krepp: A k-mer-based maximum pseudo-likelihood method for estimating read distances and genome-wide phylogenetic placement

Comparing each sequencing read in a sample to a reference database is a fundamental step in wide-ranging applications. The results of these comparisons can facilitate phylogenetic characterization. However, phylogenetic placement is currently only possible at scale for marker genes, a small fraction of the genome. We introduce krepp, an alignment-free k-mer-based method that enables placing reads from anywhere on the genome on an ultra-large reference phylogeny (e.g., 123,853 leaves). This repository contains data from benchmarking experiments in which we show the scalability and accuracy of krepp. We also demonstrate the ability of our method to compare and characterize real metagenomic samples.
, , # Data from: krepp: A k-mer-based maximum pseudo-likelihood method for estimating read distances and genome-wide phylogenetic placement

DOI: [10.5061/dryad.63xsj3vd3](10.5061/dryad.63xsj3vd3)

Datasets and queries analyzed to benchmark *krepp*, together with results and evaluation metrics.
The preprint is available at [bioRxiv](https://www.biorxiv.org/content/10.1101/2025.01.20.633730v2).

The source code can be found on GitHub (github.com/bo1929/krepp).
The version used in the manuscript is v0.4.5 (which is also available on [Zenodo](https://doi.org/10.5281/zenodo.15466358)).
All results, auxiliary data, and scripts used in the analyses can be found at github.com/bo1929/shared.krepp.
For reference indexes, refer to:

* [https://github.com/bo1929/krepp/wiki/Available-reference-indexes](https://github.com/bo1929/krepp/wiki/Available-reference-indexes)
* [https://registry.opendata.aws/kreppref/](https://registry.opendata.aws/kreppref/)
* [https://ter-trees.ucsd.edu/data/krepp/](https://t...,