Evidence map›Paper›PMID 35946263›Full record

ArticleGenome biology and evolution2022

A Practical Guide to Design and Assess a Phylogenomic Study.

Jesus Lozano-Fernandez

Abstract read
In one paragraph

Article in Genome biology and evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Characterization of the complete mitochondrial genome ofMitochondrial DNA. Part B, Resources · 2026
    Article
  12. Phylogenetic Methods Meet Deep Learning.Genome biology and evolution · 2025
    Article
  13. Article
  14. Article
  15. Article
  16. Genome Annotation.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  17. Insect Phylogenomics: From Experiment Planning to Post-phylogenetic Analyses.Methods in molecular biology (Clifton, N.J.) · 2025
    Review
  18. Article
  19. Article
  20. Article
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

1 author.

Jesus Lozano-FernandezDepartment of Genetics, Microbiology and Statistics, Biodiversity Research Institute (IRBio), University of Barcelona, Avd. Diagonal 643, 08028 Barcelona, Spain.ORCID 0000-0003-3597-1221

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the last decade, molecular systematics has undergone a change of paradigm as high-throughput sequencing now makes it possible to reconstruct evolutionary relationships using genome-scale datasets. The advent of "big data" molecular phylogenetics provided a battery of new tools for biologists but simultaneously brought new methodological challenges. The increase in analytical complexity comes at the price of highly specific training in computational biology and molecular phylogenetics, resulting very often in a polarized accumulation of knowledge (technical on one side and biological on the other). Interpreting the robustness of genome-scale phylogenetic studies is not straightforward, particularly as new methodological developments have consistently shown that the general belief of "more genes, more robustness" often does not apply, and because there is a range of systematic errors that plague phylogenomic investigations. This is particularly problematic because phylogenomic studies are highly heterogeneous in their methodology, and best practices are often not clearly defined. The main aim of this article is to present what I consider as the ten most important points to take into consideration when planning a well-thought-out phylogenomic study and while evaluating the quality of published papers. The goal is to provide a practical step-by-step guide that can be easily followed by nonexperts and phylogenomic novices in order to assess the technical robustness of phylogenomic studies or improve the experimental design of a project.

Indexed as

Biological EvolutionHigh-Throughput Nucleotide SequencingComputational BiologyGenomePhylogenygenomicshigh-throughput sequencingmodels of sequence evolutionphylogeneticssystematic errorsystematics

Identifiers

PMID35946263
PMCPMC9452790

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.