scholarly journals StatAid: An R package with a graphical user interface for data analysis

2020 ◽  
Vol 5 (54) ◽  
pp. 2630
Author(s):  
Vincent Alcazer
Keyword(s):  
Data Analysis ◽  
User Interface ◽  
Graphical User Interface ◽  
R Package

scholarly journals CIPR: a web-based R/shiny app and R package to annotate cell clusters in single cell RNA sequencing experiments

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
H. Atakan Ekiz ◽  
Christopher J. Conley ◽  
W. Zac Stephens ◽  
Ryan M. O’Connell
Keyword(s):  
Data Analysis ◽  
User Interface ◽  
Single Cell ◽  
Graphical User Interface ◽  
R Package ◽  
Web Based ◽  
Cell Clusters ◽  
Shiny App ◽  
Single Cell Rna Sequencing ◽  
R Shiny

Abstract Background Single cell RNA sequencing (scRNAseq) has provided invaluable insights into cellular heterogeneity and functional states in health and disease. During the analysis of scRNAseq data, annotating the biological identity of cell clusters is an important step before downstream analyses and it remains technically challenging. The current solutions for annotating single cell clusters generally lack a graphical user interface, can be computationally intensive or have a limited scope. On the other hand, manually annotating single cell clusters by examining the expression of marker genes can be subjective and labor-intensive. To improve the quality and efficiency of annotating cell clusters in scRNAseq data, we present a web-based R/Shiny app and R package, Cluster Identity PRedictor (CIPR), which provides a graphical user interface to quickly score gene expression profiles of unknown cell clusters against mouse or human references, or a custom dataset provided by the user. CIPR can be easily integrated into the current pipelines to facilitate scRNAseq data analysis. Results CIPR employs multiple approaches for calculating the identity score at the cluster level and can accept inputs generated by popular scRNAseq analysis software. CIPR provides 2 mouse and 5 human reference datasets, and its pipeline allows inter-species comparisons and the ability to upload a custom reference dataset for specialized studies. The option to filter out lowly variable genes and to exclude irrelevant reference cell subsets from the analysis can improve the discriminatory power of CIPR suggesting that it can be tailored to different experimental contexts. Benchmarking CIPR against existing functionally similar software revealed that our algorithm is less computationally demanding, it performs significantly faster and provides accurate predictions for multiple cell clusters in a scRNAseq experiment involving tumor-infiltrating immune cells. Conclusions CIPR facilitates scRNAseq data analysis by annotating unknown cell clusters in an objective and efficient manner. Platform independence owing to Shiny framework and the requirement for a minimal programming experience allows this software to be used by researchers from different backgrounds. CIPR can accurately predict the identity of a variety of cell clusters and can be used in various experimental contexts across a broad spectrum of research areas.

EosFit7-GUI: a new graphical user interface for equation of state calculations, analyses and teaching

2016 ◽  
Vol 49 (4) ◽  
pp. 1377-1382 ◽  
Author(s):  
Javier Gonzalez-Platas ◽  
Matteo Alvaro ◽  
Fabrizio Nestola ◽  
Ross Angel
Keyword(s):  
Thermal Expansion ◽  
Data Analysis ◽  
User Interface ◽  
Equation Of State ◽  
Least Squares ◽  
Graphical User Interface ◽  
Diffraction Data ◽  
Equations Of State ◽  
Least Squares Fitting ◽  
Parametric Data

EosFit7-GUIis a full graphical user interface designed to simplify the analysis of thermal expansion and equations of state (EoSs). The software allows users to easily perform least-squares fitting of EoS parameters to diffraction data collected as a function of varying pressure, temperature or both. It has been especially designed to allow rapid graphical evaluation of both parametric data and the EoS fitted to the data, making it useful both for data analysis and for teaching.

scholarly journals LexOPS: An R package and user interface for the controlled generation of word stimuli

2020 ◽  
Vol 52 (6) ◽  
pp. 2372-2382
Author(s):  
Jack E. Taylor ◽  
Alistair Beith ◽  
Sara C. Sereno
Keyword(s):  
User Interface ◽  
Factorial Design ◽  
Graphical User Interface ◽  
R Package ◽  
Psycholinguistic Research ◽  
Link Type ◽  
Control Current ◽  
Word Lists ◽  
And Control ◽  
Manipulation And Control

AbstractLexOPS is an R package and user interface designed to facilitate the generation of word stimuli for use in research. Notably, the tool permits the generation of suitably controlled word lists for any user-specified factorial design and can be adapted for use with any language. It features an intuitive graphical user interface, including the visualization of both the distributions within and relationships among variables of interest. An inbuilt database of English words is also provided, including a range of lexical variables commonly used in psycholinguistic research. This article introduces LexOPS, outlining the features of the package and detailing the sources of the inbuilt dataset. We also report a validation analysis, showing that, in comparison to stimuli of existing studies, stimuli optimized with LexOPS generally demonstrate greater constraint and consistency in variable manipulation and control. Current instructions for installing and using LexOPS are available at https://JackEdTaylor.github.io/LexOPSdocs/.

scholarly journals ntbox : An r package with graphical user interface for modelling and evaluating multidimensional ecological niches

2020 ◽  
Vol 11 (10) ◽  
pp. 1199-1206 ◽  
Author(s):  
Luis Osorio‐Olvera ◽  
Andrés Lira‐Noriega ◽  
Jorge Soberón ◽  
Andrew Townsend Peterson ◽  
Manuel Falconi ◽  
...  
Keyword(s):  
User Interface ◽  
Graphical User Interface ◽  
R Package ◽  
Ecological Niches

scholarly journals genBaRcode: a comprehensive R-package for genetic barcode analysis

2019 ◽  
Vol 36 (7) ◽  
pp. 2189-2194 ◽  
Author(s):  
Lars Thielecke ◽  
Kerstin Cornils ◽  
Ingmar Glauche
Keyword(s):  
User Interface ◽  
Next Generation Sequencing ◽  
Error Correction ◽  
Graphical User Interface ◽  
R Package ◽  
Next Generation ◽  
Analysis Strategies ◽  
Genetic Sequences ◽  
Reproducible Analysis ◽  
Generation Sequencing

Abstract Motivation Genetic barcodes have been established as an efficient method to trace clonal progeny of uniquely labeled cells by introducing artificial genetic sequences into the corresponding genomes. The assessment of those sequences relies on next generation sequencing and the subsequent analysis aiming to identify sequences of interest and correctly quantifying their abundance. Results We developed the genBaRcode package as a toolbox combining the flexibility of digesting next generation sequencing reads with or without a sophisticated barcode structure, with a variety of error-correction approaches and the availability of several types of visualization routines. Furthermore, a graphical user interface was incorporated to allow also less experienced R users package-based analyses. Finally, the provided tool is intended to bridge the gap between generating and analyzing barcode data and thereby supporting the establishment of standardized and reproducible analysis strategies. Availability and implementation The genBaRcode package is available at CRAN (https://cran.r-project.org/package=genBaRcode).

scholarly journals Development of a Software Package for Cattle Identification in Nigeria

2019 ◽  
Vol 23 (10) ◽  
pp. 1825-1828 ◽  
Author(s):  
R.W. Bello ◽  
S. Abubakar
Keyword(s):  
Data Analysis ◽  
User Interface ◽  
Graphical User Interface ◽  
Software Package ◽  
Smart Phone ◽  
Information Encoding ◽  
Software Application ◽  
Free Range ◽  
Encoding Method ◽  
Tools And Methods

Open grazing or free-range grazing is one of the methods employed by the Nigeria nomadic cattle herders to provide pasture for their cattle. This method of providing pasture for cattle comes with so many challenges among which are cow swapping, ownership disputes, rustling and cow intrusion to farmland. Some existing methods of guiding against these challenges are expensive, injurious, and unreliable to apply. The objective of this paper is to develop an enhanced and affordable software package for cow recognition and identification using a graphical user interface and information encoding method. Data analysis module with software application for the analysis of the generated code is proposed; the software application installed on a computer or smart-phone may be standalone or otherwise. Data about individual cow is digitally collected, coded and stored using necessary resources, tools, and methods. Moreover, by tagging individual cow with the generated code, and matching the code with the ones in the database using code reader, individual cow can be recognized and identified.Keywords: Open grazing; Free-range grazing; Nomadic herder; Cow identification; Pasture.

Computer Microvision for MEMS

1999 ◽  
Vol 605 ◽  
Author(s):  
Dennis M. Freeman
Keyword(s):  
Image Analysis ◽  
Data Analysis ◽  
User Interface ◽  
Graphical User Interface ◽  
3D Structure ◽  
Ccd Camera ◽  
Optical Microscope ◽  
Stroboscopic Illumination ◽  
Frame Grabber

AbstractWe have developed a versatile instrument for in situ measurement of motions of MEMS. Images of MEMS are magnified with an optical microscope and projected onto a CCD camera. Stroboscopic illumination is used to obtain stop-action images of the moving structures. Stopaction images from multiple focal planes provide information about 3D structure and 3D motion. Image analysis algorithms determine motions of all visible structures with nanometer accuracy.Hardware for the system includes the microscope, CCD camera and associated frame grabber, piezoelectric focusing element, and a modular stimulator that generates arbitrary periodic waveforms and synchronized stroboscopic illumination. These elements are controlled from a Pentium-based computer using a graphical user interface that guides the user through both data collection and data analysis. The system can measure motions at frequencies as high as 5 MHz with nanometer resolution, i.e., well below the wavelength of light.

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