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denoiSeq
View on CRAN: Click
here
Download and install denoiSeq package within the R console
Install from CRAN:
install.packages("denoiSeq")
Install from Github:
library("remotes")
install_github("cran/denoiSeq")
Install by package version:
library("remotes")
install_version("denoiSeq", "0.1.1")
Attach the package and use:
library("denoiSeq")
Maintained by
Gershom Buri
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All associated links for this package
First Published: 2017-07-18
Latest Update: 2018-01-31
Description:
Given count data from two conditions, it determines which transcripts are differentially expressed across the two conditions using Bayesian inference of the parameters of a bottom-up model for PCR amplification. This model is developed in Ndifon Wilfred, Hilah Gal, Eric Shifrut, Rina Aharoni, Nissan Yissachar, Nir Waysbort, Shlomit Reich Zeliger, Ruth Arnon, and Nir Friedman (2012), , and results in a distribution for the counts that is a superposition of the binomial and negative binomial distribution.
How to cite:
Gershom Buri (2017). denoiSeq: Differential Expression Analysis Using a Bottom-Up Model. R package version 0.1.1, https://cran.r-project.org/web/packages/denoiSeq. Accessed 21 Nov. 2024.
Previous versions and publish date:
0.1.0 (2017-07-18 21:15)
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Complete documentation for denoiSeq
Functions, R codes and Examples using
the denoiSeq R package
Some associated functions: ERCC . denoiseq . getSamplesOf . readsData . results . setInitValues . setOutput . setReplicates . setStepSizes . simdat . tunedStepSize .
Some associated R codes: Class_denoiSeq.R . DE_analysis.R . Gibbs_samplers.R . Metrapolis_Hast_samplers.R . ercc.R . full_conditionals.R . n_step_sampler.R . output_functions.R . simulated.R . Full denoiSeq package functions and examples
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