Evidence map›Paper›PMID 38816211›Full record

ArticleIntegrative and comparative biology2024

Practical Guidance and Workflows for Identifying Fast Evolving Non-Coding Genomic Elements Using PhyloAcc.

Gregg W C Thomas, Patrick Gemmell, Subir B Shakya, Zhirui Hu, Jun S Liu, Timothy B Sackton, Scott V Edwards

Abstract read
In one paragraph

Article in Integrative and comparative biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. The genetic foundations of convergent traits.Nature reviews. Genetics · 2026
    Review
  3. Review
  4. 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

7 authors.

Gregg W C ThomasInformatics Group, Harvard University, Cambridge, MA 02138, USA.
Patrick GemmellDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA.
Subir B ShakyaInformatics Group, Harvard University, Cambridge, MA 02138, USA.
Zhirui HuGladstone Institute of Data Science and Biotechnology, San Francisco, CA 94158, USA.
Jun S LiuDepartment of Statistics, Harvard University, Cambridge, MA 02138, USA.
Timothy B SacktonInformatics Group, Harvard University, Cambridge, MA 02138, USA.
Scott V EdwardsDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA.ORCID 0000-0003-2535-6217

Funding

Statistical and high-throughput models of enhancer function and evolutionR01HG011485 · NHGRI · HARVARD UNIVERSITY · PI EDWARDS, SCOTT V., FARLEY, EMMA KIRSTEN · 2021 to 2024
$2.5M
NHGRI NIH HHS R01 HG011485NIH HHS NHGRI R01HG011485
6 · The paper itself

Abstract

Comparative genomics provides ample ways to study genome evolution and its relationship to phenotypic traits. By developing and testing alternate models of evolution throughout a phylogeny, one can estimate rates of molecular evolution along different lineages in a phylogeny and link these rates with observations in extant species, such as convergent phenotypes. Pipelines for such work can help identify when and where genomic changes may be associated with, or possibly influence, phenotypic traits. We recently developed a set of models called PhyloAcc, using a Bayesian framework to estimate rates of nucleotide substitution on different branches of a phylogenetic tree and evaluate their association with pre-defined or estimated phenotypic traits. PhyloAcc-ST and PhyloAcc-GT both allow users to define a priori a set of target lineages and then compare different models to identify loci accelerating in one or more target lineages. Whereas ST considers only one species tree across all input loci, GT considers alternate topologies for every locus. PhyloAcc-C simultaneously models molecular rates and rates of continuous trait evolution, allowing the user to ask whether the two are associated. Here, we describe these models and provide tips and workflows on how to prepare the input data and run PhyloAcc.

Indexed as

Bayes TheoremEvolution, MolecularGenomicsModels, GeneticPhylogenyAnimalsSoftwareWorkflow

Identifiers

PMID38816211
PMCPMC11579529

What OpenQuestion holds

Textmetadata
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.