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Independent computational reproducibility of scientific results is rapidlybecoming of pivotal importance in scientific progress as computation itselfplays a more and more central role in so many branches of science.Historically, reproducibility has followed the familiar Popperian [38] modelwhereby theory cannot be verified by scientific testing, it can only befalsified. Ultimately, this implies that if an experiment cannot be reproducedindependently to some satisfactory level of precision, its value is essentiallyunquantifiable; put brutally, it is impossible to determine its scientificvalue. The burgeoning presence of software in most scientific work adds a newand particularly opaque layer of complexity [29]. In spite of much recentinterest in many scientific areas, emphasis remains more on procedures,strictures and discussion [12, 14, 16, 29, 30, 37, 41], reflecting theinexperience of most scientific journals when it comes to software, rather thanthe details of how computational reproducibility is actually achieved, forwhich there appear to be relatively few guiding examples [6, 10, 17]. Afterconsidering basic principles, here we show how full computationalreproducibility can be achieved in practice at every stage using a case studyof a multi-gigabyte protein study on the open SwissProt protein database, fromdata download all the way to individual figure by figure reproduction as anexemplar for general scientific computation.

Full Computational Reproducibility in Biological Science: Methods, Software and a Case Study in Protein Biology