Evidence map›Paper›PMID 35194619›Full record

ArticlemedRxiv : the preprint server for health sciences2022

Analysis of 6.4 million SARS-CoV-2 genomes identifies mutations associated with fitness.

Fritz Obermeyer, Martin Jankowiak, Nikolaos Barkas, Stephen F Schaffner, Jesse D Pyle, Lonya Yurkovetskiy, Matteo Bosso, Daniel J Park, Mehrtash Babadi, Bronwyn L MacInnis and 3 more

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed, 59 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors at 2 institutions in 1 country.

Fritz ObermeyerBroad Institute of MIT and Harvard; 415 Main Street, Cambridge, MA 02142, USA.
Martin JankowiakBroad Institute of MIT and Harvard; 415 Main Street, Cambridge, MA 02142, USA.
Nikolaos BarkasBroad Institute of MIT and Harvard; 415 Main Street, Cambridge, MA 02142, USA.
Stephen F SchaffnerBroad Institute of MIT and Harvard; 415 Main Street, Cambridge, MA 02142, USA.
Jesse D PyleBroad Institute of MIT and Harvard; 415 Main Street, Cambridge, MA 02142, USA.
Lonya YurkovetskiyProgram in Molecular Medicine, University of Massachusetts Medical School; Worcester, MA 01605, USA.
Matteo BossoProgram in Molecular Medicine, University of Massachusetts Medical School; Worcester, MA 01605, USA.
Daniel J ParkBroad Institute of MIT and Harvard; 415 Main Street, Cambridge, MA 02142, USA.
Mehrtash BabadiBroad Institute of MIT and Harvard; 415 Main Street, Cambridge, MA 02142, USA.
Bronwyn L MacInnisBroad Institute of MIT and Harvard; 415 Main Street, Cambridge, MA 02142, USA.
Jeremy LubanBroad Institute of MIT and Harvard; 415 Main Street, Cambridge, MA 02142, USA.
Pardis C SabetiBroad Institute of MIT and Harvard; 415 Main Street, Cambridge, MA 02142, USA.
Jacob E LemieuxBroad Institute of MIT and Harvard; 415 Main Street, Cambridge, MA 02142, USA.
Broad Institute · USUniversity of Massachusetts Chan Medical School · US

Funding

The HUSH complex in HIV-1 latencyR37AI147868 · NIAID · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI JEREMY LUBAN · 2019 to 2026
$6.4M
NIAID NIH HHS R37 AI147868
6 · The paper itself

Abstract

Repeated emergence of SARS-CoV-2 variants with increased fitness necessitates rapid detection and characterization of new lineages. To address this need, we developed PyR ONE SENTENCE SUMMARY: A Bayesian hierarchical model of all SARS-CoV-2 viral genomes predicts lineage fitness and identifies associated mutations.

Identifiers

PMID35194619
PMCPMC8863165
OpenAlexW3199067048

What OpenQuestion holds

Textmetadata
LicenceCC BY-ND
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.