{"doi":"10.1101/2025.01.20.633983","title":"WASTER: Practical <i>de novo</i> phylogenomics from low-coverage short reads","abstract":"Abstract The advent of affordable whole-genome sequencing has spurred numerous large-scale projects aimed at inferring the tree of life, yet achieving a complete species-level phylogeny remains a distant goal due to significant costs and computational demands. Traditional species tree inference methods, though effective, are hampered by the need for high-coverage sequencing, high-quality genomic alignments, and extensive computational resources. To address these challenges, this study introduces WASTER, a novel de novo tool for inferring shallow phylogenies directly from short-read sequences. WASTER employs a k-mer based approach for identifying variable sites, circumventing the need for genome assembly and alignment. Using simulations, we demonstrate that WASTER achieves accuracy comparable to that of traditional alignment-based methods, even for low sequencing depth, and has substantially higher accuracy than other alignment-free methods. We validate WASTER’s efficacy on real data, where it accurately reconstructs phylogenies of eukaryotic species with as low depth as 1.5X. WASTER provides a fast and efficient solution for phylogeny estimation in cases where genome assembly and/or alignment may bias analyses or is challenging, for example due to low sequencing depth. It also provides a method for generating guide trees for tree-based alignment algorithms. WASTER’s ability to accurately estimate shallow phylogenies from low-coverage sequencing data without relying on assembly and alignment will lead to substantially reduced sequencing and computational costs in phylogenomic projects.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2025,"id":555366,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9452,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":7695,"name":"Rasmus Nielsen","orcid":"0000-0003-0513-6591","position":1,"is_corresponding":false},{"id":283068,"name":"Chao Zhang","orcid":"0000-0002-4222-9968","position":0,"is_corresponding":true}],"reference_count":40,"raw_metadata":null,"created_at":"2026-07-19T02:54:59.329539Z","pmid":"39896589","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}