Sequence Comparison Without Alignment: The SpaM Approaches

Morgenstern, Burkhard

doi:10.1007/978-1-0716-1036-7_8

Cited by 11 publications

(9 citation statements)

References 71 publications

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“…Furthermore, for a substitution matrix assigning a score to any two symbols of the nucleotide alphabet

, we define the score of a spaced-word match as the sum of all substitution scores of nucleotide pairs aligned to each other at the don’t care positions of P . Spaced-word matches—called spaced seeds in this context—have been originally introduced in sequence-database searching ( Li et al , 2003 ; Ma et al , 2002 ); later they were applied in sequence classification ( Břinda et al , 2015 ) and alignment-free sequence comparison to estimate phylogenetic distances between DNA and protein sequences ( Leimeister et al , 2017 , 2019 ; Morgenstern et al , 2015 ; Röhling et al , 2020 ), see Morgenstern (2020) for a review. The results of these methods depend on the underlying binary pattern or set of patterns.…”

Section: Methodsmentioning

confidence: 99%

App-SpaM: phylogenetic placement of short reads without sequence alignment

Blanke

Morgenstern

2021

Bioinformatics Advances

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Motivation Phylogenetic placement is the task of placing a query sequence of unknown taxonomic origin into a given phylogenetic tree of a set of reference sequences. A major field of application of such methods is, for example, the taxonomic identification of reads in metabarcoding or metagenomic studies. Several approaches to phylogenetic placement have been proposed in recent years. The most accurate of them require a multiple sequence alignment of the references as input. However, calculating multiple alignments is not only time consuming, but also limits the applicability of these approaches. Results Herein, we propose App-SpaM, an efficient algorithm for phylogenetic placement of short sequencing reads on a tree of a set of reference sequences. App-SpaM produces results of high quality that are on a par with the best available approaches to phylogenetic placement, while our software is two orders of magnitude faster than these existing methods. Our approach neither requires a multiple alignment of the reference sequences, nor alignments of the queries to the references. This enables App-SpaM to perform phylogenetic placement on a broad variety of data sets. Availability The source code of App-SpaM is freely available on Github at https://github.com/matthiasblanke/App-SpaM together with detailed instructions for installation and settings. App-SpaM is furthermore available as a Conda-package on the Bioconda channel. Supplementary information Supplementary data are available at Bioinformatics Advances online.

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“…Furthermore, for a substitution matrix assigning a score to any two symbols of the nucleotide alphabet

Section: Methodsmentioning

confidence: 99%

App-SpaM: phylogenetic placement of short reads without sequence alignment

Blanke

Morgenstern

2021

Bioinformatics Advances

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“…These methods are used to infer evolutionary relationships, e.g. by estimating evolutionary distances between sequences [5,17]. For example, they are used to classify sequences taxonomically, based on seed matches to a database of reference genomes [23,28], which is phylogenetic placement [13].…”

Section: Introductionmentioning

confidence: 99%

How to optimally sample a sequence for rapid analysis

Frith

Shaw

Spouge

2022

Preprint

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We face an increasing flood of genetic sequence data, from diverse sources, requiring rapid computational analysis. Rapid analysis can be achieved by sampling a subset of positions in each sequence. Previous sequence-sampling methods, such as minimizers, syncmers, and minimally-overlapping words, were developed by heuristic intuition, and are not optimal. We present a sequence-sampling approach that provably optimizes sensitivity for a whole class of sequence comparison methods, for randomly-evolving sequences. It it likely near-optimal for a wide range of alignment-based and alignment-free analyses. For real biological DNA, it increases specificity by avoiding simple repeats. Our approach generalizes universal hitting sets (which guarantee to sample a sequence at least once), and polar sets (which guarantee to sample a sequence at most once). This helps us understand how to do rapid sequence analysis as accurately as possible.

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“…As we have shown in previous papers, this approach can reliably distinguish between homologous and background SpaMs [ 34 ]. Other approaches have been proposed recently, that use the number of SpaMs to estimate phylogenetic distances between DNA sequences [ 36 , 39 ], see [ 40 ] for a review of the various SpaM -based methods.…”

Section: Introductionmentioning

confidence: 99%

Insertions and deletions as phylogenetic signal in an alignment-free context

Birth

Dencker²,

Morgenstern³

2022

PLoS Comput Biol

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Most methods for phylogenetic tree reconstruction are based on sequence alignments; they infer phylogenies from substitutions that may have occurred at the aligned sequence positions. Gaps in alignments are usually not employed as phylogenetic signal. In this paper, we explore an alignment-free approach that uses insertions and deletions (indels) as an additional source of information for phylogeny inference. For a set of four or more input sequences, we generate so-called quartet blocks of four putative homologous segments each. For pairs of such quartet blocks involving the same four sequences, we compare the distances between the two blocks in these sequences, to obtain hints about indels that may have happened between the blocks since the respective four sequences have evolved from their last common ancestor. A prototype implementation that we call Gap-SpaM is presented to infer phylogenetic trees from these data, using a quartet-tree approach or, alternatively, under the maximum-parsimony paradigm. This approach should not be regarded as an alternative to established methods, but rather as a complementary source of phylogenetic information. Interestingly, however, our software is able to produce phylogenetic trees from putative indels alone that are comparable to trees obtained with existing alignment-free methods.

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Sequence Comparison Without Alignment: The SpaM Approaches

Cited by 11 publications

References 71 publications

App-SpaM: phylogenetic placement of short reads without sequence alignment

App-SpaM: phylogenetic placement of short reads without sequence alignment

How to optimally sample a sequence for rapid analysis

Insertions and deletions as phylogenetic signal in an alignment-free context

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