Abstract
BackgroundLikelihood-based phylogenetic inference is generally considered to be the most reliable classification method for unknown sequences. However, traditional likelihood-based phylogenetic methods cannot be applied to large volumes of short reads from next-generation sequencing due to computational complexity issues and lack of phylogenetic signal. "Phylogenetic placement," where a reference tree is fixed and the unknown query sequences are placed onto the tree via a reference alignment, is a way to bring the inferential power offered by likelihood-based approaches to large data sets.ResultsThis paper introduces pplacer, a software package for phylogenetic placement and subsequent visualization. The algorithm can place twenty thousand short reads on a reference tree of one thousand taxa per hour per processor, has essentially linear time and memory complexity in the number of reference taxa, and is easy to run in parallel. Pplacer features calculation of the posterior probability of a placement on an edge, which is a statistically rigorous way of quantifying uncertainty on an edge-by-edge basis. It also can inform the user of the positional uncertainty for query sequences by calculating expected distance between placement locations, which is crucial in the estimation of uncertainty with a well-sampled reference tree. The software provides visualizations using branch thickness and color to represent number of placements and their uncertainty. A simulation study using reads generated from 631 COG alignments shows a high level of accuracy for phylogenetic placement over a wide range of alignment diversity, and the power of edge uncertainty estimates to measure placement confidence.ConclusionsPplacer enables efficient phylogenetic placement and subsequent visualization, making likelihood-based phylogenetics methodology practical for large collections of reads; it is freely available as source code, binaries, and a web service.
Highlights
Likelihood-based phylogenetic inference is generally considered to be the most reliable classification method for unknown sequences
Overview of phylogenetic placement using pplacer Pplacer places query sequences in a fixed reference phylogeny according to phylogenetic posterior probability and maximum likelihood criteria
In Bayesian mode, pplacer evaluates the posterior probability of a fragment placement on an edge conditioned on the reference tree topology and branch lengths
Summary
Likelihood-based phylogenetic inference is generally considered to be the most reliable classification method for unknown sequences. High-throughput pyrosequencing technologies have enabled the widespread use of metagenomics and metatranscriptomics in a variety of fields [1]. The most common way of analyzing a metagenomic data set is to use BLAST [9] to assign a taxonomic name to each query sequence based on “reference” data of known origin. This strategy has its problems: when a query sequence is only distantly related to sequences in the database, BLAST can either err substantially by forcing a query into an alignment with a known sequence, or return an uninformatively broad collection of alignments. Similarity statistics such as BLAST E-values can be difficult to interpret because they are dependent on fragment length and database size.
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