Integrated Open-Source Software for Multiscale Electrophysiology

AbstractThe methods for electrophysiology in neuroscience have evolved tremendously over the recent years with a growing emphasis on dense-array signal recordings. Such increased complexity and augmented wealth in the volume of data recorded, have not been accompanied by efforts to streamline and facilitate access to processing methods, which too are susceptible to grow in sophistication. Moreover, unsuccessful attempts to reproduce peer-reviewed publications indicate a problem of transparency in science. This growing problem could be tackled by unrestricted access to methods that promote research transparency and data sharing, ensuring the reproducibility of published results.Here, we provide a free, extensive, open-source software that provides data-analysis, data-management and multi-modality integration solutions for invasive neurophysiology. Users can perform their entire analysis through a user-friendly environment without the need of programming skills, in a tractable (logged) way. This work contributes to open-science, analysis standardization, transparency and reproducibility in invasive neurophysiology.

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Integrated open-source software for multiscale electrophysiology

Scientific Data ◽

10.1038/s41597-019-0242-z ◽

2019 ◽

Vol 6 (1) ◽

Cited By ~ 2

Author(s):

Konstantinos Nasiotis ◽

Martin Cousineau ◽

François Tadel ◽

Adrien Peyrache ◽

Richard M. Leahy ◽

...

Keyword(s):

Data Analysis ◽

Open Source ◽

Open Source Software ◽

Analysis Data ◽

Open Science ◽

Dense Array ◽

Unrestricted Access ◽

Research Transparency ◽

Programming Skills ◽

User Friendly

Abstract The methods for electrophysiology in neuroscience have evolved tremendously over the recent years with a growing emphasis on dense-array signal recordings. Such increased complexity and augmented wealth in the volume of data recorded, have not been accompanied by efforts to streamline and facilitate access to processing methods, which too are susceptible to grow in sophistication. Moreover, unsuccessful attempts to reproduce peer-reviewed publications indicate a problem of transparency in science. This growing problem could be tackled by unrestricted access to methods that promote research transparency and data sharing, ensuring the reproducibility of published results. Here, we provide a free, extensive, open-source software that provides data-analysis, data-management and multi-modality integration solutions for invasive neurophysiology. Users can perform their entire analysis through a user-friendly environment without the need of programming skills, in a tractable (logged) way. This work contributes to open-science, analysis standardization, transparency and reproducibility in invasive neurophysiology.

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Open-source software for mouse-tracking in Qualtrics to measure category competition

10.31219/osf.io/ymxau ◽

2018 ◽

Author(s):

Maya B Mathur ◽

David Reichling

Keyword(s):

Data Collection ◽

Open Source ◽

Real Time ◽

Cognitive Processes ◽

Open Source Software ◽

Online Survey ◽

Mouse Tracking ◽

Crowdsourced Data ◽

Programming Skills ◽

User Friendly

Mouse-tracking is a sophisticated tool for measuring rapid, dynamic cognitive processes in real time, particularly in experiments investigating competition between perceptual or cognitive categories. We provide user-friendly, open-source software (https://osf.io/st2ef/) for designing and analyzing such experiments online using the Qualtrics survey platform. The software consists of a Qualtrics template with embedded Javascript and CSS along with R code to clean, parse, and analyze the data. No special programming skills are required to use this software. As we discuss, this software could be readily modified for use with other online survey platforms that allow the addition of custom Javascript. We empirically validate the provided software by benchmarking its performance on previously tested stimuli in a standard category-competition experiment with realistic crowdsourced data collection.

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Image Processing Filters for Grids of Cells Analogous to Filters Processing Grids of Pixels

Frontiers in Computer Science ◽

10.3389/fcomp.2021.774396 ◽

2021 ◽

Vol 3 ◽

Author(s):

Robert Haase

Keyword(s):

Image Processing ◽

Open Source ◽

Open Source Software ◽

Image Data ◽

Tissue Level ◽

General Purpose ◽

Cellular Processes ◽

Microscopy Image ◽

Programming Skills ◽

User Friendly

Intra- and extra-cellular processes shape tissues together. For understanding how neighborhood relationships between cells play a role in this process, having image processing filters based on these relationships would be beneficial. Those operations are known and their application to microscopy image data typically requires programming skills. User-friendly general purpose tools for pursuing image processing on a level of neighboring cells were yet missing. In this manuscript I demonstrate image processing filters which process grids of cells on tissue level and the analogy to their better known counter parts processing grids of pixels. The tools are available as part of free and open source software in the ImageJ/Fiji and napari ecosystems and their application does not require any programming experience.

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The GenABEL Project for statistical genomics

F1000Research ◽

10.12688/f1000research.8733.1 ◽

2016 ◽

Vol 5 ◽

pp. 914 ◽

Cited By ~ 31

Author(s):

Lennart C. Karssen ◽

Cornelia M. van Duijn ◽

Yurii S. Aulchenko

Keyword(s):

Open Source ◽

Open Source Software ◽

Open Science ◽

Data Sets ◽

Scientific Software ◽

Specific Data ◽

Methodology Development ◽

Statistical Genomics ◽

Web Forum ◽

User Friendly

Development of free/libre open source software is usually done by a community of people with an interest in the tool. For scientific software, however, this is less often the case. Most scientific software is written by only a few authors, often a student working on a thesis. Once the paper describing the tool has been published, the tool is no longer developed further and is left to its own device. Here we describe the broad, multidisciplinary community we formed around a set of tools for statistical genomics. The GenABEL project for statistical omics actively promotes open interdisciplinary development of statistical methodology and its implementation in efficient and user-friendly software under an open source licence. The software tools developed withing the project collectively make up the GenABEL suite, which currently consists of eleven tools. The open framework of the project actively encourages involvement of the community in all stages, from formulation of methodological ideas to application of software to specific data sets. A web forum is used to channel user questions and discussions, further promoting the use of the GenABEL suite. Developer discussions take place on a dedicated mailing list, and development is further supported by robust development practices including use of public version control, code review and continuous integration. Use of this open science model attracts contributions from users and developers outside the “core team”, facilitating agile statistical omics methodology development and fast dissemination.

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Open Plot Project: an open-source toolkit for 3-D structural data analysis

Solid Earth ◽

10.5194/se-2-53-2011 ◽

2011 ◽

Vol 2 (1) ◽

pp. 53-63 ◽

Cited By ~ 18

Author(s):

S. Tavani ◽

P. Arbues ◽

M. Snidero ◽

N. Carrera ◽

J. A. Muñoz

Keyword(s):

Spatial Distribution ◽

Data Analysis ◽

Open Source ◽

Open Source Software ◽

Source Code ◽

Structural Data ◽

Geological Modelling ◽

Analysis Tools ◽

Transect Analysis ◽

Selection Of

Abstract. In this work we present the Open Plot Project, an open-source software for structural data analysis, including a 3-D environment. The software includes many classical functionalities of structural data analysis tools, like stereoplot, contouring, tensorial regression, scatterplots, histograms and transect analysis. In addition, efficient filtering tools are present allowing the selection of data according to their attributes, including spatial distribution and orientation. This first alpha release represents a stand-alone toolkit for structural data analysis. The presence of a 3-D environment with digitalising tools allows the integration of structural data with information extracted from georeferenced images to produce structurally validated dip domains. This, coupled with many import/export facilities, allows easy incorporation of structural analyses in workflows for 3-D geological modelling. Accordingly, Open Plot Project also candidates as a structural add-on for 3-D geological modelling software. The software (for both Windows and Linux O.S.), the User Manual, a set of example movies (complementary to the User Manual), and the source code are provided as Supplement. We intend the publication of the source code to set the foundation for free, public software that, hopefully, the structural geologists' community will use, modify, and implement. The creation of additional public controls/tools is strongly encouraged.

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Conquery: an Open Source Application to analyze High Content Healthcare Data (Preprint)

10.2196/preprints.32745 ◽

2021 ◽

Author(s):

Fabian Kovacs ◽

Max Thonagel ◽

Marion Ludwig ◽

Alexander Albrecht ◽

Manuel Hegner ◽

...

Keyword(s):

Decision Making ◽

Big Data ◽

Data Analysis ◽

Open Source ◽

Open Source Software ◽

Medical Records ◽

Healthcare Sector ◽

Study Cohort ◽

Decision Making Processes ◽

Analytical Approaches

BACKGROUND Big data in healthcare must be exploited to achieve a substantial increase in efficiency and competitiveness. Especially the analysis of patient-related data possesses huge potential to improve decision-making processes. However, most analytical approaches used today are highly time- and resource-consuming. OBJECTIVE The presented software solution Conquery is an open-source software tool providing advanced, but intuitive data analysis without the need for specialized statistical training. Conquery aims to simplify big data analysis for novice database users in the medical sector. METHODS Conquery is a document-oriented distributed timeseries database and analysis platform. Its main application is the analysis of per-person medical records by non-technical medical professionals. Complex analyses are realized in the Conquery frontend by dragging tree nodes into the query editor. Queries are evaluated by a bespoke distributed query-engine for medical records in a column-oriented fashion. We present a custom compression scheme to facilitate low response times that uses online calculated as well as precomputed metadata and data statistics. RESULTS Conquery allows for easy navigation through the hierarchy and enables complex study cohort construction whilst reducing the demand on time and resources. The UI of Conquery and a query output is exemplified by the construction of a relevant clinical cohort. CONCLUSIONS Conquery is an efficient and intuitive open-source software for performant and secure data analysis and aims at supporting decision-making processes in the healthcare sector.

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