scholarly journals TCGAbiolinksGUI: A graphical user interface to analyze cancer molecular and clinical data

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 439 ◽  
Author(s):  
Tiago Chedraoui Silva ◽  
Antonio Colaprico ◽  
Catharina Olsen ◽  
Tathiane M Malta ◽  
Gianluca Bontempi ◽  
...  
Keyword(s):  
Data Analysis ◽  
User Interface ◽  
Graphical User Interface ◽  
Cancer Genomics ◽  
Genomic Data ◽  
Bioconductor Project ◽  
Video Tutorials ◽  
Data Portal ◽  
Advanced Knowledge ◽  
Data Commons

The GDC (Genomic Data Commons) data portal provides users with data from cancer genomics studies. Recently, we developed the R/Bioconductor TCGAbiolinks package, which allows users to search, download and prepare cancer genomics data for integrative data analysis. The use of this package requires users to have advanced knowledge of R thus limiting the number of users. To overcome this obstacle and improve the accessibility of the package by a wider range of users, we developed a graphical user interface (GUI) using Shiny available through the package TCGAbiolinksGUI. The TCGAbiolinksGUI package is freely available within the Bioconductor project at http://bioconductor.org/packages/TCGAbiolinksGUI/. Links to the GitHub repository, a demo version of the tool, a docker image and PDF/video tutorials are available from the TCGAbiolinksGUI site.

scholarly journals TCGAbiolinksGUI: A graphical user interface to analyze GDC cancer molecular and clinical data

2017 ◽  
Author(s):  
Tiago C Silva ◽  
Antonio Colaprico ◽  
Catharina Olsen ◽  
Gianluca Bontempi ◽  
Michele Ceccarelli ◽  
...  
Keyword(s):  
User Interface ◽  
Graphical User Interface ◽  
Cancer Genomics ◽  
Bioconductor Package ◽  
Link Type ◽  
Bioconductor Project ◽  
Video Tutorials ◽  
Data Portal ◽  
Advanced Knowledge ◽  
Data Commons

AbstractBackground:The GDC (Genomic Data Commons) data portal provides users with data from cancer genomics studies. Recently, we developed the R/Bioconductor TCGAbiolinks package, which allows users to search, download and prepare cancer genomics data for integrative data analysis. The use of this package requires users to have advanced knowledge of R thus limiting the number of users.Results:To overcome this obstacle and improve the accessibility of the package by a wider range of users, we developed TCGAbiolinksGUI that uses shiny graphical user interface (GUI) available through the R/Bioconductor package.Conclusion:The TCGAbiolinksGUI package is freely available within the Bioconductor project at http://bioconductor.org/packages/TCGAbiolinksGUI/. Links to the GitHub repository, a demo version of the tool, a docker image and PDF/video tutorials are available at http://bit.do/TCGAbiolinksDocs.

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 Uniform Genomic Data Analysis in the NCI Genomic Data Commons

2019 ◽  
Author(s):  
Zhenyu Zhang ◽  
Kyle Hernandez ◽  
Jeremiah Savage ◽  
Shenglai Li ◽  
Dan Miller ◽  
...  
Keyword(s):  
Methylation Status ◽  
Genomic Data ◽  
Data Repository ◽  
Sequencing Data ◽  
Data Types ◽  
Data Production ◽  
Number Variation ◽  
Data Portal ◽  
Data Commons ◽  
Human Genome Reference

AbstractThe goal of the National Cancer Institute (NCI) Genomic Data Commons (GDC) is to provide the cancer research community with a data repository of uniformly processed genomic and associated clinical data that enables data sharing and collaborative analysis in the support of precision medicine. The initial GDC dataset include genomic, epigenomic, proteomic, clinical and other data from the NCI TCGA and TARGET programs. Data production for the GDC started in June, 2015 using an OpenStack-based private cloud. By June of 2016, the GDC had analyzed more than 50,000 raw sequencing data inputs, as well as multiple other data types. Using the latest human genome reference build GRCh38, the GDC generated a variety of data types from aligned reads to somatic mutations, gene expression, miRNA expression, DNA methylation status, and copy number variation. In this paper, we describe the pipelines and workflows used to process and harmonize the data in the GDC. The generated data, as well as the original input files from TCGA and TARGET, are available for download and exploratory analysis at the GDC Data Portal and Legacy Archive (https://gdc.cancer.gov/).

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.

scholarly journals GenomicDataCommons: a Bioconductor Interface to the NCI Genomic Data Commons

2017 ◽  
Author(s):  
Martin T. Morgan ◽  
Sean R. Davis
Keyword(s):  
High Performance ◽  
Data Transfer ◽  
Cancer Genomics ◽  
Genomic Data ◽  
Software Project ◽  
Link Type ◽  
Open Development ◽  
Statistical Programming ◽  
Basic Infrastructure ◽  
Data Commons

AbstractThe National Cancer Institute (NCI) Genomic Data Commons (Grossman et al. 2016, https://gdc.cancer.gov/) provides the cancer research community with an open and unified repository for sharing and accessing data across numerous cancer studies and projects via a high-performance data transfer and query infrastructure. The Bioconductor project (Huber et al. 2015) is an open source and open development software project built on the R statistical programming environment (R Core Team 2016). A major goal of the Bioconductor project is to facilitate the use, analysis, and comprehension of genomic data. The GenomicDataCommons Bioconductor package provides basic infrastructure for querying, accessing, and mining genomic datasets available from the GDC. We expect that Bioconductor developer and bioinformatics community will build on the GenomicDataCommons package to add higher-level functionality and expose cancer genomics data to many state-of-the-art bioinformatics methods available in Bioconductor.Availabilityhttps://bioconductor.org/packages/GenomicDataCommons & https://github.com/seandavi/GenomicDataCommons.

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