Search results for "Reproducible research"

showing 4 items of 4 documents

pcaExplorer: an R/Bioconductor package for interacting with RNA-seq principal components

2019

AbstractBackgroundPrincipal component analysis (PCA) is frequently useentirely written ind in genomics applications for quality assessment and exploratory analysis in high-dimensional data, such as RNA sequencing (RNA-seq) gene expression assays. Despite the availability of many software packages developed for this purpose, an interactive and comprehensive interface for performing these operations is lacking.ResultsWe developed the pcaExplorer software package to enhance commonly performed analysis steps with an interactive and user-friendly application, which provides state saving as well as the automated creation of reproducible reports. pcaExplorer is implemented in R using the Shiny fra…

Computer scienceInterface (computing)ShinyBioconductorPrincipal component analysis610 MedizinRNA-SeqGenomicslcsh:Computer applications to medicine. Medical informaticsReproducible researchBioconductorTranscriptomeExploratory data analysisUser-friendly610 Medical sciencesGene expressionHumansRNA-SeqGenelcsh:QH301-705.5Data CurationBase Sequencebusiness.industrySequence Analysis RNARRNAReproducibility of Resultslcsh:Biology (General)Principal component analysisRNAlcsh:R858-859.7Software engineeringbusinessSoftware
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sar: Automatic generation of statistical reports using Stata and Microsoft Word for Windows

2013

The output provided by most Stata commands is plain text not suitable to be presented or published. After the numerical and graphical outputs are obtained, the user has to copy them into a word processor to complete the editing process. Some Stata commands help you to obtain well-formatted output, especially tabulated results in LATEX or other formats, but they are not a complete solution nor are they friendly tools. Stata automatic report (Sar) is an easy-to-use macro for Microsoft Word for Windows that allows a powerful integration between Stata and Word. With Sar, the user can retrieve numerical results and graphs from Stata and automatically insert them into a well-formatted Word docum…

Computer sciencebusiness.industryProgramming languagePlain textWord processingProcess (computing)computer.file_formatcomputer.software_genreAutomationMathematics (miscellaneous)WorkflowSar Stata Automation object report automation Microsoft Word reproducible research Automation OLEData miningMacrobusinesscomputerWord (computer architecture)
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ideal: an R/Bioconductor package for interactive differential expression analysis

2020

AbstractBackgroundRNA sequencing (RNA-seq) is an ever increasingly popular tool for transcriptome profiling. A key point to make the best use of the available data is to provide software tools that are easy to use but still provide flexibility and transparency in the adopted methods. Despite the availability of many packages focused on detecting differential expression, a method to streamline this type of bioinformatics analysis in a comprehensive, accessible, and reproducible way is lacking.ResultsWe developed the ideal software package, which serves as a web application for interactive and reproducible RNA-seq analysis, while producing a wealth of visualizations to facilitate data interpr…

Differential expression analysisComputer scienceShinyBioconductorInteractive data analysislcsh:Computer applications to medicine. Medical informaticsReproducible researchBioconductorDifferential expressionCode (cryptography)Transcriptome profilingHumansRNA-SeqTranscriptomicslcsh:QH301-705.5Flexibility (engineering)Ideal (set theory)Base Sequencebusiness.industryData visualizationGene Expression ProfilingRRNAReproducibility of ResultsTransparency (human–computer interaction)Gene Expression Regulationlcsh:Biology (General)Data Interpretation StatisticalWeb applicationlcsh:R858-859.7Software engineeringbusinessSoftwareBMC Bioinformatics
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GeneTonic: an R/Bioconductor package for streamlining the interpretation of RNA-seq data

2021

AbstractBackgroundThe interpretation of results from transcriptome profiling experiments via RNA sequencing (RNA-seq) can be a complex task, where the essential information is distributed among different tabular and list formats - normalized expression values, results from differential expression analysis, and results from functional enrichment analyses. A number of tools and databases are widely used for the purpose of identification of relevant functional patterns, yet often their contextualization within the data and results at hand is not straightforward, especially if these analytic components are not combined together efficiently.ResultsWe developed the GeneTonic software package, whi…

QH301-705.5Process (engineering)Computer scienceShinyComputer applications to medicine. Medical informaticsBioconductor610 MedizinR858-859.7Context (language use)Interactive data analysisReproducible researchBioconductorInteractivity610 Medical sciencesUse caseRNA-SeqBiology (General)MIT LicenseTranscriptomicsInformation retrievalBase SequenceSequence Analysis RNAData interpretationData visualizationRReproducibility of ResultsIdentification (information)WorkflowRNASoftwareFunctional enrichment analysis
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