Cargando…
How to Reveal Magnitude of Gene Signals: Hierarchical Hypergeometric Complementary Cumulative Distribution Function
This article introduces a new method for genome-wide association study (GWAS), hierarchical hypergeometric complementary cumulative distribution function (HH-CCDF). Existing GWAS methods, e.g. the linear model and hierarchical association coefficient algorithm, calculate the association between a ma...
Autor principal: | Kim, Bongsong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6196626/ https://www.ncbi.nlm.nih.gov/pubmed/30364489 http://dx.doi.org/10.1177/1176934318797352 |
Ejemplares similares
-
Feature Learning of Virus Genome Evolution With the Nucleotide Skip-Gram Neural Network
por: Shim, Hyunjin
Publicado: (2019) -
Genomic Prediction Using Canopy Coverage Image and Genotypic Information in Soybean via a Hybrid Model
por: Howard, Reka, et al.
Publicado: (2019) -
Cost-Effective Extreme Case-Control Design Using a Resampling
Method
por: Kim, Young Min, et al.
Publicado: (2019) -
Linearization of Median Genomes Under the Double-Cut-and-Join-Indel Model
por: Avdeyev, Pavel, et al.
Publicado: (2019) -
Modeling Cumulative Biological Phenomena with Suppes-Bayes Causal Networks
por: Ramazzotti, Daniele, et al.
Publicado: (2018)