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Balancing sufficiency and impact in reporting standards for mass spectrometry imaging experiments

期刊

GIGASCIENCE
卷 7, 期 10, 页码 -

出版社

OXFORD UNIV PRESS
DOI: 10.1093/gigascience/giy102

关键词

mass spectrometry; imaging; reporting; standard

资金

  1. Australian Research Council (ARC) Centre of Excellence for Convergent Bio-Nano Science AMP
  2. Technology (CBNS, ARC Project) [CE140100036]
  3. Bioplatforms Australia (Australian Government)
  4. ARC [DE160101142]

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Reproducibility, or a lack thereof, is an increasingly important topic across many research fields. A key aspect of reproducibility is accurate reporting of both experiments and the resulting data. Herein, we propose a reporting guideline for mass spectrometry imaging (MSI). Previous standards have laid out guidelines sufficient to guarantee a certain quality of reporting; however, they set a high bar and as a consequence can be exhaustive and broad, thus limiting uptake. To help address this lack of uptake, we propose a reporting supplement-Minimum Information About a Mass Spectrometry Imaging Experiment (MIAMSIE)-and its abbreviated reporting standard version, MSIcheck. MIAMSIE is intended to improve author-driven reporting. It is intentionally not exhaustive, but is rather designed for extensibility and could therefore eventually become analogous to existing standards that aim to guarantee reporting quality. Conversely, its abbreviated form MSIcheck is intended as a diagnostic tool focused on key aspects in MSI reporting. We discuss how existing standards influenced MIAMSIE/MSIcheck and how these new approaches could positively impact reporting quality, followed by test implementation of both standards to demonstrate their use. For MIAMSIE, we report on author reviews of four articles and a dataset. For MSIcheck, we show a snapshot review of a one-month subset of the MSI literature that indicated issues with data provision and the reporting of both data analysis steps and calibration settings for MS systems. Although our contribution is MSI specific, we believe the underlying approach could be considered as a general strategy for improving scientific reporting.

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