Cargando…
Combining location-and-scale batch effect adjustment with data cleaning by latent factor adjustment
BACKGROUND: In the context of high-throughput molecular data analysis it is common that the observations included in a dataset form distinct groups; for example, measured at different times, under different conditions or even in different labs. These groups are generally denoted as batches. Systemat...
Autores principales: | Hornung, Roman, Boulesteix, Anne-Laure, Causeur, David |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4710051/ https://www.ncbi.nlm.nih.gov/pubmed/26753519 http://dx.doi.org/10.1186/s12859-015-0870-z |
Ejemplares similares
-
Alternative empirical Bayes models for adjusting for batch effects in genomic studies
por: Zhang, Yuqing, et al.
Publicado: (2018) -
Priority-Lasso: a simple hierarchical approach to the prediction of clinical outcome using multi-omics data
por: Klau, Simon, et al.
Publicado: (2018) -
BEclear: Batch Effect Detection and Adjustment in DNA Methylation Data
por: Akulenko, Ruslan, et al.
Publicado: (2016) -
Adjusting for sampling variability in sparse data: geostatistical approaches to disease mapping
por: Hampton, Kristen H, et al.
Publicado: (2011) -
Removing Batch Effects in Analysis of Expression Microarray Data: An Evaluation of Six Batch Adjustment Methods
por: Chen, Chao, et al.
Publicado: (2011)