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A large sample size, or N, increases the sensitivity of an experiment to detect differences between treatment groups. However, the biological entity that N refers to may not be obvious. Defining the wrong entity can inflate the sample size and increase both false-positive and false-negative results.
Orphan drug development is a rapidly expanding field. Nevertheless, clinical trials for rare diseases can present inherent challenges. Optimal study design and partnerships between academia and industry are therefore required for the successful development, delivery and clinical approval of effective therapies in this group of disorders.
Automated single-particle picking in electron cryo-microscopy data has seen important advances in the past couple of years and now enables computer-assisted particle selection even for challenging datasets. These advances have implications for streamlined and automated image processing, with potential benefits for improving the resolution of resulting structures.
Ensuring reproducibility and replicability has been an issue in many scientific disciplines in the past decade. Here, we discuss another ‘R’ that has not gotten enough airtime — reanalysis. We cover how open science and a focus on enabling reanalysis also make the goals of reproducibility and replicability easier to achieve.
As Nature Reviews Methods Primers publishes its first articles, the editors outline the journal’s aims and scope and our contribution to the pursuit of reproducibility.