus it is very important to make sure that the overlap is big enough. If only a few bases overlap was required, some read pairs will match by chance, so this has to be avoided.

The following parameters are used to define what is good enough and long enough.

The tool accepts both paired and unpaired reads but will only merge paired reads in forward-reverse orientation. After merging, the merged reads will always be in the forward orientation.

The option "Include all reads" is left unchecked by default. Selecting this option will include the non-merged reads in the OTU clustering analysis. Doing so may increase greatly the running time of the analysis. However, people working with data expected to have non-overlapping paired reads (for example fungal ITS data) should check this option to include all reads in the analysis.