Single-cell specific and interpretable machine learning models for sparse scChIP-seq data imputation

MOTIVATION: Single-cell Chromatin ImmunoPrecipitation DNA-Sequencing (scChIP-seq) analysis is challenging due to data sparsity. High degree of sparsity in biological high-throughput single-cell data is generally handled with imputation methods that complete the data, but specific methods for scChIP-...

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Detalles Bibliográficos
Autores principales: Albrecht, Steffen, Andreani, Tommaso, Andrade-Navarro, Miguel A., Fontaine, Jean Fred
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9249201/
https://www.ncbi.nlm.nih.gov/pubmed/35776722
http://dx.doi.org/10.1371/journal.pone.0270043

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9249201/
https://www.ncbi.nlm.nih.gov/pubmed/35776722
http://dx.doi.org/10.1371/journal.pone.0270043

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