Phylogeny reconstruction based on the length distribution of k-mismatch common substrings

Morgenstern, Burkhard; Schöbel, Svenja; Leimeister, Chris-André

doi:10.1186/s13015-017-0118-8

Cited by 18 publications

(14 citation statements)

References 35 publications

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“…A number of alignment-free methods have been proposed in recent years that estimate the nucleotide match probability p in an (unknown) alignment of two DNA sequences from the number N k of word or k-mer matches for a fixed word length k. This can be done by comparing N k to the total number of words in the compared sequences [39] or -equivalently -to the length of the sequences [35]. A certain draw-back of these approaches is that they assume that the compared sequences are homologous to each other over their entire length.…”

Section: Availability and Future Directionsmentioning

confidence: 99%

“…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].…”

Section: Introductionmentioning

confidence: 99%

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

Röhling

Dencker

Morgenstern

2019

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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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Section: Availability and Future Directionsmentioning

confidence: 99%

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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“…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]. As has been mentioned by various authors, an additional advantage of many alignment-free methods is that they can be applied not only to complete genome sequences, but also to unassembled reads.…”

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

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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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“…To this end, the program used the average length of common substrings between the compared sequences. Later, we proposed an approach to estimate phylogenetic distances based on the length distribution of k-mismatch common substrings [53].…”

Section: Introductionmentioning

confidence: 99%

Sequence Comparison without Alignment: TheSpaMapproaches

Morgenstern

2019

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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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Phylogeny reconstruction based on the length distribution of k-mismatch common substrings

Cited by 18 publications

References 35 publications

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

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

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

Sequence Comparison without Alignment: TheSpaMapproaches

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