Cargando…
BOOME: A Python package for handling misclassified disease and ultrahigh-dimensional error-prone gene expression data
In gene expression data analysis framework, ultrahigh dimensionality and measurement error are ubiquitous features. Therefore, it is crucial to correct measurement error effects and make variable selection when fitting a regression model. In this paper, we introduce a python package BOOME, which ref...
Autor principal: | Chen, Li-Pang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9612554/ https://www.ncbi.nlm.nih.gov/pubmed/36301828 http://dx.doi.org/10.1371/journal.pone.0276664 |
Ejemplares similares
-
Handling misclassified stratification variables in the analysis of randomised trials with continuous outcomes
por: Yelland, Lisa N., et al.
Publicado: (2023) -
Classification and prediction for multi-cancer data with ultrahigh-dimensional gene expressions
por: Chen, Li-Pang
Publicado: (2022) -
Misclassified group-tested current status data
por: Petito, L. C., et al.
Publicado: (2016) -
Half the boom better than no boom at all
Publicado: (2009) -
DSAVE: Detection of misclassified cells in single-cell RNA-Seq data
por: Gustafsson, Johan, et al.
Publicado: (2020)