Evidence map›Paper›PMID 39896589›Full record

ArticlebioRxiv : the preprint server for biology2025

WASTER: Practical

Chao Zhang, Rasmus Nielsen

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Chao ZhangGlobe Institute, University of Copenhagen, Øster Voldgade 5-7, Copenhagen, 1350, Denmark.ORCID 0000-0002-4222-9968
Rasmus NielsenGlobe Institute, University of Copenhagen, Øster Voldgade 5-7, Copenhagen, 1350, Denmark.

Funding

Enabling Precision Genomics Using Adaptive VariationR01GM138634 · NIGMS · UNIVERSITY OF CALIFORNIA BERKELEY · PI NIELSEN, RASMUS · 2020 to 2023
$1.7M
Inference and application of graphs for genomic dataR35GM153400 · NIGMS · UNIVERSITY OF CALIFORNIA BERKELEY · PI RASMUS NIELSEN · 2024 to 2026
$1.3M
NIGMS NIH HHS R01 GM138634NIGMS NIH HHS R35 GM153400
6 · The paper itself

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

Indexed as

Alignment freeAssembly freeLow coverage readsPhylogenomicsShallow phylogenies

Identifiers

PMID39896589
PMCPMC11785061

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.