Population Health and Reproduction, University of California Davis, 1 Shields Ave., Davis, CA, 95616, USA.
Biology Department, Woods Hole Oceanographic Institution, 266 Woods Hole Rd., Woods Hole, MA, 02543, USA.
Gigascience. 2019 Feb 1;8(2):giy159. doi: 10.1093/gigascience/giy159.
DNA sequencing technology has revolutionized the field of biology, shifting biology from a data-limited to data-rich state. Central to the interpretation of sequencing data are the computational tools and approaches that convert raw data into biologically meaningful information. Both the tools and the generation of data are actively evolving, yet the practice of re-analysis of previously generated data with new tools is not commonplace. Re-analysis of existing data provides an affordable means of generating new information and will likely become more routine within biology, yet necessitates a new set of considerations for best practices and resource development. Here, we discuss several practices that we believe to be broadly applicable when re-analyzing data, especially when done by small research groups.
DNA 测序技术彻底改变了生物学领域，使生物学从数据有限的状态转变为数据丰富的状态。解释测序数据的核心是将原始数据转化为有生物学意义的信息的计算工具和方法。工具和数据的产生都在积极发展，但用新工具重新分析以前生成的数据的做法并不常见。对现有数据进行重新分析是生成新信息的一种经济实惠的手段，并且在生物学领域中可能会变得更加常规，但需要为最佳实践和资源开发考虑一组新的因素。在这里，我们讨论了一些我们认为在重新分析数据时特别适用于小型研究小组的实践。
