Evidence map›Paper›PMID 26586802›Full record

ArticleNucleic acids research2016

Estimate of within population incremental selection through branch imbalance in lineage trees.

Gilad Liberman, Jennifer I C Benichou, Yaakov Maman, Jacob Glanville, Idan Alter, Yoram Louzoun

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2016. 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
1.5field-weighted citation impact, top 15% 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, 8 citations in OpenAlex.

  1. Article
  2. Antibody repertoire sequencing analysis.Acta biochimica et biophysica Sinica · 2022
    Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. The analysis of clonal expansions in normal and autoimmune B cell repertoires.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2015
    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

6 authors at 3 institutions in 2 countries.

Gilad LibermanGonda Multidisciplinary Brain Research Center, Bar Ilan University, Ramat-Gan 5290002, Israel.
Jennifer I C BenichouDepartment of Mathematics, Bar Ilan University, Ramat-Gan 5290002, Israel.
Yaakov MamanDepartment of Immunobiology, Yale University School of Medicine, New Haven, CT 06520-8011, USA Howard Hughes Medical Institute, New Haven, CT 06519, USA.
Jacob GlanvilleProgram in Computational and Systems Immunology, Stanford University, Stanford, CA 94305, USA Department of Pathology, Transplantation and Infection, Stanford University, Stanford, CA 94305, USA Program in Immunology, Transplantation and Infection, Stanford University, Stanford, CA 94305, USA Distributed Bio, San Francisco, CA 94080, USA.
Idan AlterDepartment of Mathematics, Bar Ilan University, Ramat-Gan 5290002, Israel.
Yoram LouzounGonda Multidisciplinary Brain Research Center, Bar Ilan University, Ramat-Gan 5290002, Israel Department of Mathematics, Bar Ilan University, Ramat-Gan 5290002, Israel ylouzoun@gmail.com.
Bar-Ilan University · ILStanford University · USYale University · US

Funding

MOLECULAR &CELLULAR IMMUNOBIOLOGYT32AI007290 · NIAID · STANFORD UNIVERSITY · PI Sean Curtis Bendall, Olivia M Martinez · 1985 to 2026
$27.0M
NIAID NIH HHS T32 AI007290
6 · The paper itself

Abstract

Incremental selection within a population, defined as limited fitness changes following mutation, is an important aspect of many evolutionary processes. Strongly advantageous or deleterious mutations are detected using the synonymous to non-synonymous mutations ratio. However, there are currently no precise methods to estimate incremental selection. We here provide for the first time such a detailed method and show its precision in multiple cases of micro-evolution. The proposed method is a novel mixed lineage tree/sequence based method to detect within population selection as defined by the effect of mutations on the average number of offspring. Specifically, we propose to measure the log of the ratio between the number of leaves in lineage trees branches following synonymous and non-synonymous mutations. The method requires a high enough number of sequences, and a large enough number of independent mutations. It assumes that all mutations are independent events. It does not require of a baseline model and is practically not affected by sampling biases. We show the method's wide applicability by testing it on multiple cases of micro-evolution. We show that it can detect genes and inter-genic regions using the selection rate and detect selection pressures in viral proteins and in the immune response to pathogens.

Indexed as

AlgorithmsBiological EvolutionModels, GeneticPedigreeSelection, GeneticAlphapapillomavirusAnimalsBase SequenceComputer SimulationEpitopesHepatitis B virusHIVHumansImmunoglobulinsInfluenza A virusMiceEpitopesImmunoglobulinsReceptors, Antigen, B-CellRNA, Viral

Identifiers

PMID26586802
PMCPMC4797263
OpenAlexW2219842023

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.