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BAC specifications

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Unique identifier OMICS_00801
Name BAC
Alternative name Bayesian analysis of ChIP-chip
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License Artistic License version 2.0
Computer skills Advanced
Version 1.40.0
Stability Stable
Requirements
R(>=2.10)
Maintained Yes

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Documentation


Publications for Bayesian analysis of ChIP-chip

BAC citations

 (2)
library_books

Bayesian modeling of ChIP chip data using latent variables

2009
BMC Bioinformatics
PMCID: 2779819
PMID: 19857265
DOI: 10.1186/1471-2105-10-352

[…] sing essentially a mixture of normal distributions, and models the spatial structure of the probes using a Gaussian intrinsic auto-regression model []. Gottardo [] developed a software for the model, Bayesian analysis of ChIP-chip (or BAC for short). Using BAC [] does not need extra experimental information, but it is extremely slow, roughly 10 hours for a dataset with 300,000 probes on a personal […]

library_books

Improved ChIP chip analysis by a mixture model approach

2009
BMC Bioinformatics
PMCID: 2700807
PMID: 19500407
DOI: 10.1186/1471-2105-10-173

[…] iers [], and it assumes at most one peak per genomic region, so that the genome has to be partitioned (often arbitrarily) into smaller regions before applying HGMM. Gottardo et. al.'s method [], BAC (Bayesian Analysis of ChIP-chip), is based on approaches used for gene expression studies [] with some additional modifications to exploit the spatial dependence between neighboring probes and to impro […]


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BAC institution(s)
Department of Statistics, University of British Columbia, Vancouver, BC, Canada; Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, MA, USA
BAC funding source(s)
This work was funded by NIH grant 1R01 HG004069-01.

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