A combined test for feature selection on sparse metaproteomics data—an alternative to missing value imputation

One of the difficulties encountered in the statistical analysis of metaproteomics data is the high proportion of missing values, which are usually treated by imputation. Nevertheless, imputation methods are based on restrictive assumptions regarding missingness mechanisms, namely “at random” or “not...

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Detalles Bibliográficos
Autores principales: Plancade, Sandra, Berland, Magali, Blein-Nicolas, Mélisande, Langella, Olivier, Bassignani, Ariane, Juste, Catherine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2022
Materias:
Bioinformatics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9235818/
https://www.ncbi.nlm.nih.gov/pubmed/35769140
http://dx.doi.org/10.7717/peerj.13525

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9235818/
https://www.ncbi.nlm.nih.gov/pubmed/35769140
http://dx.doi.org/10.7717/peerj.13525

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