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Count model based differential expression and normalization on GeoMx RNA data

Bioconductor version: Release (3.18)

A series of statistical models using count generating distributions for background modelling, feature and sample QC, normalization and differential expression analysis on GeoMx RNA data. The application of these methods are demonstrated by example data analysis vignette.

Author: Nicole Ortogero [cre], Lei Yang [aut], Zhi Yang [aut]

Maintainer: Nicole Ortogero <nortogero at nanostring.com>

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


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biocViews DifferentialExpression, GeneExpression, Normalization, Software
Version 1.8.0
In Bioconductor since BioC 3.14 (R-4.1) (2.5 years)
License MIT + file LICENSE
Depends R (>= 4.1.0), Biobase
Imports Matrix, robust, plyr, lme4, Rcpp (>=, withr, methods, graphics, stats, testthat, GeomxTools, NanoStringNCTools
System Requirements
URL https://github.com/Nanostring-Biostats/GeoDiff
Bug Reports https://github.com/Nanostring-Biostats/GeoDiff
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Suggests knitr, rmarkdown, dplyr
Linking To Rcpp, RcppArmadillo, roptim
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Source Package GeoDiff_1.8.0.tar.gz
Windows Binary GeoDiff_1.8.0.zip (64-bit only)
macOS Binary (x86_64) GeoDiff_1.8.0.tgz
macOS Binary (arm64) GeoDiff_1.8.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/GeoDiff
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/GeoDiff
Bioc Package Browser https://code.bioconductor.org/browse/GeoDiff/
Package Short Url https://bioconductor.org/packages/GeoDiff/
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