Evidence map›Paper›PMID 34305211›Full record

ArticleJournal of the American Statistical Association2021

Nonbifurcating Phylogenetic Tree Inference via the Adaptive LASSO.

Cheng Zhang, V U Dinh, Frederick A Matsen

Abstract read
In one paragraph

Article in Journal of the American Statistical Association, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Cheng ZhangSchool of Mathematical Sciences and Center for Statistical Science, Peking University.
V U DinhDepartment of Mathematical Sciences, University of Delaware.
Frederick A MatsenComputational Biology Program, Fred Hutchinson Cancer Research Center.

Funding

Understanding Transmission with Integrated Genetic and Epidemiologic InferenceU54GM111274 · NIGMS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI HALLORAN, M ELIZABETH · 2014 to 2018
$12.5M
Modeling the dynamics and evolution of immune responses to influenza virusesU19AI117891 · NIAID · EMORY UNIVERSITY · PI AHMED, RAFI, ANTIA, RUSTOM NOSHIR · 2015 to 2019
$8.4M
DEFINING THE INFANT IMMUNE RESPONSE TO HIVR01AI120961 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI OVERBAUGH, JULIE M. · 2016 to 2020
$4.1M
Leveraing deep sequencing data to understand antibody maturationR01GM113246 · NIGMS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI MATSEN, FREDERICK ALBERT · 2014 to 2018
$1.9M
NIAID NIH HHS R01 AI120961NIAID NIH HHS U19 AI117891NIGMS NIH HHS R01 GM113246NIGMS NIH HHS U54 GM111274
6 · The paper itself

Abstract

Phylogenetic tree inference using deep DNA sequencing is reshaping our understanding of rapidly evolving systems, such as the within-host battle between viruses and the immune system. Densely sampled phylogenetic trees can contain special features, including

Indexed as

adaptive LASSOconsistencyFISTAℓ1 regularizationmodel selectionphylogeneticssparsity

Identifiers

PMID34305211
PMCPMC8300927

What OpenQuestion holds

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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.