Towards a comprehensive evaluation of dimension reduction methods for transcriptomic data visualization

Dimension reduction (DR) algorithms project data from high dimensions to lower dimensions to enable visualization of interesting high-dimensional structure. DR algorithms are widely used for analysis of single-cell transcriptomic data. Despite widespread use of DR algorithms such as t-SNE and UMAP,...

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Detalles Bibliográficos
Autores principales: Huang, Haiyang, Wang, Yingfan, Rudin, Cynthia, Browne, Edward P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9296444/
https://www.ncbi.nlm.nih.gov/pubmed/35853932
http://dx.doi.org/10.1038/s42003-022-03628-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9296444/
https://www.ncbi.nlm.nih.gov/pubmed/35853932
http://dx.doi.org/10.1038/s42003-022-03628-x

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