Caryl and Israel Englander Institute for Precision Medicine, Institute for Computational Biomedicine, Weill Cornell Medicine, Cornell University, New York, NY 10021, USA; Department of Physiology and Biophysics, Weill Cornell Medicine, Cornell University, New York, NY 10021, USA.
Division of Hematology/Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY 10021, USA.
Cancer Cell. 2021 Oct 11;39(10):1305-1307. doi: 10.1016/j.ccell.2021.09.006. Epub 2021 Sep 30.
Diffuse large B cell lymphoma (DLBCL) is a markedly phenotypically heterogenous disease, frequently assessed using bulk genomic techniques that blur the intrinsic heterogeneity of each tumor. In this issue of Cancer Cell, Steen et al. have utilized a computational framework called EcoTyper to skillfully dissect bulk transcriptomic tumor profiles into different cell type components in an unsupervised manner.
弥漫性大 B 细胞淋巴瘤 (DLBCL) 是一种显著表型异质性疾病，常使用批量基因组技术进行评估，从而模糊了每个肿瘤的固有异质性。在本期《癌细胞》中，Steen 等人利用一种称为 EcoTyper 的计算框架，以非监督的方式巧妙地将批量转录组肿瘤图谱解析为不同的细胞类型成分。
