An often overlooked source of the “replication crisis” is the tendency to treat the replication study as a definitive verdict while ignoring the statistical uncertainty inherent in both the original and replication studies. This simplistic view fosters misleading dichotomies and erodes public trust in science.

There may be hundreds of papers out there reporting on experimental results in cell lines that do not actually exist.

A few years ago, I came across a cartoon that seemed to capture a particular aspect of scholarly journal publishing quite well: The academic journal publishing system sure feels all too often a bit like a sinking boat.

Throughout the Epiverse project, we use the renv R package to ensure reproducibility of the training materials and the pipelines we are providing. But we sometimes get reports from users who struggle to rebuild the environment and run the code. In this post, we dissect the source of these issues, explain why in reality renv is not at fault, and how this is caused by the inherent complexity of reproducibility.

The Unified Medical Language System (UMLS) is a widely used biomedical and clinical vocabulary maintained by the United States National Library of Medicine. However, it is notoriously difficult to access and work with due to licensing restrictions and its complex download system. In the same vein as my previous posts about DrugBank and ChEMBL, this post describes open source software I’ve developed for downloading and working with this data.

I’ve been working on improving reproducibility in the field of cheminformatics for some time now. For example, I’ve written posts about making data from DrugBank and ChEMBL more actionable. Over the last year, I’ve been preparing a concept with the editors of the Journal of Cheminformatics on how to include an assessment of reproducibility to reviews of manuscripts submitted to the journal.

At GigaScience we see more and more of our published papers use computational workflows, as they provides researchers easy access to high-quality analysis methods without the requirement of computational expertise. However, systems are needed to enable the sharing of these workflows in a reusable form.

Frictionless Data improves not just machine readability of scientific articles, but also enables humans to directly interact with the data within the article itself.

What is renv RStudio’s renv package is a powerful dependency management toolkit for R. It allows you to create a lockfile that records the exact versions of R packages used in a given project, and provides tooling to install exactly those same versions on another machine, or at a later point in time. This is very useful to create an isolated project environment for reproducibility or production purposes.

I teach R to a lot of scientists, those that are new to science (i.e. students)as well as more established scientists, new to R.I find that after all their struggles of dealing with dates,or remembering where to put the comma, they’re so grateful to actual have an analysis,that they often forget or aren’t aware of the next steps.