Analytical code sharing practices in biomedical research

Authors : Nitesh Kumar Sharma, Ram Ayyala, Dhrithi Deshpande et al.

Data-driven computational analysis is becoming increasingly important in biomedical research, as the amount of data being generated continues to grow. However, the lack of practices of sharing research outputs, such as data, source code and methods, affects transparency and reproducibility of studies, which are critical to the advancement of science. Many published studies are not reproducible due to insufficient documentation, code, and data being shared.

We conducted a comprehensive analysis of 453 manuscripts published between 2016-2021 and found that 50.1% of them fail to share the analytical code. Even among those that did disclose their code, a vast majority failed to offer additional research outputs, such as data. Furthermore, only one in ten papers organized their code in a structured and reproducible manner. We discovered a significant association between the presence of code availability statements and increased code availability (p=2.71×10−9).

Additionally, a greater proportion of studies conducting secondary analyses were inclined to share their code compared to those conducting primary analyses (p=1.15*10−07). In light of our findings, we propose raising awareness of code sharing practices and taking immediate steps to enhance code availability to improve reproducibility in biomedical research.

By increasing transparency and reproducibility, we can promote scientific rigor, encourage collaboration, and accelerate scientific discoveries. We must prioritize open science practices, including sharing code, data, and other research products, to ensure that biomedical research can be replicated and built upon by others in the scientific community.

URL : Analytical code sharing practices in biomedical research

DOI : https://doi.org/10.1101/2023.07.31.551384

Low availability of code in ecology: A call for urgent action

Authors : Antica Culina, Ilona van den Berg, Simon Evans, Alfredo Sánchez-Tójar

Access to analytical code is essential for transparent and reproducible research. We review the state of code availability in ecology using a random sample of 346 nonmolecular articles published between 2015 and 2019 under mandatory or encouraged code-sharing policies.

Our results call for urgent action to increase code availability: only 27% of eligible articles were accompanied by code. In contrast, data were available for 79% of eligible articles, highlighting that code availability is an important limiting factor for computational reproducibility in ecology.

Although the percentage of ecological journals with mandatory or encouraged code-sharing policies has increased considerably, from 15% in 2015 to 75% in 2020, our results show that code-sharing policies are not adhered to by most authors.

We hope these results will encourage journals, institutions, funding agencies, and researchers to address this alarming situation.

URL : Low availability of code in ecology: A call for urgent action

DOI : https://doi.org/10.1371/journal.pbio.3000763