kamino: proteome-wide variant calling for amino acid phylogenomics
Derelle, R.; Lees, J. A.; Chindelevitch, L.
Show abstract
Amino acid-based phylogenetics usually relies on first clustering and aligning orthologous proteins. This approach is powerful but computationally demanding. Here, we present kamino, a reference-free and alignment-free method that builds amino acid phylogenomic alignments directly from proteomes. kamino adapts a local graph-based variant-calling algorithm to efficiently identify variable homologous positions among proteins and concatenate these polymorphic regions. Across diverse prokaryotic and eukaryotic datasets, we showed that kamino is able to generate good quality alignments. Phylogenetic analyses revealed that kamino generally recovered signals broadly similar to those obtained from marker-based approaches, while being much faster. Its main limitations are reduced performance on deeply divergent prokaryotic datasets and substantial memory requirements for large eukaryotic datasets. kamino therefore provides a fast and simple approach for constructing phylogenomic amino acid alignments, complementing classical marker-based workflows. The program is implemented in Rust and is freely available at https://github.com/rderelle/kamino.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- PhyloMagnet: Fast and accurate screening of short-read meta-omics data using gene-centric phylogenetics 94%
- TopHap: Rapid inference of key phylogenetic structures from common haplotypes in large genome collections with limited diversity 94%
- raxtax: A k-mer-based non-Bayesian Taxonomic Classifier 94%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.