ArticleMethods in molecular biology (Clifton, N.J.)2021
Sequence Comparison Without Alignment: The SpaM Approaches.
Article in Methods in molecular biology (Clifton, N.J.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed.
- CGRWDL: alignment-free phylogeny reconstruction method for viruses based on chaos game representation weighted by dynamical language model.Frontiers in microbiology · 2024Article
- How to optimally sample a sequence for rapid analysis.Bioinformatics (Oxford, England) · 2023Article
- AlcoR: alignment-free simulation, mapping, and visualization of low-complexity regions in biological data.GigaScience · 2022Article
- The complexity landscape of viral genomes.GigaScience · 2022Article
- Insertions and deletions as phylogenetic signal in an alignment-free context.PLoS computational biology · 2022Article
- Convolutional Neural Network Applied to SARS-CoV-2 Sequence Classification.Sensors (Basel, Switzerland) · 2022Article
- App-SpaM: phylogenetic placement of short reads without sequence alignment.Bioinformatics advances · 2021Article
- The number of k-mer matches between two DNA sequences as a function of k and applications to estimate phylogenetic distances.PloS one · 2020Article
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Abstract
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 are often too slow. 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 using the length of maximal word matches. While these methods are very fast, most of them rely on ad hoc measures of sequences similarity or dissimilarity that are hard to interpret. In this chapter, 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 using a stochastic model of molecular evolution.
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