Evidence map›Paper›PMID 27309738›Full record

ArticlePLoS computational biology2016

Training in High-Throughput Sequencing: Common Guidelines to Enable Material Sharing, Dissemination, and Reusability.

Bastian Schiffthaler, Myrto Kostadima, NGS Trainer Consortium, Nicolas Delhomme, Gabriella Rustici

Abstract read
In one paragraph

Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. 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

5 authors.

Bastian SchiffthalerDepartment of Plant Physiology, Umeå Plant Science Centre, Umeå University, Umeå, Sweden.
Myrto KostadimaDepartment of Haematology, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-1818-4050
NGS Trainer Consortium
Nicolas DelhommeDepartment of Plant Physiology, Umeå Plant Science Centre, Umeå University, Umeå, Sweden.ORCID 0000-0002-3053-0796
Gabriella RusticiSchool of Biological Sciences, Department of Genetics, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0003-3085-1271

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The advancement of high-throughput sequencing (HTS) technologies and the rapid development of numerous analysis algorithms and pipelines in this field has resulted in an unprecedentedly high demand for training scientists in HTS data analysis. Embarking on developing new training materials is challenging for many reasons. Trainers often do not have prior experience in preparing or delivering such materials and struggle to keep them up to date. A repository of curated HTS training materials would support trainers in materials preparation, reduce the duplication of effort by increasing the usage of existing materials, and allow for the sharing of teaching experience among the HTS trainers' community. To achieve this, we have developed a strategy for materials' curation and dissemination. Standards for describing training materials have been proposed and applied to the curation of existing materials. A Git repository has been set up for sharing annotated materials that can now be reused, modified, or incorporated into new courses. This repository uses Git; hence, it is decentralized and self-managed by the community and can be forked/built-upon by all users. The repository is accessible at http://bioinformatics.upsc.se/htmr.

Indexed as

AlgorithmsComputational BiologyData Interpretation, StatisticalEducationHigh-Throughput Nucleotide SequencingHumansTeaching

Identifiers

PMID27309738
PMCPMC4910983

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.