Alignment-free inference of hierarchical and reticulate phylogenomic relationships

Bernard, Guillaume; Chan, Cheong Xin; Chan, Yao-ban; Chua, Xin-Yi; Cong, Yingnan; Hogan, James M.; Maetschke, Stefan; Ragan, Mark A.

doi:10.1093/bib/bbx067

Cited by 82 publications

(68 citation statements)

References 106 publications

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“…In recent years, a large number of alignment-free approaches to phylogeny reconstruction have been developed and applied, since these methods are much faster than traditional, alignment-based phylogenetic methods, see [51,39,3,25] for recent review papers and [50] for a systematic evaluation of alignment-free software tools. Most alignment-free approaches are based on k-mer statistics [21,44,7,48,17], but there are also approaches based on the length of common substrings [47,8,27,37,32,46], on word or spaced-word matches [38,33,35,34,1,41] or on so-called micro-alignments [49,20,29,28].…”

Section: Introductionmentioning

confidence: 99%

Read-SpaM: assembly-free and alignment-free comparison of bacterial genomes with low sequencing coverage

Lau

Leimeister

Dörrer

et al. 2019

Preprint

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In many fields of biomedical research, it is important to estimate phylogenetic distances between taxa based on low-coverage sequencing reads. Major applications are, for example, phylogeny reconstruction, species identification from small sequencing samples, or bacterial strain typing in medical diagnostics. Herein, we adapt our previously developed software program Filtered Spaced-Word Matches (FSWM) for alignment-free phylogeny reconstruction to work on unassembled reads; we call this implementation Read-SpaM. Test runs on simulated reads from bacterial genomes show that our approach can estimate phylogenetic distances with high accuracy, even for large evolutionary distances and for very low sequencing coverage.

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Section: Introductionmentioning

confidence: 99%

Read-SpaM: assembly-free and alignment-free comparison of bacterial genomes with low sequencing coverage

Lau

Leimeister

Dörrer

et al. 2019

Preprint

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“…Similarly, the length of longest common sub-words can be efficiently found using data structures such as generalized suffix trees or suffix arrays [25]. A review of earlier alignment-free methods is given in [78]; more recent review papers are [27,72,84,5,40]. A first systematic benchmark study of alignment-free methods has been published in 2019, as a collaboration of several groups working in the field [83].…”

Section: Introductionmentioning

confidence: 99%

Sequence Comparison without Alignment: TheSpaMapproaches

Morgenstern

2019

Preprint

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Sequence alignment is at the heart of DNA and protein sequence analysis. For the data volumes that are nowadays produced by massively parallel sequencing technologies, however, pairwise and multiple alignment methods have become too slow for many data-analysis tasks. Therefore, fast alignment-free approaches to sequence comparison have become popular in recent years. Most of these approaches are based on word frequencies, for words of a fixed length, or on word-matching statistics. Other approaches are based on the length of maximal word matches. While these methods are very fast, most of them are based on ad-hoc measures of sequences similarity or dissimilarity that are often hard to interpret. In this review article, I describe a number of alignment-free methods that we developed in recent years. Our approaches are based on spaced word matches ('SpaM'), i.e. on inexact word matches, that are allowed to contain mismatches at certain pre-defined positions. Unlike most previous alignment-free approaches, our approaches are able to accurately estimate phylogenetic distances between DNA or protein sequences based on stochastic models of molecular evolution.

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“…For the huge amounts of sequence data that are now available, however, sequence alignment has become too slow. Therefore, considerable efforts have been made in recent years, to develop fast alignmentfree approaches that can estimate phylogenetic distances without the need to calculate full alignments of the input sequences, see [20,50,57,4,26] for recent review articles. Alignment-free approaches are not only used in phylogeny reconstruction, but are also important in metagenomics [10,39,32] and in medical applications, for example to identify drug-resistant bacteria [5] or to classify viruses [55,2].…”

Section: Introductionmentioning

confidence: 99%

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

Röhling

Dencker

Morgenstern

2019

Preprint

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We study the number N k of length-k word matches between pairs of evolutionarily related DNA sequences, as a function of k. We show that the Jukes-Cantor distance between two genome sequences -i.e. the number of substitutions per site that occurred since they evolved from their last common ancestor -can be estimated from the slope of a function F that depends on N k and that is affine-linear within a certain range of k. Integers k min and k max can be calculated depending on the length of the input sequences, such that the slope of F in the relevant range can be estimated from the values F (k min ) and F (k max ). This approach can be generalized to so-called spaced-word matches, where mismatches are allowed at positions specified by a user-defined binary pattern. Based on these theoretical results, we implemented a 1 software program for alignment-free sequence comparison called Slope-SpaM. Test runs on real and simulated sequence data show that Slope-SpaM can accurately estimate phylogenetic distances for distances up to around 0.5 substitutions per position. The statistical stability of our results is improved if spaced words are used instead of contiguous words. Unlike previous alignment-free methods that are based on the number of (spaced) word matches, Slope-SpaM produces accurate results, even if sequences share only local homologies.

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Alignment-free inference of hierarchical and reticulate phylogenomic relationships

Cited by 82 publications

References 106 publications

Read-SpaM: assembly-free and alignment-free comparison of bacterial genomes with low sequencing coverage

Read-SpaM: assembly-free and alignment-free comparison of bacterial genomes with low sequencing coverage

Sequence Comparison without Alignment: TheSpaMapproaches

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

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