Evidence map›Paper›PMID 27054412›Full record

ArticleeLife2016

Using mobile sequencers in an academic classroom.

Sophie Zaaijer, Columbia University Ubiquitous Genomics 2015 class, Yaniv Erlich

Abstract read
In one paragraph

Article in eLife, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Article
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  5. Balancing openness with Indigenous data sovereignty: An opportunity to leave no one behind in the journey to sequence all of life.Proceedings of the National Academy of Sciences of the United States of America · 2022
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  13. Review
  14. Article
  15. Meet-U: Educating through research immersion.PLoS computational biology · 2018
    Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. 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.

Sophie ZaaijerDepartment of Computer Science, Fu Foundation School of Engineering, Columbia University, New York, United States.
Columbia University Ubiquitous Genomics 2015 class
Yaniv ErlichDepartment of Computer Science, Fu Foundation School of Engineering, Columbia University, New York, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The advent of mobile DNA sequencers has made it possible to generate DNA sequencing data outside of laboratories and genome centers. Here, we report our experience of using the MinION, a mobile sequencer, in a 13-week academic course for undergraduate and graduate students. The course consisted of theoretical sessions that presented fundamental topics in genomics and several applied hackathon sessions. In these hackathons, the students used MinION sequencers to generate and analyze their own data and gain hands-on experience in the topics discussed in the theoretical classes. The manuscript describes the structure of our class, the educational material, and the lessons we learned in the process. We hope that the knowledge and material presented here will provide the community with useful tools to help educate future generations of genome scientists.

Indexed as

HumansMolecular BiologySequence Analysis, DNAeducationgeneticsgenomicshuman

Identifiers

PMID27054412
PMCPMC4869913

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.