Evidence map›Paper›PMID 31071140›Full record

ArticlePloS one2019

NanoR: A user-friendly R package to analyze and compare nanopore sequencing data.

Davide Bolognini, Niccolò Bartalucci, Alessandra Mingrino, Alessandro Maria Vannucchi, Alberto Magi

Abstract readComparative Study
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
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  3. Review
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  6. Review
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  11. Review
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  13. Article
  14. Versatile Quality Control Methods for Nanopore Sequencing.Evolutionary bioinformatics online · 2019
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Davide BologniniDepartment of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, Florence, Italy.ORCID 0000-0002-8735-8093
Niccolò BartalucciDepartment of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, Florence, Italy.
Alessandra MingrinoDepartment of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, Florence, Italy.
Alessandro Maria VannucchiDepartment of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, Florence, Italy.
Alberto MagiDepartment of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, Florence, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MinION and GridION X5 from Oxford Nanopore Technologies are devices for real-time DNA and RNA sequencing. On the one hand, MinION is the only real-time, low cost and portable sequencing device and, thanks to its unique properties, is becoming more and more popular among biologists; on the other, GridION X5, mainly for its costs, is less widespread but highly suitable for researchers with large sequencing projects. Despite the fact that Oxford Nanopore Technologies' devices have been increasingly used in the last few years, there is a lack of high-performing and user-friendly tools to handle the data outputted by both MinION and GridION X5 platforms. Here we present NanoR, a cross-platform R package designed with the purpose to simplify and improve nanopore data visualization. Indeed, NanoR is built on few functions but overcomes the capabilities of existing tools to extract meaningful informations from MinION sequencing data; in addition, as exclusive features, NanoR can deal with GridION X5 sequencing outputs and allows comparison of both MinION and GridION X5 sequencing data in one command. NanoR is released as free package for R at https://github.com/davidebolo1993/NanoR.

Indexed as

NanoporesNanopore SequencingSequence Analysis, DNASoftware

Identifiers

PMID31071140
PMCPMC6508625

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.