ArticlePloS one2011
Gentle masking of low-complexity sequences improves homology search.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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20 citing papers in PubMed, 38 citations in OpenAlex.
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- Mitochondrial mutations in Caenorhabditis elegans show signatures of oxidative damage and an AT-bias.Genetics · 2021Article
- Improved Large-Scale Homology Search by Two-Step Seed Search Using Multiple Reduced Amino Acid Alphabets.Genes · 2021Article
- De novo assembly, annotation, and comparative analysis of 26 diverse maize genomes.Science (New York, N.Y.) · 2021Article
- Weighted minimizer sampling improves long read mapping.Bioinformatics (Oxford, England) · 2020Article
- Tandem-genotypes: robust detection of tandem repeat expansions from long DNA reads.Genome biology · 2019Article
- Estimating error models for whole genome sequencing using mixtures of Dirichlet-multinomial distributions.Bioinformatics (Oxford, England) · 2017Article
- Evaluation of exome variants using the Ion Proton Platform to sequence error-prone regions.PloS one · 2017Article
- Split-alignment of genomes finds orthologies more accurately.Genome biology · 2015Article
- Searching for repeats, as an example of using the generalised Ruzzo-Tompa algorithm to find optimal subsequences with gaps.International journal of bioinformatics research and applications · 2014Article
- A mostly traditional approach improves alignment of bisulfite-converted DNA.Nucleic acids research · 2012Article
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1 author at 1 institution in 1 country.
Funding
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Abstract
Detection of sequences that are homologous, i.e. descended from a common ancestor, is a fundamental task in computational biology. This task is confounded by low-complexity tracts (such as atatatatatat), which arise frequently and independently, causing strong similarities that are not homologies. There has been much research on identifying low-complexity tracts, but little research on how to treat them during homology search. We propose to find homologies by aligning sequences with "gentle" masking of low-complexity tracts. Gentle masking means that the match score involving a masked letter is min(0,S), where S is the unmasked score. Gentle masking slightly but noticeably improves the sensitivity of homology search (compared to "harsh" masking), without harming specificity. We show examples in three useful homology search problems: detection of NUMTs (nuclear copies of mitochondrial DNA), recruitment of metagenomic DNA reads to reference genomes, and pseudogene detection. Gentle masking is currently the best way to treat low-complexity tracts during homology search.
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