Current Challenges in Cell-Type Discovery Through Single-Cell Data

被引:0
|
作者
Roditi, Laura De Vargas [1 ]
Macnair, Will [2 ]
Claassen, Manfred
机构
[1] ETH, Inst Mol Syst Biol, Auguste Piccard Hof 1, CH-8093 Zurich, Switzerland
[2] SIB, Zurich, Switzerland
关键词
FLOW-CYTOMETRY DATA; ORIGIN;
D O I
10.1051/itmconf/20150500010
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Single cell sequencing and proteome profiling efforts in the past few years have revealed widespread genetic and proteomic heterogeneity among tumor cells. However, sensible cell-type definition of such heterogeneous cell populations has so far been a challenging task. Single cell technologies such as RNA sequencing and mass cytometry provide information precluded by conventional bulk measurements and have achieved significant improvements in multiparametricity at high cellular throughput. By combining these technologies with computational and mathematical techniques it is possible to quantitatively define cellular heterogeneity, uncovering distinct phenotypic profiles that can be utilized to, for example, characterize tumor heterogeneity with the potential to develop and improve therapeutic strategies.
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页数:3
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