A novel joint analysis framework improves identification of differentially expressed genes in cross disease transcriptomic analysis

MOTIVATION: Detecting differentially expressed (DE) genes between disease and normal control group is one of the most common analyses in genome-wide transcriptomic data. Since most studies don’t have a lot of samples, researchers have used meta-analysis to group different datasets for the same disea...

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Detalles Bibliográficos
Autores principales: Qin, Wenyi, Lu, Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Methodology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5819186/
https://www.ncbi.nlm.nih.gov/pubmed/29467826
http://dx.doi.org/10.1186/s13040-018-0163-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5819186/
https://www.ncbi.nlm.nih.gov/pubmed/29467826
http://dx.doi.org/10.1186/s13040-018-0163-y

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