Presentation Title
Degree Name
Master of Computer Science and Systems (MCSS)
Department
Institute of Technology
Location
Carwein Auditorium (KEY 102), UW Tacoma
Event Website
http://guides.lib.uw.edu/tactalks
Start Date
19-5-2016 5:30 PM
End Date
19-5-2016 5:35 PM
Abstract
Reproducibility is vital in science. Recent articles in the June 26 issue of science discussed how rarely published results can be reproduced across different disciplines. Nosek and colleagues proposed guidelines consisting of eight standards and three levels to promote transparency, openness and reproducibility in scientific publications. These suggestions overlook the fact that modern biomedical workflows and pipelines consist of multiple applications and libraries, each with their own set of software dependencies.
For complex computational methods, it is often necessary not just to recreate the code but also the software and hardware environment to reproduce results. Virtual machines (VM), and container software (a lightweight solution for VM) such as Docker, make it possible to reproduce the exact environment regardless of the underlying hardware and operating system. However, workflows that use Graphical User Interfaces (GUIs) remain difficult to replicate on different host systems as there is no high level graphical software layer common to all platforms.
As proof of concept, we present a Docker package, called GUIdock, that contains a Bioconductor application written in R and C++ called networkBMA for gene network inference. GUIdock uses Docker, an open source project that provides a container with only the absolutely necessary software dependencies, and configures a common X Windows (X11) graphic interface on Linux, Macintosh, and Windows platforms.
Our package also includes Cytoscape, a Java-based platform with a graphical user interface for visualizing and analyzing gene networks, and the CyNetworkBMA app, a Cytoscape app that allows the use of networkBMA via the user-friendly Cytoscape interface. Complex graphics-based workflows, ubiquitous in systems biology, can now be easily exported and reproduced on many different platforms.
COinS
GUIdock: Using Docker Containers with a Common Graphics User Interface to Address the Reproducibility of Research
Carwein Auditorium (KEY 102), UW Tacoma
Reproducibility is vital in science. Recent articles in the June 26 issue of science discussed how rarely published results can be reproduced across different disciplines. Nosek and colleagues proposed guidelines consisting of eight standards and three levels to promote transparency, openness and reproducibility in scientific publications. These suggestions overlook the fact that modern biomedical workflows and pipelines consist of multiple applications and libraries, each with their own set of software dependencies.
For complex computational methods, it is often necessary not just to recreate the code but also the software and hardware environment to reproduce results. Virtual machines (VM), and container software (a lightweight solution for VM) such as Docker, make it possible to reproduce the exact environment regardless of the underlying hardware and operating system. However, workflows that use Graphical User Interfaces (GUIs) remain difficult to replicate on different host systems as there is no high level graphical software layer common to all platforms.
As proof of concept, we present a Docker package, called GUIdock, that contains a Bioconductor application written in R and C++ called networkBMA for gene network inference. GUIdock uses Docker, an open source project that provides a container with only the absolutely necessary software dependencies, and configures a common X Windows (X11) graphic interface on Linux, Macintosh, and Windows platforms.
Our package also includes Cytoscape, a Java-based platform with a graphical user interface for visualizing and analyzing gene networks, and the CyNetworkBMA app, a Cytoscape app that allows the use of networkBMA via the user-friendly Cytoscape interface. Complex graphics-based workflows, ubiquitous in systems biology, can now be easily exported and reproduced on many different platforms.
https://digitalcommons.tacoma.uw.edu/tactalks/2016/spring/11