Transcriptome Deconvolution of Heterogeneous Tumor Samples with Immune Infiltration

Transcriptome deconvolution in cancer and other heterogeneous tissues remains challenging. Available methods lack the ability to estimate both component-specific proportions and expression profiles for individual samples. We present DeMixT, a new tool to deconvolve high-dimensional data from mixture...

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Detalles Bibliográficos
Autores principales: Wang, Zeya, Cao, Shaolong, Morris, Jeffrey S., Ahn, Jaeil, Liu, Rongjie, Tyekucheva, Svitlana, Gao, Fan, Li, Bo, Lu, Wei, Tang, Ximing, Wistuba, Ignacio I., Bowden, Michaela, Mucci, Lorelei, Loda, Massimo, Parmigiani, Giovanni, Holmes, Chris C., Wang, Wenyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6249353/
https://www.ncbi.nlm.nih.gov/pubmed/30469014
http://dx.doi.org/10.1016/j.isci.2018.10.028

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6249353/
https://www.ncbi.nlm.nih.gov/pubmed/30469014
http://dx.doi.org/10.1016/j.isci.2018.10.028

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