ShrinkBayes statistics

To access cutting-edge analytics on consensus tools, life science contexts and associated fields, you will need to subscribe to our premium service.

Subscribe
info

Citations per year

Citations chart
info

Popular tool citations

chevron_left Differential expression Normalization chevron_right
Popular tools chart
info

Tool usage distribution map

Tool usage distribution map
info

Associated diseases

Associated diseases

ShrinkBayes specifications

Information


Unique identifier OMICS_01961
Name ShrinkBayes
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License GNU General Public License version 3.0
Computer skills Advanced
Stability Stable
Requirements
INLA, snowfall, VGAM, mclust, logcondens, Iso
Maintained Yes

Versioning


Add your version

Maintainer


  • person_outline Mark van de Wiel <>

Publication for ShrinkBayes

ShrinkBayes in publications

 (6)
PMCID: 5447894
PMID: 28398587
DOI: 10.1093/jxb/erx104

[…] the log of the negative binomial dispersion parameter was assumed to be constant and a draw from a normal distribution with unknown mean and variance. an empirical bayes procedure via the r package ‘shrinkbayes’ () was used to estimate the unknown parameters, and to approximate the posterior distribution for the fixed effect associated with gene (g) and sample type (s) using the integrated […]

PMCID: 5444478
PMID: 28204533
DOI: 10.1093/jxb/erw422

[…] random effects were assumed to follow gamma distributions, where the parameters for the lane effects were specified to create a vague distribution. an empirical bayes procedure via the r package ‘shrinkbayes’ () was used to estimate the unknown parameters, and to approximate the posterior distribution for the fixed effect associated with the gene (g), genotype (t), and stage (s) using […]

PMCID: 5217027
PMID: 27351222
DOI: 10.18632/oncotarget.10270

[…] secondary antibodies (li-cor biosciences, lincoln, ne, usa)., the mirnas differential expression analysis was performed using a bayesian approach that has been implemented in the r-package shrinkbayes. this approach has been known for its robustness in small sample series []. p-values < 0.05 were considered statistically significant for a single test, and benjamini-hochberg […]

PMCID: 4753849
PMID: 26628518
DOI: 10.1093/jxb/erv513

[…] that the expected number of reads is less than a given threshold. a gene was declared as ‘inactive’ in a specific root type if the resulting posterior probability was >0.5. the r-package shrinkbayes, which is based on the ideas of , was used to obtain empirical bayes estimates of hyperparameters and compute the desired posterior probabilities. a key idea of shrinkbayes is to use […]

PMCID: 4753846
PMID: 26463995
DOI: 10.1093/jxb/erv453

[…] in the distributions of the fixed effects, negative binomial dispersion, and precision of the biological replicate effects were estimated using an empirical bayes procedure via the r package ‘shrinkbayes’ (). integrated nested laplace approximation () was used to approximate the posterior distribution for the fixed effect associated with gene, tissue, and condition., for a given threshold […]


To access a full list of publications, you will need to upgrade to our premium service.

ShrinkBayes institution(s)
Department of Epidemiology and Biostatistics, VU University medical center, Amsterdam, The Netherlands; Department of Mathematics, VU University, Amsterdam, The Netherlands; Department of Medical Oncology, VU University medical center, Amsterdam, The Netherlands; Department of Pathology, VU University medical center, Amsterdam, The Netherlands

ShrinkBayes reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review ShrinkBayes