Abstract Number: PB0747
Meeting: ISTH 2020 Congress
Background: Scientists are widely concerned about the ‘crisis of reproducibility’ and proposed solutions include standardised, open and freely shared analytical software. Many methods used in haemostasis involve specialist equipment and inaccessible software for data collection and analysis, while in-house methods may lack traceability or be difficult to transfer.
Aims: To develop open source software tools that are freely available to use online to enhance reproducibility of analysis within and between haemostasis laboratories.
Methods: Online apps were developed using the statistical programming language R, in combination with the ‘Shiny’ add-on package that can be run through a computer browser to help analysis of user data from haemostasis assays.
Results: Spectrophotometric time courses of clotting and lysis using clots made from purified components or plasma are common in haemostasis work but extracting parameters from these curves is not trivial. The ‘Clotlysis’ app streamlines curve fitting and calculation of times to % clotting or lysis, absorbance values and first derivatives (Fig.1). Results can also be readily explored using heatmaps or scatter plots (e.g. Fig 2). All critical settings for baselines and interpolation are recorded to promote reproducible analysis. Similar apps are available to analyse chromogenic assays (e.g. zymogen activation with automated time squared calculations), fibrinolytic halo assays, clotting assays, D-dimer test positive and negative predictive values, and thrombin generation assays. More details and links are available at https://drclongstaff.github.io/shiny-clots/. Code can be downloaded from Github.
Conclusions: NIBSC organises global collaborative studies on behalf of WHO and the SSC/ISTH. We observe that analysis of the same data by participating labs or centrally by NIBSC can produce different results. Our recent experience making reference preparations for ancrod, batroxobin, streptokinase and thrombin shows that this source of variability can be reduced by using shared, standardised software. Data analysis is speeded up and simplified, while reproducibility is facilitated.
To cite this abstract in AMA style:Longstaff C, Locke M. Online Apps Improve Haemostasis Assay Reproducibility and Facilitate Open Data and Code Sharing [abstract]. Res Pract Thromb Haemost. 2020; 4 (Suppl 1). https://abstracts.isth.org/abstract/online-apps-improve-haemostasis-assay-reproducibility-and-facilitate-open-data-and-code-sharing/. Accessed January 28, 2022.
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