Evidence map›Paper›PMID 30602937›Full record

ArticleProceedings. Mathematical, physical, and engineering sciences2018

Bridging trees for posterior inference on ancestral recombination graphs.

K Heine, A Beskos, A Jasra, D Balding, M De Iorio

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Proceedings. Mathematical, physical, and engineering sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. A general and efficient representation of ancestral recombination graphs.bioRxiv : the preprint server for biology · 2024
    Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Methodologies for Microbial Ancestral Sequence Reconstruction.Methods in molecular biology (Clifton, N.J.) · 2022
    Review
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

5 authors.

K HeineDepartment of Mathematical Sciences, University of Bath, Claverton Down, Bath BA2 7AY, UK.ORCID 0000-0001-6300-3258
A BeskosDepartment of Statistical Science, University College London, Gower Street, London WC1E 6BT, UK.
A JasraDepartment of Statistics and Applied Probability, National University of Singapore, 6 Science Drive 2, 117546, Singapore.
D BaldingCentre for Systems Genomics, School of BioSciences, University of Melbourne, Victoria 3010, Australia.
M De IorioDepartment of Statistical Science, University College London, Gower Street, London WC1E 6BT, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present a new Markov chain Monte Carlo algorithm, implemented in the software Arbores, for inferring the history of a sample of DNA sequences. Our principal innovation is a bridging procedure, previously applied only for simple stochastic processes, in which the local computations within a bridge can proceed independently of the rest of the DNA sequence, facilitating large-scale parallelization.

Indexed as

ancestral recombination graphBayesian inferencecoalescentMarkov chain Monte Carlotree scanning

Identifiers

PMID30602937
PMCPMC6304023

What OpenQuestion holds

Textmetadata
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Registered trials

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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.