Step 7 数据分析
检测获得的FCS 格式文件由FlowJo (BD Biosciences),分析处理。
以上7个步骤是高维多色流式实验非常严谨的标准流程,有正在做的老师希望通过今天的分享可以帮助您的实验。
参考文献:
1. Robinson JP, Roederer M (2015) History ofscience flow cytometry strikes gold. Science350:739–740. https://doi.org/10.1126/science.aad6770
2. Spitzer MH, Nolan GP (2016) Mass cytometry: single cells, many features. Cell165:780–791. https://doi.org/10.1016/j.cell.2016.04.019
3. Zheng GXY, Terry JM, Belgrader P et al(2017) Massively parallel digital transcriptional
profiling of single cells. Nat Commun8:14049. https://doi.org/10.1038/ncomms14049
4. Brodie TM, Tosevski V (2017) Highdimensional single-cell analysis with mass cytometry. Curr Protoc Immunol 118:5.11.1–5.11.25. https://doi.org/10.1002/cpim.31
5. Papalexi E, Satija R (2017) Single-cell RNAsequencing to explore immune cell heterogeneity. Nat Rev Immunol 510:363. https://doi.org/10.1038/nri.2017.76
6. Mair F, Prlic M (2018) OMIP-044: 28-colorimmunophenotyping of the human dendritic
cell compartment. Cytometry A 106:255.https://doi.org/10.1002/cyto.a.23331
7. Futamura K, Sekino M, Hata A et al (2015) Novel full-spectral flow cytometry with multiple spectrally-adjacent fluorescent proteins and fluorochromes and visualization of in vivo cellular movement. Cytometry A 87:830–842. https://doi.org/10.1002/cyto.a.22725
8. Feher K, Volkmann von K, Kirsch J et al (2016) Multispectral flow cytometry: the consequences of increased light collection. Cytometry A 89:681–689. https://doi.org/10.1002/ cyto.a.22888
9. Kvistborg P, Gouttefangeas C, Aghaeepour N et al (2015) Thinking outside the gate: singlecell assessments in multiple dimensions. Immunity 42:591–592. https://doi.org/10.1016/j. immuni.2015.04.006
10. Saeys Y, Gassen SV, Lambrecht BN (2016) Computational flow cytometry: helping to make sense of high-dimensional immunology data. Nat Rev Immunol 16:449–462. https:// http://doi.org/10.1038/nri.2016.56
11. Mair F, Hartmann FJ, Mrdjen D et al (2016) The end of gating? An introduction to automated analysis of high dimensional cytometry data. Eur J Immunol 46:34–43. https://doi. org/10.1002/eji.201545774
12. Chester C, Maecker HT (2015) Algorithmic tools for mining high-dimensional cytometry data. J Immunol 195:773–779. https://doi. org/10.4049/jimmunol.1500633
13. Meinelt E, Reunanen M, Edinger M et al Standardizing application setup across multiple flow cytometers using BD FACSDiva™ Version 6 Software: technical bul
14.Ashhurst TM, Smith AL, King NJC (2017) High-dimensional fluorescence cytometry. Curr Protoc Immunol 10:5.8.1–5.8.38. https://doi.org/10.1002/cpim.37
15.Liechti T, Gu¨nthard HF, Trkola A (2018) OMIP-047: high-dimensional phenotypic characterization of B cells. Cytometry A 103:2262–2596. https://doi.org/10.1002/ cyto.a.23488