質譜流式細胞儀使用感應耦合電漿質譜儀技術，使能檢測的參數數目較傳統流式細胞儀大量增加，大量的數據提升了分析的難度。此研究使用R 語言套件「Cytofkit」來分析透明細胞腎細胞癌質譜流式細胞儀數據與視覺化，利用Cytofkit內的PhenoGraph 工具分析數據之後，因套件本身能輸出的圖表有格式限制且種類有限，無法進行更詳細的數據判讀。因此，使用經PhenoGraph 分析後所輸出的檔案進行更多種類的圖表設計及數據分析，以提供更多資訊判斷細胞間的差異。 本研究以熱圖、箱形圖及小提琴圖呈現質譜流式細胞儀資料，並輔以統計檢定。透過細胞標誌表現量熱圖再製，標誌標準化的熱圖、比較各組織細胞、各細胞簇及各病人細胞的箱形圖及小提琴圖設計等，加上統計檢定分析的驗證，以更容易地找出各組織中特別的細胞標誌供日後透明細胞腎細胞癌檢測為主要目的。除此之外，也藉由圖表的製作，檢測樣本數增加在PhenoGraph 分析是否穩定分群及抽樣細胞數是否足夠。;The technique of inductively coupled plasma mass spectrometer (ICP-MS) is introduced into CyTOF. It makes the number of parameters detected in CyTOF much more than those in flow cytometry. However, it makes it more difficult to analyze data. This study analyzes and visualizes clear cell renal cell carcinoma CyTOF by using package ‘Cytofkit’ in R. Although Cytofkit provides the function to make plots, the formats of plots are fixed and plot types are limited. It is difficult to interpret data more detailedly. Thus, we used exported files from running PhenoGraph, an analysis method in Cytofkit, to make different types of plots and do statistical analysis to provide more information for comparing cells. This study displayed heatmaps, box plots and violin plots of CyTOF data and the statistical analysis. The main goal is to uncover special markers among different tissue cells. Plotting heatmaps, box plots and violin plots, which are designed to compare cells in different tissues, clusters and patients, makes it easier to find differences. Also, statistical analysis is made to validate the finding. Furthermore, plots are designed to test the clustering stability of PhenoGraph analysis when more samples are added and whether sample size is enough.
