Woltka grants users the flexibility to control the classification criteria, in addition to the flexibility in the classification system itself. This maximizes the potential of exploring microbiome big data in various angles, and enables novel applications.
Woltka features the following modes of classification, as controlled by the --rank (or -r) parameter:
Simply report subject IDs. A classification system is not required in this analysis. This mode has the highest granularity and is useful in e.g. the OGU analysis.
Find the best classification unit in the entire hierarchy in describing the query sequence, without forcing it to a particular rank.
This mode uses a lowest common ancestor (LCA) algorithm designed for a tree structure without fixed ranks to tackle ambiguous assignments. It chooses the lowest unit when possible, and go higher in the hierarchy if necessary.
Choose a classification unit at the given rank to describe the query sequence. This is the closest to the conventional notion of "taxonomic classification".
The rank can be species, genus, family..., or K, M, R, map..., or ATC4, ATC3..., or whatever, as long as the classification hierarchies you supplied have them.
Attempt to classify at the given rank, and when this is not possible, go up in hierarchy until a proper unit is reached. The same LCA algorithm is used in this process.
The difference from free-rank classification (2) is that, it discards all units below the given rank, even if some of them may describe the query sequence.
Multiple ranks can be specified simultaneously, delimited by comma (e.g., --rank none,free,phylum,genus,species), in which case Woltka will generate one profile for each rank. This is significantly faster than running Woltka multiple times on individual ranks.
One can omit the --rank parameter. In such case, Woltka automatically performs free-rank classification (2) (same as --rank free) if there is a classification system, or no classification (1) (same as --rank none) if there isn't.
In many cases a query sequence has matches in multiple reference sequences, and those sequences may have different assignments at the target rank. Woltka deals with this situation using your choice of the following mechanisms.
In the resulting profile, each subject receives 1 / k count, where k is the total number of subjects of the current query. In this way, the total feature frequency per sample is consistent with the number of reads in the input alignment.
For example, sequence A was aligned to five genomes: two under genus Escherichia, one under each of genera Salmonella, Klebsiella, and Enterobacter. In the genus level classification by Woltka, Escherichia receives 2/5 count, and each of the other three receives 1/5 each.
In the read-to-feature maps (--outmap), a multi-assignment is reported as:
A <tab> Escherichia:2 <tab> Salmonella:1 <tab> Klebsiella:1 <tab> Enterobacter:1
It applies to none (1) or given-rank (3) classifications. With this flag, ambiguous assignments will be considered as unassigned.
In the above case, this query sequence won't receive any genus-level assignment due to the ambiguity.
3. Lowest common ancestor (LCA)
This is how free-rank (2) and given-rank-and-above (4) classifications work. No parameter is needed.
In the above case, the query sequence will be assigned to family Enterobacteriaceae, because all four genera belong to this family.
At a given rank (3), as long as the dominant unit reaches the given percentage threshold of all subjects, it will be considered as the right target.
In the above case, at the family level, all four genera (five genomes) belong to Enterobacteriaceae (100%), so there is no doubt that it can be assigned to Enterobacteriaceae. Now we replace one genome with one under genus Pseudomonas (family Pseudomonadaceae). Therefore, the proportion of Enterobacteriaceae becomes 4/5 = 80%.
The query sequence will be assigned to Enterobacteriaceae if you specify --major 80 or above, or unassigned if this parameter is omitted or below 80.
Note: Majority rule overrides the --above flag. Currently, Woltka cannot combine LCA and majority rule due to the rank-free nature of the classification system.
With flag --unassigned, Woltka reports unassigned sequences in the profile and the feature map. They will be marked as "Unassigned".
A sequence is deemed unassigned because of one of the following reasons:
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The subject(s) is not found in the classification system. For flexibility, Woltka does NOT consider this as a conflict between data and database, and it does NOT halt the program and warn the user. Instead, it is treated as unassigned.
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The LCA (see above) of the subjects is the root. A tree-structured classification hierarchy always has a root. No matter how diverse the subjects are, they always coalesce to the root eventually. But reporting "root" as an assignment is meaningless. So it will be considered as unassigned.
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In unique-assignment mode, assignments of subjects are not unique (see above).
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In majority-rule mode, none of the candidate units reaches the threshold (see above).
With the unassigned part reported, the sum of feature counts in each sample of the resulting profile equals to the number of query sequences in the original alignment file. This property is potentially useful in certain downstream analyses.
Even if this function was not used in generating the profile, one can still manually calculate the unassigned part by subtracting the sum of feature counts from the number of sequences.
[Important] The "unassigned" part represents query sequences that were aligned to one or more subjects, but Woltka cannot find a suitable assignment based on those subjects. Therefore, assigned + unassigned is NOT the entire sample, but only the part of sample that are found in the alignment.
In the "coord-match" functional classification (see details), subjects are genes instead of genomes, therefore despite that some query sequences can be aligned to one or more genomes, they can still be excluded from the unassigned part if their coordinates do not match any gene.