Evidence map›Paper›PMID 28918303›Full record

ArticleVirology2017

Decoding noises in HIV computational genotyping.

MingRui Jia, Timothy Shaw, Xing Zhang, Dong Liu, Ye Shen, Amara E Ezeamama, Chunfu Yang, Ming Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Virology, 2017. 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.

No citing paper in PubMed yet.

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

8 authors.

MingRui JiaDepartment of Pain Management, Shandong Provincial Hospital Affiliated to Shandong University, 324 Jingwu Road, Jinan, Shandong Province 250021, China; Department of Epidemiology and Biostatistics, University of Georgia, GA 30602, USA.
Timothy ShawDepartment of Epidemiology and Biostatistics, University of Georgia, GA 30602, USA.
Xing ZhangDiagnostic Imaging center, MD Anderson Cancer Center, Houston, TX 77030, USA.
Dong LiuDepartment of Epidemiology and Biostatistics, University of Georgia, GA 30602, USA; Laboratory of Ichthyology, Shanghai Ocean University, Shanghai 201306, China.
Ye ShenDepartment of Epidemiology and Biostatistics, University of Georgia, GA 30602, USA.
Amara E EzeamamaDepartment of Psychiatry, Michigan State University, MI 48824, USA.
Chunfu YangInternational Laboratory Branch, Division of Global HIV/TB, Center for Global Health, Centers for Diseases Control and Prevention, GA 30333, USA.
Ming ZhangDepartment of Epidemiology and Biostatistics, University of Georgia, GA 30602, USA. Electronic address: mzhang01@uga.edu.

Funding

Streamlined Genotyping for HIV-1 RecombinantsR03AI120203 · NIAID · UNIVERSITY OF GEORGIA · PI ZHANG, MING · 2015 to 2016
$150k
A High-throughput Strategy to Identify HIV Intra-subtype Recombinant SequencesR03AI104258 · NIAID · UNIVERSITY OF GEORGIA · PI ZHANG, MING · 2013 to 2014
$74k
Intramural CDC HHS CC999999NIAID NIH HHS R03 AI104258NIAID NIH HHS R03 AI120203
6 · The paper itself

Abstract

Lack of a consistent and reliable genotyping system can critically impede HIV genomic research on pathogenesis, fitness, virulence, drug resistance, and genomic-based healthcare and treatment. At present, mis-genotyping, i.e., background noises in molecular genotyping, and its impact on epidemic surveillance is unknown. For the first time, we present a comprehensive assessment of HIV genotyping quality. HIV sequence data were retrieved from worldwide published records, and subjected to a systematic genotyping assessment pipeline. Results showed that mis-genotyped cases occurred at 4.6% globally, with some regional and high-risk population heterogeneities. Results also revealed a consistent mis-genotyping pattern in gp120 in all studied populations except the group of men who have sex with men. Our study also suggests novel virus diversities in the mis-genotyped cases. Finally, this study reemphasizes the importance of implementing a standardized genotyping pipeline to avoid genotyping disparity and to advance our understanding of virus evolution in various epidemiological settings.

Indexed as

Diagnostic ErrorsGenotyping TechniquesComputational BiologyGenetic VariationGenotypeHIVHumansEpidemic surveillanceHIVMolecular genotyping

Identifiers

PMID28918303
PMCPMC6443101

What OpenQuestion holds

Textmetadata
LicenceTDM
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.