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SingscoreAMLMutations

Using singscore to predict mutations in AML from transcriptomic signatures

Bioconductor version: Release (3.17)

This workflow package shows how transcriptomic signatures can be used to infer phenotypes. The workflow begins by showing how the TCGA AML transcriptomic data can be downloaded and processed using the TCGAbiolinks packages. It then shows how samples can be scored using the singscore package and signatures from the MSigDB. Finally, the predictive capacity of scores in the context of predicting a specific mutation in AML is shown.The workflow exhibits the interplay of Bioconductor packages to achieve a gene-set level analysis.

Author: Dharmesh D. Bhuva [aut, cre] , Momeneh Foroutan [aut] , Yi Xie [aut] , Ruqian Lyu [aut], Malvika Kharbanda [aut] , Joseph Cursons [aut] , Melissa J. Davis [aut]

Maintainer: Dharmesh D. Bhuva <bhuva.d at wehi.edu.au>

Citation (from within R, enter citation("SingscoreAMLMutations")):

Installation

To install this package, start R (version "4.3") and enter: 

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("SingscoreAMLMutations")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("SingscoreAMLMutations")
Using singscore to predict mutations in AML from transcriptomic signatures HTML R Script
Using singscore to predict mutations in AML from transcriptomic signatures (Chinese version) HTML R Script
NEWS Text

Details

biocViews GeneExpressionWorkflow, GenomicVariantsWorkflow, ImmunoOncologyWorkflow, Workflow
Version 1.16.0
License Artistic-2.0
Depends R (>= 4.1.0)
Imports dcanr, edgeR, ggplot2, gridExtra, GSEABase, mclust, org.Hs.eg.db, plyr, reshape2, rtracklayer, singscore, SummarizedExperiment, TCGAbiolinks, BiocFileCache
Linking To
Suggests knitr, rmarkdown, BiocStyle, BiocWorkflowTools, spelling
System Requirements
Enhances
URL https://github.com/DavisLaboratory/SingscoreAMLMutations
Bug Reports https://github.com/DavisLaboratory/SingscoreAMLMutations/issues
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package SingscoreAMLMutations_1.16.0.tar.gz
Windows Binary
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/SingscoreAMLMutations
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/SingscoreAMLMutations
Package Short Url https://bioconductor.org/packages/SingscoreAMLMutations/
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