APPLES: Scalable Distance-Based Phylogenetic Placement with or without Alignments

Balaban, Metin; Sarmashghi, Shahab; Mirarab, Siavash

doi:10.1093/sysbio/syz063

“…These approaches rely on assembly construction pipelines (e.g., Jin et al, 2019) to remove contaminants (i.e., to avoid misassembly or to filter out misassembled contigs). Elsewhere, we have advocated going beyond organelle genomes and using all reads in an assembly-free fashion to increase the resolution of taxonomic identification (Balaban et al, 2019;Sarmashghi et al, 2019). However, this goal has been hampered by the presence of contaminants.…”

Section: Discussionmentioning

confidence: 99%

“…By combining these three principles, Skmer provides excellent accuracy in estimating distances between genome skims. These distances can then be used for taxonomic identification and phylogenetic placement (Balaban, Sarmashghi, & Mirarab, 2019) of query genome skims with respect to a set of reference genome skims. Previous results have shown high accuracy and increased resolution compared to barcodes when using genome skims for taxonomic identification (Balaban et al, 2019;Sarmashghi et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

The impact of contaminants on the accuracy of genome skimming and the effectiveness of exclusion read filters

Rachtman

¹

,

Balaban

²

,

Bafna

³

et al. 2020

Molecular Ecology Resources

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The ability to detect the identity of a sample obtained from its environment is a cornerstone of molecular ecological research. Thanks to the falling price of shotgun sequencing, genome skimming, the acquisition of short reads spread across the genome at low coverage, is emerging as an alternative to traditional barcoding. By obtaining far more data across the whole genome, skimming has the promise to increase the precision of sample identification beyond traditional barcoding while keeping the costs manageable. While methods for assembly‐free sample identification based on genome skims are now available, little is known about how these methods react to the presence of DNA from organisms other than the target species. In this paper, we show that the accuracy of distances computed between a pair of genome skims based on k‐mer similarity can degrade dramatically if the skims include contaminant reads; i.e., any reads originating from other organisms. We establish a theoretical model of the impact of contamination. We then suggest and evaluate a solution to the contamination problem: Query reads in a genome skim against an extensive database of possible contaminants (e.g., all microbial organisms) and filter out any read that matches. We evaluate the effectiveness of this strategy when implemented using Kraken‐II, in detailed analyses. Our results show substantial improvements in accuracy as a result of filtering but also point to limitations, including a need for relatively close matches in the contaminant database.

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“…In the last few years, a number of alignment-free approaches have been proposed that are able to use unassembled short sequencing reads as input [9,28,35,37,63,64], as a basis for sequence clustering [34], for phylogenetic tree reconstruction [65] or for phylogenetic placement [64]. We are planning to evaluate systematically if Slope-SpaM can be used to find the position of unassembled reads in existing phylogenies, or to estimate phylogenetic distances between species based on sequencing reads instead of assembled genomes.…”

Section: Availability and Future Directionsmentioning

confidence: 99%

The number of k-mer matches between two DNA sequences as a function of k and applications to estimate phylogenetic distances

Röhling

¹

,

Linne

²

,

Schellhorn

³

et al. 2020

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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 (SpaM), where mismatches are allowed at positions specified by a user-defined binary pattern. Based on these theoretical results, we implemented a prototype 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. OPEN ACCESSCitation: Röhling S, Linne A, Schellhorn J, Hosseini M, Dencker T, Morgenstern B (2020) The number of k-mer matches between two DNA sequences as a function of k and applications to estimate phylogenetic distances. PLoS ONE 15(2): e0228070. https://doi.org/10. Data Availability Statement:The source code of our software is freely available through GitHub Traditionally, phylogenetic distances are inferred from pairwise or multiple sequence alignments. 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 alignment-free approaches that can estimate phylogenetic distances without the need to calculate full alignments of the input sequences, see [3][4][5][6][7] for recent review articles. Alignment-free approaches are not only used in phylogeny reconstruction, but are also important in metagenomics [8][9][10], to find genome rearrangements [11] and in epidemiology [12] and other medical applications, for example to identify drug-resistant bacteria [13] or to classify viruses [14,15]. In all these applications, it is crucial to rapidly estimate pairwise similarity or dissimilarity values in large sets of sequence data.Some alignment-free approaches are based on word frequencies [16,17] or on the length of common substrings [18][19][20]. Other methods use variants of the D 2 distance which is defined as the number of word matches of a pre-defined length between two sequences [15,[21][22][23]; a review focusing on these methods is given in [24]. kWIP [25] is a further development of this concept that uses information-theoretical...

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“…In the last few years, a number of alignment-free approaches have been proposed that are able to use unassembled short sequencing reads as input [54,14,39,33,3,47], as a basis for sequence clustering [1], for phylogenetic tree reconstruction [? ] or for phylogenetic placement [3]. We are planning to evaluate systematically if Slope-SpaM can be used to find the position of unassembled reads in existing phylogenies, or to estimate phylogenetic distances between species based on sequencing reads instead of assembled genomes.…”

Section: Availability and Future Directionsmentioning

confidence: 99%

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

Röhling

¹

,

Dencker

²

,

Morgenstern

³

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.

show abstract

APPLES: Scalable Distance-Based Phylogenetic Placement with or without Alignments

Cited by 66 publications

References 59 publications

The impact of contaminants on the accuracy of genome skimming and the effectiveness of exclusion read filters

The impact of contaminants on the accuracy of genome skimming and the effectiveness of exclusion read filters

The number of k-mer matches between two DNA sequences as a function of k and applications to estimate phylogenetic distances

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

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