CrossNorm: a novel normalization strategy for microarray data in cancers

Normalization is essential to get rid of biases in microarray data for their accurate analysis. Existing normalization methods for microarray gene expression data commonly assume a similar global expression pattern among samples being studied. However, scenarios of global shifts in gene expressions...

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Detalles Bibliográficos
Autores principales: Cheng, Lixin, Lo, Leung-Yau, Tang, Nelson L. S., Wang, Dong, Leung, Kwong-Sak
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4702063/
https://www.ncbi.nlm.nih.gov/pubmed/26732145
http://dx.doi.org/10.1038/srep18898

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4702063/
https://www.ncbi.nlm.nih.gov/pubmed/26732145
http://dx.doi.org/10.1038/srep18898

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