Comparison of methods for the detection of outliers and associated biomarkers in mislabeled omics data

BACKGROUND: Previous studies have reported that labeling errors are not uncommon in omics data. Potential outliers may severely undermine the correct classification of patients and the identification of reliable biomarkers for a particular disease. Three methods have been proposed to address the pro...

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Detalles Bibliográficos
Autores principales: Sun, Hongwei, Cui, Yuehua, Wang, Hui, Liu, Haixia, Wang, Tong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7646480/
https://www.ncbi.nlm.nih.gov/pubmed/32795265
http://dx.doi.org/10.1186/s12859-020-03653-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7646480/
https://www.ncbi.nlm.nih.gov/pubmed/32795265
http://dx.doi.org/10.1186/s12859-020-03653-9

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