Evidence map›Paper›PMID 36265468›Full record

ArticleCell systems2022

Quantifying the uncertainty of assembly-free genome-wide distance estimates and phylogenetic relationships using subsampling.

Eleonora Rachtman, Shahab Sarmashghi, Vineet Bafna, Siavash Mirarab

Open access · greenAbstract read
In one paragraph

Article in Cell systems, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.0field-weighted citation impact, top 25% of its field
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

7 citing papers in PubMed, 12 citations in OpenAlex.

  1. DipSkmer: Reference-free population genomics with diploid genome skims.bioRxiv : the preprint server for biology · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Eleonora RachtmanBioinformatics and Systems Biology Graduate Program, UC San Diego, San Diego, CA 92093, USA.
Shahab SarmashghiDepartment of Electrical and Computer Engineering, UC San Diego, San Diego, CA 92093, USA.
Vineet BafnaDepartment of Computer Science and Engineering, UC San Diego, San Diego, CA 92093, USA.
Siavash MirarabDepartment of Electrical and Computer Engineering, UC San Diego, San Diego, CA 92093, USA. Electronic address: smirarab@ucsd.edu.
University of California, San Diego · US

Funding

Biology-aware machine learning methods for characterizing microbiome genotype and phenotypeR35GM142725 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MIR ARABBAYGI, SIAVASH · 2021 to 2025
$1.9M
NIGMS NIH HHS R35 GM142725
6 · The paper itself

Abstract

Computing distance between two genomes without alignments or even access to assemblies has many downstream analyses. However, alignment-free methods, including in the fast-growing field of genome skimming, are hampered by a significant methodological gap. While accurate methods (many k-mer-based) for assembly-free distance calculation exist, measuring the uncertainty of estimated distances has not been sufficiently studied. In this paper, we show that bootstrapping, the standard non-parametric method of measuring estimator uncertainty, is not accurate for k-mer-based methods that rely on k-mer frequency profiles. Instead, we propose using subsampling (with no replacement) in combination with a correction step to reduce the variance of the inferred distribution. We show that the distribution of distances using our procedure matches the true uncertainty of the estimator. The resulting phylogenetic support values effectively differentiate between correct and incorrect branches and identify controversial branches that change across alignment-free and alignment-based phylogenies reported in the literature.

Indexed as

AlgorithmsGenomePhylogenySequence AlignmentUncertaintyassembly-free and alignment-free distance calculationdata subsamplinggenome skimminggenomic distancek-mer-based distance calculationphylogenetic uncertaintystatistical branch supportuncertainty quantification

Identifiers

PMID36265468
PMCPMC9589918
OpenAlexW4306851531

What OpenQuestion holds

Textmetadata
LicenceTDM
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.