Evidence map›Paper›PMID 38941113›Full record

ArticleBriefings in bioinformatics2024

A cloud-based training module for efficient de novo transcriptome assembly using Nextflow and Google cloud.

Ryan P Seaman, Ross Campbell, Valena Doe, Zelaikha Yosufzai, Joel H Graber

Erratum issuedAbstract read
In one paragraph

Article in Briefings in bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Ryan P SeamanMDI Biological Laboratory, 159 Old Bar Harbor Road, Bar Harbor, ME 04609, USA.
Ross CampbellHealth Data and AI, 4301 Fairfax Dr, Unit 210, Deloitte Consulting LLP, Arlington, VA 22203, USA.
Valena DoeGoogle Cloud, Google, 1900 Reston Metro Plaza, Reston, VA 20190, USA.
Zelaikha YosufzaiHealth Data and AI, 4301 Fairfax Dr, Unit 210, Deloitte Consulting LLP, Arlington, VA 22203, USA.
Joel H GraberMDI Biological Laboratory, 159 Old Bar Harbor Road, Bar Harbor, ME 04609, USA.ORCID 0000-0001-5137-4553

Funding

The Maine Biomedical Research Network (INBRE)P20GM103423 · NIGMS · MOUNT DESERT ISLAND BIOLOGICAL LAB · PI Dustin Lynn Updike · 2012 to 2026
$60.0M
Administrative Supplement to the Maine INBREInstitutional Development AwardNational Institute of General Medical Sciences of the National Institutes of Health P20GM103423NIGMS NIH HHS P20 GM103423
6 · The paper itself

Abstract

This study describes the development of a resource module that is part of a learning platform named "NIGMS Sandbox for Cloud-based Learning" (https://github.com/NIGMS/NIGMS-Sandbox). The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox at the beginning of this Supplement. This module delivers learning materials on de novo transcriptome assembly using Nextflow in an interactive format that uses appropriate cloud resources for data access and analysis. Cloud computing is a powerful new means by which biomedical researchers can access resources and capacity that were previously either unattainable or prohibitively expensive. To take advantage of these resources, however, the biomedical research community needs new skills and knowledge. We present here a cloud-based training module, developed in conjunction with Google Cloud, Deloitte Consulting, and the NIH STRIDES Program, that uses the biological problem of de novo transcriptome assembly to demonstrate and teach the concepts of computational workflows (using Nextflow) and cost- and resource-efficient use of Cloud services (using Google Cloud Platform). Our work highlights the reduced necessity of on-site computing resources and the accessibility of cloud-based infrastructure for bioinformatics applications.

Indexed as

Cloud ComputingTranscriptomeComputational BiologyGene Expression ProfilingHumansInternetSoftwareannotationassemblycloud computingnextflowtraining moduletranscriptome

Identifiers

PMID38941113
PMCPMC11212313

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.