TY - JOUR
T1 - Pynapple, a toolbox for data analysis in neuroscience
AU - Viejo, Guillaume
AU - Levenstein, Daniel
AU - Carrasco, Sofia Skromne
AU - Mehrotra, Dhruv
AU - Mahallati, Sara
AU - Vite, Gilberto R.
AU - Denny, Henry
AU - Sjulson, Lucas
AU - Battaglia, Francesco P.
AU - Peyrache, Adrien
N1 - Publisher Copyright:
© 2023, eLife Sciences Publications Ltd. All rights reserved.
PY - 2023
Y1 - 2023
N2 - Datasets collected in neuroscientific studies are of ever-growing complexity, often combining high-dimensional time series data from multiple data acquisition modalities. Handling and manipulating these various data streams in an adequate programming environment is crucial to ensure reliable analysis, and to facilitate sharing of reproducible analysis pipelines. Here, we present Pynapple, the PYthon Neural Analysis Package, a lightweight python package designed to process a broad range of time-resolved data in systems neuroscience. The core feature of this package is a small number of versatile objects that support the manipulation of any data streams and task parameters. The package includes a set of methods to read common data formats and allows users to easily write their own. The resulting code is easy to read and write, avoids low-level data processing and other error-prone steps, and is open source. Libraries for higher-level analyses are developed within the Pynapple framework but are contained within a collaborative repository of specialized and continuously updated analysis routines. This provides flexibility while ensuring long-term stability of the core package. In conclusion, Pynapple provides a common framework for data analysis in neuroscience.
AB - Datasets collected in neuroscientific studies are of ever-growing complexity, often combining high-dimensional time series data from multiple data acquisition modalities. Handling and manipulating these various data streams in an adequate programming environment is crucial to ensure reliable analysis, and to facilitate sharing of reproducible analysis pipelines. Here, we present Pynapple, the PYthon Neural Analysis Package, a lightweight python package designed to process a broad range of time-resolved data in systems neuroscience. The core feature of this package is a small number of versatile objects that support the manipulation of any data streams and task parameters. The package includes a set of methods to read common data formats and allows users to easily write their own. The resulting code is easy to read and write, avoids low-level data processing and other error-prone steps, and is open source. Libraries for higher-level analyses are developed within the Pynapple framework but are contained within a collaborative repository of specialized and continuously updated analysis routines. This provides flexibility while ensuring long-term stability of the core package. In conclusion, Pynapple provides a common framework for data analysis in neuroscience.
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U2 - 10.7554/eLife.85786
DO - 10.7554/eLife.85786
M3 - Article
C2 - 37843985
AN - SCOPUS:85174454316
SN - 2050-084X
VL - 12
JO - eLife
JF - eLife
ER -