BNBR specifications

Information


Unique identifier OMICS_29075
Name BNBR
Alternative name Bayesian Negative Binomial Regression
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
Computer skills Advanced
Stability Stable
Maintained Yes

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Versioning


No version available

Maintainers


  • person_outline Xiaoning Qian
  • person_outline Mingyuan Zhou
  • person_outline Siamak Zamani Dadaneh

Publication for Bayesian Negative Binomial Regression

BNBR citations

 (2)
library_books

Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer’s disease

2016
Genome Med
PMCID: 5088659
PMID: 27799057
DOI: 10.1186/s13073-016-0355-3

[…] jor brain cell types: astrocyte, endothelial, microglia, neuron, and oligodendrocyte. Genes with less than 50 reads across all samples were discarded. The remaining gene count data were analyzed by a Bayesian negative binomial regression model with cell type identity, basal expression (or library size), and subject source incorporated as predictors by making use of the RStan source code provided i […]

library_books

Single Cell Transcriptomics Reveals that Differentiation and Spatial Signatures Shape Epidermal and Hair Follicle Heterogeneity

2016
Cell Syst
PMCID: 5052454
PMID: 27641957
DOI: 10.1016/j.cels.2016.08.010

[…] t of the mean, it can be described as σ=rμ with overdispersion factor r. Hence,a=μr2−1b=r2−1.By attaching prior distributions to the overdispersion factor r and the coefficients βk, we acquire a full Bayesian negative binomial regression model, withμ=∑k=1Kβkxky|λ∼Poisson(λ)λ|μ,r∼Gamma(μr2−1,r2−1)r∼Cauchy(0,1)βk=Pareto(0,1.5).The model was implemented in STAN. A more detailed explanation of the mod […]

BNBR institution(s)
Department of Electrical & Computer Engineering, TEES-AgriLife Center for Bioinformatics & Genomic Systems Engineering, Texas A&M University, College Station, TX, USA; Department of Information, Risk, & Operations Management, The University of Texas at Austin, Austin, TX, USA
BNBR funding source(s)
Supported by Award CCF-1553281 from the National Science Foundation and the USDA NIFA Award 06-505570-01006.

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