ArticleBMC genomics2017
Optimal choice of word length when comparing two Markov sequences using a χ
Article in BMC genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- K-mer-based Approaches to Bridging Pangenomics and Population Genetics.Molecular biology and evolution · 2025Review
- Article
- KITSUNE: A Tool for Identifying Empirically Optimal K-mer Length for Alignment-Free Phylogenomic Analysis.Frontiers in bioengineering and biotechnology · 2020Article
- Afann: bias adjustment for alignment-free sequence comparison based on sequencing data using neural network regression.Genome biology · 2019Article
- Alignment-Free Sequence Analysis and Applications.Annual review of biomedical data science · 2018Article
- The International Conference on Intelligent Biology and Medicine (ICIBM) 2016: summary and innovation in genomics.BMC genomics · 2017Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAlignment-free sequence comparison using counts of word patterns (grams, k-tuples) has become an active research topic due to the large amount of sequence data from the new sequencing technologies. Genome sequences are frequently modelled by Markov chains and the likelihood ratio test or the corresponding approximate χ
resultsWe develop an optimal strategy to choose k by maximizing the statistical power of detecting differences between two sequences. Let the orders of the Markov chains for the two sequences be r
conclusionOur studies provide guidelines on choosing the optimal word length for the comparison of Markov sequences.
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