Evidence map›Paper›PMID 39990799›Full record

ArticleArXiv2025

GitHub is an effective platform for collaborative and reproducible laboratory research.

Katharine Y Chen, Maria Toro-Moreno, Arvind Rasi Subramaniam

Abstract readPreprint
In one paragraph

Article in ArXiv, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Katharine Y ChenBasic Sciences Division and Computational Biology Section of the Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, USA.
Maria Toro-MorenoBasic Sciences Division and Computational Biology Section of the Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, USA.ORCID 0000-0002-0497-2259
Arvind Rasi SubramaniamBasic Sciences Division and Computational Biology Section of the Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, USA.ORCID 0000-0001-6145-4303

Funding

Unraveling microprotein biology with an evolutionary-immunological frameworkR01AT012826 · NCCIH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Alok Joglekar, Arvind Rasi Subramaniam · 2023 to 2026
$5.9M
Regulation of Protein Synthesis by Synonymous Codon UsageR35GM119835 · NIGMS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI SUBRAMANIAM, ARVIND RASI · 2016 to 2025
$4.1M
NCCIH NIH HHS R01 AT012826NIGMS NIH HHS R35 GM119835
6 · The paper itself

Abstract

Laboratory research is a complex, collaborative process that involves several stages, including hypothesis formulation, experimental design, data generation and analysis, and manuscript writing. Although reproducibility and data sharing are increasingly prioritized at the publication stage, integrating these principles at earlier stages of laboratory research has been hampered by the lack of broadly applicable solutions. Here, we propose that the workflow used in modern software development offers a robust framework for enhancing reproducibility and collaboration in laboratory research. In particular, we show that GitHub, a platform widely used for collaborative software projects, can be effectively adapted to organize and document all aspects of a research project's lifecycle in a molecular biology laboratory. We outline a three-step approach for incorporating the GitHub ecosystem into laboratory research workflows: 1. designing and organizing experiments using issues and project boards, 2. documenting experiments and data analyses with a version control system, and 3. ensuring reproducible software environments for data analyses and writing tasks with containerized packages. The versatility, scalability, and affordability of this approach make it suitable for various scenarios, ranging from small research groups to large, cross-institutional collaborations. Adopting this framework from a project's outset can increase the efficiency and fidelity of knowledge transfer within and across research laboratories. An example GitHub repository based on this approach is available at https://github.com/rasilab/github_demo and a template repository that can be copied is available at https://github.com/rasilab/github_template.

Identifiers

PMID39990799
PMCPMC11844616

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.