PCA via joint graph Laplacian and sparse constraint: Identification of differentially expressed genes and sample clustering on gene expression data

BACKGROUND: In recent years, identification of differentially expressed genes and sample clustering have become hot topics in bioinformatics. Principal Component Analysis (PCA) is a widely used method in gene expression data. However, it has two limitations: first, the geometric structure hidden in...

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Detalles Bibliográficos
Autores principales: Feng, Chun-Mei, Xu, Yong, Hou, Mi-Xiao, Dai, Ling-Yun, Shang, Jun-Liang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6936054/
https://www.ncbi.nlm.nih.gov/pubmed/31888433
http://dx.doi.org/10.1186/s12859-019-3229-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6936054/
https://www.ncbi.nlm.nih.gov/pubmed/31888433
http://dx.doi.org/10.1186/s12859-019-3229-z

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