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pcaExplorer: an R/Bioconductor package for interacting with RNA-seq principal components
by
Marini, Federico
, Binder, Harald
in
Algorithms
/ Biochemistry
/ Bioinformatics
/ Biomedical and Life Sciences
/ Computational Biology/Bioinformatics
/ Computer Appl. in Life Sciences
/ Computer programs
/ Data analysis
/ Data structures
/ Datasets
/ Dimensional analysis
/ Exploration
/ Exploratory data analysis
/ Exports
/ Gene expression
/ Gene sequencing
/ Genes
/ Genomics
/ Information management
/ Life Sciences
/ Methods
/ Microarrays
/ Packaging
/ Principal component analysis
/ Principal components analysis
/ Product development
/ Quality assessment
/ Quality control
/ Reproducible research
/ Ribonucleic acid
/ RNA
/ RNA sequencing
/ RNA-Seq
/ Shiny
/ Software
/ Software packages
/ Source code
/ Technology application
/ Transcriptome analysis
/ User-friendly
/ Web applications
2019
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pcaExplorer: an R/Bioconductor package for interacting with RNA-seq principal components
by
Marini, Federico
, Binder, Harald
in
Algorithms
/ Biochemistry
/ Bioinformatics
/ Biomedical and Life Sciences
/ Computational Biology/Bioinformatics
/ Computer Appl. in Life Sciences
/ Computer programs
/ Data analysis
/ Data structures
/ Datasets
/ Dimensional analysis
/ Exploration
/ Exploratory data analysis
/ Exports
/ Gene expression
/ Gene sequencing
/ Genes
/ Genomics
/ Information management
/ Life Sciences
/ Methods
/ Microarrays
/ Packaging
/ Principal component analysis
/ Principal components analysis
/ Product development
/ Quality assessment
/ Quality control
/ Reproducible research
/ Ribonucleic acid
/ RNA
/ RNA sequencing
/ RNA-Seq
/ Shiny
/ Software
/ Software packages
/ Source code
/ Technology application
/ Transcriptome analysis
/ User-friendly
/ Web applications
2019
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Do you wish to request the book?
pcaExplorer: an R/Bioconductor package for interacting with RNA-seq principal components
by
Marini, Federico
, Binder, Harald
in
Algorithms
/ Biochemistry
/ Bioinformatics
/ Biomedical and Life Sciences
/ Computational Biology/Bioinformatics
/ Computer Appl. in Life Sciences
/ Computer programs
/ Data analysis
/ Data structures
/ Datasets
/ Dimensional analysis
/ Exploration
/ Exploratory data analysis
/ Exports
/ Gene expression
/ Gene sequencing
/ Genes
/ Genomics
/ Information management
/ Life Sciences
/ Methods
/ Microarrays
/ Packaging
/ Principal component analysis
/ Principal components analysis
/ Product development
/ Quality assessment
/ Quality control
/ Reproducible research
/ Ribonucleic acid
/ RNA
/ RNA sequencing
/ RNA-Seq
/ Shiny
/ Software
/ Software packages
/ Source code
/ Technology application
/ Transcriptome analysis
/ User-friendly
/ Web applications
2019
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pcaExplorer: an R/Bioconductor package for interacting with RNA-seq principal components
Journal Article
pcaExplorer: an R/Bioconductor package for interacting with RNA-seq principal components
2019
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Overview
Background
Principal component analysis (PCA) is frequently used 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.
Results
We 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 framework and exploits data structures from the open-source Bioconductor project. Users can easily generate a wide variety of publication-ready graphs, while assessing the expression data in the different modules available, including a general overview, dimension reduction on samples and genes, as well as functional interpretation of the principal components.
Conclusion
pcaExplorer
is distributed as an R package in the Bioconductor project (
http://bioconductor.org/packages/pcaExplorer/
), and is designed to assist a broad range of researchers in the critical step of interactive data exploration.
Publisher
BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
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