Fast and accurate phylogeny reconstruction using filtered spaced-word matches

Abstract

MotivationWord-based or ‘alignment-free’ algorithms are increasingly used for phylogeny reconstruction and genome comparison, since they are much faster than traditional approaches that are based on full sequence alignments. Existing alignment-free programs, however, are less accurate than alignment-based methods.ResultsWe propose Filtered Spaced Word Matches (FSWM), a fast alignment-free approach to estimate phylogenetic distances between large genomic sequences. For a pre-defined binary pattern of match and don’t-care positions, FSWM rapidly identifies spaced word-matches between input sequences, i.e. gap-free local alignments with matching nucleotides at the match positions and with mismatches allowed at the don’t-care positions. We then estimate the number of nucleotide substitutions per site by considering the nucleotides aligned at the don’t-care positions of the identified spaced-word matches. To reduce the noise from spurious random matches, we use a filtering procedure where we discard all spaced-word matches for which the overall similarity between the aligned segments is below a threshold. We show that our approach can accurately estimate substitution frequencies even for distantly related sequences that cannot be analyzed with existing alignment-free methods; phylogenetic trees constructed with FSWM distances are of high quality. A program run on a pair of eukaryotic genomes of a few hundred Mb each takes a few minutes.Availability and ImplementationThe program source code for FSWM including a documentation, as well as the software that we used to generate artificial genome sequences are freely available at http://fswm.gobics.de/Supplementary information Supplementary data are available at Bioinformatics online.

The number of spaced-word matches between twoDNAsequences as a function of the underlying pattern weight

“…Most of these approaches calculate heuristic measures of sequence (dis-)similarity that are difficult to interpret. At the same time, alignment-free methods have been proposed that can accurately estimate phylogenetic distances between sequences based on stochastic models of DNA or protein evolution, using the length of common substrings [22,35] or so-called micro alignments [54,21,30,29,12].…”

Scalable alignment-free approaches in microbial phylogenomics

“…Finally, the spaced-word frequencies method uses sets of match and mismatch position patterns to compare the spaced-word frequencies between two sequences. The patterns can vary in length and number 55,56 .…”

“…the SHortest Unique subSTRING, shustring 60 . Finally, the k-mismatch average common substring method is a variant of the acs method, using the longest common substring with k-mismatches 56,61 .…”

“…to maximise the area under the ROC curve or ensure a minimum desired frequency of true positives. Measures that capture these trends behave as pairwise similarities, and like their classical MSA-based counterparts can be used in distance analysis to generate a tree [50][51][52][53][54][55][56][57][58] . arranged into a (very local) "alignment" matrix and used as input into likelihood, Bayesian or other (non-distance) algorithms for tree inference, although at the cost of the speed and scalability we hoped to secure by taking an AF approach in the first place.…”

“…Tom Macke wrote a program "sig" that could map the distribution of oligonucleotides, including degenerate ones, across a set of catalogs 36,56,57 . Similar programs are mentioned by Sobieski et al 41 In those years, hardware and operating systems were far less standardized than today, and it was not straightforward to exchange programs, much less to offer remote access.…”