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Biobank for Translational Medicine: Standard Operating Procedures for Optimal Sample Management

Biobank for Translational Medicine: Standard Operating Procedures for Optimal Sample Management

Published on: November 30, 2022

Analytical code sharing practices in biomedical research.

Nitesh Kumar Sharma¹, Ram Ayyala², Dhrithi Deshpande¹

¹Titus Family Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, 1540 Alcazar Street, Los Angeles, CA 90033, USA.

Biorxiv : the Preprint Server for Biology

|August 23, 2023

Summary

This summary is machine-generated.

Most biomedical studies lack reproducible research outputs like code and data. Enhancing code sharing practices is crucial for scientific transparency and accelerating discoveries.

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Area of Science:

Biomedical Research
Computational Biology
Data Science

Background:

The increasing volume of data in biomedical research necessitates robust computational analysis.
Lack of shared research outputs (data, code, methods) hinders study transparency and reproducibility.
Many published studies are not reproducible due to insufficient sharing of documentation, code, and data.

Approach:

A comprehensive analysis of 453 biomedical manuscripts published between 2016-2021 was conducted.
The study assessed the availability and organization of analytical code and other research outputs.
Statistical associations between code availability statements, types of analyses, and code sharing were examined.

Key Points:

50.1% of analyzed manuscripts failed to share analytical code.
Among studies sharing code, most did not share additional outputs like data.
Only 10% of papers organized their code in a structured, reproducible manner.
Code availability statements significantly correlate with increased code sharing (p=2.71×10^-9).
Secondary analyses were more likely to share code than primary analyses (p=1.15*10^-07).

Conclusions:

Immediate steps are needed to enhance code availability and improve reproducibility in biomedical research.
Prioritizing open science practices, including sharing code and data, is essential for scientific rigor and collaboration.
Increased transparency and reproducibility will accelerate scientific discoveries and enable the scientific community to build upon existing research.