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scDisInFact: disentangled learning for integration and prediction of multi-batch multi-condition single-cell RNA-sequencing data
Single-cell RNA-sequencing (scRNA-seq) has been widely used for disease studies, where sample batches are collected from donors under different conditions including demographical groups, disease stages, and drug treatments. It is worth noting that the differences among sample batches in such a study...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10187255/ https://www.ncbi.nlm.nih.gov/pubmed/37205545 http://dx.doi.org/10.1101/2023.05.01.538975 |