Data from: 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.