Really reproducible behavioural paper

• Autorzy: Dzik J.M. , Puscian A. , Harda Z. , Radwanska K. , Leski S.
• Języki publikacji: EN

Abstrakty

EN

INTRODUCTION: The reproducibility of behavioural tests has been improved by the introduction of a number of automated experimental systems. One of such systems is IntelliCage™, which allows for sophisticated experimental designs. Despite the improved reproducibility of experiments, reported results may be rendered irreproducible due to errors introduced by manual data analysis and not standardized reporting of analysis methods. The efficiency of manual analysis is also an issue. AIM(S): Our aim was to facilitate development of automated workflows for reproducible analysis of data yielded by the IntelliCage™ system. METHOD(S): We developed an open source Python library (PyMICE – RRID:nlx_158570) providing IntelliCage™ data as collection of data structures. We have described the library and presented some examples of its use in a paper. According to the literate programming paradigm, the paper was composed of Python and LaTeX snippets. Pweave tool has been used to weave the paper. RESULTS: All analyses contained in our paper “PyMICE – a Python library for analysis of IntelliCage data” (accepted by Behavior Research Methods) are fully reproducible. The source code of the paper (https://github.com/Neuroinflab/PyMICE_SM) does not contain any plots. Instead, they may be easily reproduced by the reader. Also, the correctness of performed analyses may be easily verified. CONCLUSIONS: We propose PyMICE as a common platform for implementing and sharing automated analysis workflows for IntelliCage™ data. The library is a user-friendly tool for analysis of behavioural data in an automated workflow. Such workflow is an unambiguous, formal specification of the performed analysis. The analysis itself may be easily reproduced by simply reapplying the workflow to the same data. Such workflow may be used to perform exactly the same analysis for multiple datasets, e.g. when the same protocol is applied to multiple groups of animals. This is a very common case, as most of experiments have at least one experimental and one control group. FINANCIAL SUPPORT: JD, KR and SŁ supported by a Symfonia NCN grant UMO-2013/08/W/NZ4/00691. AP supported by a grant from Switzerland through the Swiss Contribution to the enlarged European Union (PSPB-210/2010 to Ewelina Knapska and Hans-Peter Lipp). KR and ZH supported by an FNP grant POMOST/2011-4/7 to KR.

• Wydawca: -
• Czasopismo: Acta Neurobiologiae Experimentalis
• Rocznik: 2017
• Tom: 77
• Numer: Suppl.1
• Opis fizyczny: p.134-135

Twórcy

autor

Dzik J.M.

• Laboratory of Neuroinformatics, Department of Neurophysiology, Nencki Institute of Experimental Biology Polish Academy of Sciences, Warsaw, Poland

autor

Puscian A.

• Laboratory of Emotions Neurobiology, Department of Neurophysiology, Nencki Institute of Experimental Biology Polish Academy of Sciences, Warsaw, Poland

autor

Harda Z.

• Laboratory of Molecular Basis of Behavior, Department of Molecular and Cellular Neurobiology, Nencki Institute of Experimental Biology Polish Academy of Sciences, Warsaw, Poland

autor

Radwanska K.

• Laboratory of Molecular Basis of Behavior, Department of Molecular and Cellular Neurobiology, Nencki Institute of Experimental Biology Polish Academy of Sciences, Warsaw, Poland

autor

Leski S.

• Laboratory of Neuroinformatics, Department of Neurophysiology, Nencki Institute of Experimental Biology Polish Academy of Sciences, Warsaw, Poland