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Genotyping the population using next generation sequencing data is essentially important for the rare variant detection. In order to distinguish the genomic structural variation from sequencing error, we propose a statistical model which involves the genotype effect through a latent variable to depict the distribution of non-reference allele frequency data among different samples and different genome loci, while decomposing the sequencing error into sample effect and positional effect. An ECM algorithm is implemented to estimate the model parameters, and then the genotypes and SNPs are inferred based on the empirical Bayes method.
Version: | 2.0.1 |
Published: | 2016-04-13 |
DOI: | 10.32614/CRAN.package.ebGenotyping |
Author: | Na You and Gongyi Huang |
Maintainer: | Gongyi Huang <53hgy at 163.com> |
License: | GPL-2 |
NeedsCompilation: | no |
CRAN checks: | ebGenotyping results |
Reference manual: | ebGenotyping.pdf |
Package source: | ebGenotyping_2.0.1.tar.gz |
Windows binaries: | r-devel: ebGenotyping_2.0.1.zip, r-release: ebGenotyping_2.0.1.zip, r-oldrel: ebGenotyping_2.0.1.zip |
macOS binaries: | r-release (arm64): ebGenotyping_2.0.1.tgz, r-oldrel (arm64): ebGenotyping_2.0.1.tgz, r-release (x86_64): ebGenotyping_2.0.1.tgz, r-oldrel (x86_64): ebGenotyping_2.0.1.tgz |
Old sources: | ebGenotyping archive |
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