Browse
Submit Data
Databases
API
Help

Dataset Information

28 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Rapid computation and visualization of data from Kano surveys in R.

ABSTRACT:

Objective

The Kano model for user satisfaction is a popular survey-based method used by product designers to prioritize the inclusion and implementation of product features based on users' requirements. Despite its overall simplicity, a current drawback of the Kano approach is that the data analysis and processing of users' responses is laborsome and rather prone to human error. To address this drawback, this paper provides and presents a complete code to conduct a rapid yet comprehensive computation and visualization of Kano data in R.

Results

A detailed walkthrough of the code is provided, together with a sample dataset to demonstrate its functionality. The code is encapsulated on a simple function that can substantially decrease the time for evaluating Kano results, speeding up its application in the context of product development.

SUBMITTER: Atlason RS

PROVIDER: S-EPMC6263047 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Rapid computation and visualization of data from Kano surveys in R.

Atlason Reynir S RS Giacalone Davide D

BMC research notes 20181128 1

<h4>Objective</h4>The Kano model for user satisfaction is a popular survey-based method used by product designers to prioritize the inclusion and implementation of product features based on users' requirements. Despite its overall simplicity, a current drawback of the Kano approach is that the data analysis and processing of users' responses is laborsome and rather prone to human error. To address this drawback, this paper provides and presents a complete code to conduct a rapid yet comprehensiv ...[more]

PMID: 30486860

Similar Datasets

Instant Feedback Rapid Prototyping for GPU-Accelerated Computation, Manipulation, and Visualization of Multidimensional Data.

Project description:ObjectiveWe have created an open-source application and framework for rapid GPU-accelerated prototyping, targeting image analysis, including volumetric images such as CT or MRI data.MethodsA visual graph editor enables the design of processing pipelines without programming. Run-time compiled compute shaders enable prototyping of complex operations in a matter of minutes.ResultsGPU-acceleration increases processing the speed by at least an order of magnitude when compared to traditional multithreaded CPU-based implementations, while offering the flexibility of scripted implementations.ConclusionOur framework enables real-time, intuition-guided accelerated algorithm and method development, supported by built-in scriptable visualization.SignificanceThis is, to our knowledge, the first tool for medical data analysis that provides both high performance and rapid prototyping. As such, it has the potential to act as a force multiplier for further research, enabling handling of high-resolution datasets while providing quasi-instant feedback and visualization of results.

| S-EPMC6008673 | biostudies-literature

Sensitivity analysis of agent-based simulation utilizing massively parallel computation and interactive data visualization.

Project description:An essential step in the analysis of agent-based simulation is sensitivity analysis, which namely examines the dependency of parameter values on simulation results. Although a number of approaches have been proposed for sensitivity analysis, they still have limitations in exhaustivity and interpretability. In this study, we propose a novel methodology for sensitivity analysis of agent-based simulation, MASSIVE (Massively parallel Agent-based Simulations and Subsequent Interactive Visualization-based Exploration). MASSIVE takes a unique paradigm, which is completely different from those of sensitivity analysis methods developed so far, By combining massively parallel computation and interactive data visualization, MASSIVE enables us to inspect a broad parameter space intuitively. We demonstrated the utility of MASSIVE by its application to cancer evolution simulation, which successfully identified conditions that generate heterogeneous tumors. We believe that our approach would be a de facto standard for sensitivity analysis of agent-based simulation in an era of evergrowing computational technology. All the results form our MASSIVE analysis are available at https://www.hgc.jp/~niiyan/massive.

| S-EPMC6400389 | biostudies-literature

Computation and visualization of cell-cell signaling topologies in single-cell systems data using Connectome.

Project description:Single-cell RNA-sequencing data has revolutionized our ability to understand of the patterns of cell-cell and ligand-receptor connectivity that influence the function of tissues and organs. However, the quantification and visualization of these patterns in a way that informs tissue biology are major computational and epistemological challenges. Here, we present Connectome, a software package for R which facilitates rapid calculation and interactive exploration of cell-cell signaling network topologies contained in single-cell RNA-sequencing data. Connectome can be used with any reference set of known ligand-receptor mechanisms. It has built-in functionality to facilitate differential and comparative connectomics, in which signaling networks are compared between tissue systems. Connectome focuses on computational and graphical tools designed to analyze and explore cell-cell connectivity patterns across disparate single-cell datasets and reveal biologic insight. We present approaches to quantify focused network topologies and discuss some of the biologic theory leading to their design.

| S-EPMC8906120 | biostudies-literature

VASCo: computation and visualization of annotated protein surface contacts.

Project description:BACKGROUND:Structural data from crystallographic analyses contain a vast amount of information on protein-protein contacts. Knowledge on protein-protein interactions is essential for understanding many processes in living cells. The methods to investigate these interactions range from genetics to biophysics, crystallography, bioinformatics and computer modeling. Also crystal contact information can be useful to understand biologically relevant protein oligomerisation as they rely in principle on the same physico-chemical interaction forces. Visualization of crystal and biological contact data including different surface properties can help to analyse protein-protein interactions. RESULTS:VASCo is a program package for the calculation of protein surface properties and the visualization of annotated surfaces. Special emphasis is laid on protein-protein interactions, which are calculated based on surface point distances. The same approach is used to compare surfaces of two aligned molecules. Molecular properties such as electrostatic potential or hydrophobicity are mapped onto these surface points. Molecular surfaces and the corresponding properties are calculated using well established programs integrated into the package, as well as using custom developed programs. The modular package can easily be extended to include new properties for annotation. The output of the program is most conveniently displayed in PyMOL using a custom-made plug-in. CONCLUSION:VASCo supplements other available protein contact visualisation tools and provides additional information on biological interactions as well as on crystal contacts. The tool provides a unique feature to compare surfaces of two aligned molecules based on point distances and thereby facilitates the visualization and analysis of surface differences.

| S-EPMC2649047 | biostudies-literature

Molecular Perception for Visualization and Computation: The Proxima Library.

Project description:Proxima is a molecular perception library designed with a double purpose: to be used with immersive molecular viewers (thus providing any required feature not supported by third party libraries) and to be integrated in workflow managers thus providing the functionalities needed for the first steps of molecular modeling studies. It thus stands at the boundary between visualization and computation. The purpose of the present article is to provide a general introduction to the first release of Proxima, describe its most significant features, and highlight its performance by means of some case studies. The current version of Proxima is available for evaluation purposes at https://bitbucket.org/sns-smartlab/proxima/src/master/.

| S-EPMC7997373 | biostudies-literature

ChimericFragments: computation, analysis and visualization of global RNA networks

Project description: Not available

| S-EPMC11023125 | biostudies-literature

Genome2D: a visualization tool for the rapid analysis of bacterial transcriptome data.

Project description:Genome2D is a Windows-based software tool for visualization of bacterial transcriptome and customized datasets on linear chromosome maps constructed from annotated genome sequences. Genome2D facilitates the analysis of transcriptome data by using different color ranges to depict differences in gene-expression levels on a genome map. Such output format enables visual inspection of the transcriptome data, and will quickly reveal transcriptional units, without prior knowledge of expression level cutoff values. The compiled version of Genome2D is freely available for academic or non-profit use from http://molgen.biol.rug.nl/molgen/research/molgensoftware.php.

| S-EPMC416473 | biostudies-literature

Dynamic Visualization and Fast Computation for Convex Clustering via Algorithmic Regularization.

Project description:Convex clustering is a promising new approach to the classical problem of clustering, combining strong performance in empirical studies with rigorous theoretical foundations. Despite these advantages, convex clustering has not been widely adopted, due to its computationally intensive nature and its lack of compelling visualizations. To address these impediments, we introduce Algorithmic Regularization, an innovative technique for obtaining high-quality estimates of regularization paths using an iterative one-step approximation scheme. We justify our approach with a novel theoretical result, guaranteeing global convergence of the approximate path to the exact solution under easily-checked non-data-dependent assumptions. The application of algorithmic regularization to convex clustering yields the Convex Clustering via Algorithmic Regularization Paths (CARP) algorithm for computing the clustering solution path. On example data sets from genomics and text analysis, CARP delivers over a 100-fold speed-up over existing methods, while attaining a finer approximation grid than standard methods. Furthermore, CARP enables improved visualization of clustering solutions: the fine solution grid returned by CARP can be used to construct a convex clustering-based dendrogram, as well as forming the basis of a dynamic path-wise visualization based on modern web technologies. Our methods are implemented in the open-source R package clustRviz, available at https://github.com/DataSlingers/clustRviz.

| S-EPMC7518335 | biostudies-literature

Interactive computation and visualization of deep brain stimulation effects using Duality.

Project description:Deep brain stimulation (DBS) is an established treatment for movement disorders such as Parkinson's disease or essential tremor. Currently, the selection of optimal stimulation settings is performed by iteratively adjusting the stimulation parameters and is a time consuming procedure that requires multiple clinic visits of several hours. Recently, computational models to predict and visualize the effect of DBS have been developed with the goal to simplify and accelerate this procedure by providing visual guidance and such models have been made available also on mobile devices. However, currently available visualization software still either lacks mobility, i.e., it is running on desktop computers and not easily available in clinical praxis, or flexibility, as the simulations that are visualized on mobile devices have to be precomputed. The goal of the pipeline presented in this paper is to close this gap: Using Duality, a newly developed software for the interactive visualization of simulation results, we implemented a pipeline that allows to compute DBS simulations in near-real time and instantaneously visualize the result on a tablet computer. Therefore, a client-server setup is used, so that the visualization and user interaction occur on the tablet computer, while the computations are carried out on a remote server. We present two examples for the use of Duality, one for postoperative programming and one for the planning of DBS surgery in a pre- or intraoperative setting. We carry out a performance analysis and present the results of a case study in which the pipeline for postoperative programming was applied.

| S-EPMC7394461 | biostudies-literature

netgsa: Fast computation and interactive visualization for topology-based pathway enrichment analysis.

Project description:Existing software tools for topology-based pathway enrichment analysis are either computationally inefficient, have undesirable statistical power, or require expert knowledge to leverage the methods' capabilities. To address these limitations, we have overhauled NetGSA, an existing topology-based method, to provide a computationally-efficient user-friendly tool that offers interactive visualization. Pathway enrichment analysis for thousands of genes can be performed in minutes on a personal computer without sacrificing statistical power. The new software also removes the need for expert knowledge by directly curating gene-gene interaction information from multiple external databases. Lastly, by utilizing the capabilities of Cytoscape, the new software also offers interactive and intuitive network visualization.

| S-EPMC8221786 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data