Evidence map›Paper›PMID 26751471›Full record

ArticleViruses2016

Quantifying Next Generation Sequencing Sample Pre-Processing Bias in HIV-1 Complete Genome Sequencing.

Bram Vrancken, Nídia Sequeira Trovão, Guy Baele, Eric van Wijngaerden, Anne-Mieke Vandamme, Kristel van Laethem, Philippe Lemey

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in Viruses, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.3field-weighted citation impact, top 21% 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

10 citing papers in PubMed, 20 citations in OpenAlex.

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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

7 authors at 2 institutions in 2 countries.

Bram VranckenRega Institute for Medical Research, Clinical and Epidemiological Virology, Department of Microbiology and Immunology, KU Leuven-University of Leuven, 3000 Leuven, Belgium. bram.vrancken@rega.kuleuven.be.
Nídia Sequeira TrovãoRega Institute for Medical Research, Clinical and Epidemiological Virology, Department of Microbiology and Immunology, KU Leuven-University of Leuven, 3000 Leuven, Belgium. Nidia.SequeiraTrovao@rega.kuleuven.be.
Guy BaeleRega Institute for Medical Research, Clinical and Epidemiological Virology, Department of Microbiology and Immunology, KU Leuven-University of Leuven, 3000 Leuven, Belgium. guy.baele@rega.kuleuven.be.
Eric van WijngaerdenUniversity Hospitals Leuven, 3000 Leuven, Belgium. eric.vanwijngaerden@uzleuven.be.
Anne-Mieke VandammeRega Institute for Medical Research, Clinical and Epidemiological Virology, Department of Microbiology and Immunology, KU Leuven-University of Leuven, 3000 Leuven, Belgium. annemie.vandamme@uzleuven.be.
Kristel van LaethemRega Institute for Medical Research, Clinical and Epidemiological Virology, Department of Microbiology and Immunology, KU Leuven-University of Leuven, 3000 Leuven, Belgium. kristel.vanlaethem@uzleuven.be.
Philippe LemeyRega Institute for Medical Research, Clinical and Epidemiological Virology, Department of Microbiology and Immunology, KU Leuven-University of Leuven, 3000 Leuven, Belgium. philippe.lemey@rega.kuleuven.be.
Rega Institute for Medical Research · BEKU Leuven · BE

Funding

European Research Council 260864
6 · The paper itself

Abstract

Genetic analyses play a central role in infectious disease research. Massively parallelized "mechanical cloning" and sequencing technologies were quickly adopted by HIV researchers in order to broaden the understanding of the clinical importance of minor drug-resistant variants. These efforts have, however, remained largely limited to small genomic regions. The growing need to monitor multiple genome regions for drug resistance testing, as well as the obvious benefit for studying evolutionary and epidemic processes makes complete genome sequencing an important goal in viral research. In addition, a major drawback for NGS applications to RNA viruses is the need for large quantities of input DNA. Here, we use a generic overlapping amplicon-based near full-genome amplification protocol to compare low-input enzymatic fragmentation (Nextera™) with conventional mechanical shearing for Roche 454 sequencing. We find that the fragmentation method has only a modest impact on the characterization of the population composition and that for reliable results, the variation introduced at all steps of the procedure--from nucleic acid extraction to sequencing--should be taken into account, a finding that is also relevant for NGS technologies that are now more commonly used. Furthermore, by applying our protocol to deep sequence a number of pre-therapy plasma and PBMC samples, we illustrate the potential benefits of a near complete genome sequencing approach in routine genotyping.

Indexed as

Genome, ViralHigh-Throughput Nucleotide SequencingHIV-1HIV InfectionsHumansSequence Analysis, RNAfull genome sequencingHIVNGS

Identifiers

PMID26751471
PMCPMC4728572
OpenAlexW2227151527

What OpenQuestion holds

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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.