ArticlePLoS computational biology2024
Robust expansion of phylogeny for fast-growing genome sequence data.
Article in PLoS computational biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Genomic features associated with sustained mammalian transmission of avian influenza A viruses.Nature microbiology · 2026Article
- Scalable method for exploring phylogenetic placement uncertainty with custom visualizations usingiMeta · 2025Article
- Development of avian influenza A(H5) virus datasets for Nextclade enables rapid and accurate clade assignment.Virus evolution · 2025Article
- F1ALA: ultrafast and memory-efficient ancestral lineage annotation applied to the huge SARS-CoV-2 phylogeny.Virus evolution · 2024Article
- Variational Phylodynamic Inference Using Pandemic-scale Data.Molecular biology and evolution · 2022Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Massive sequencing of SARS-CoV-2 genomes has urged novel methods that employ existing phylogenies to add new samples efficiently instead of de novo inference. 'TIPars' was developed for such challenge integrating parsimony analysis with pre-computed ancestral sequences. It took about 21 seconds to insert 100 SARS-CoV-2 genomes into a 100k-taxa reference tree using 1.4 gigabytes. Benchmarking on four datasets, TIPars achieved the highest accuracy for phylogenies of moderately similar sequences. For highly similar and divergent scenarios, fully parsimony-based and likelihood-based phylogenetic placement methods performed the best respectively while TIPars was the second best. TIPars accomplished efficient and accurate expansion of phylogenies of both similar and divergent sequences, which would have broad biological applications beyond SARS-CoV-2. TIPars is accessible from https://tipars.hku.hk/ and source codes are available at https://github.com/id-bioinfo/TIPars.
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Registered trials
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