Fluorescent cell barcoding (FCB) enables efficient collection of tens to hundreds of flow cytometry samples by covalently marking cells with varying concentration of spectrally distinct dyes. A key consideration in FCB is to balance the density of dye barcodes, the complexity of cells in the sample, and the desired accuracy of the debarcoding. Unfortunately, barcoding bench and computational methods have not benefited from the high dimensional revolution in cytometry due to a lack of automated computational tools that effectively balance these common cytometry needs. DebarcodeR addresses these unmet needs by providing a framework for computational debarcoding augmented by improvements to experimental methods. Adaptive regression modeling accounted for differential dye uptake between different cell types and Gaussian mixture modeling provided a robust method to probabilistically assign cells to samples. Assignment tolerance parameters are available to allow users to balance high cell recovery with accurate assignments. Improvements to experimental methods include: (1) inclusion of an “external standard” control where a pool of all cells was stained a single level of each barcoding dyes and (2) an “internal standard” where each cell is stained with a single level of a separate dye. DebarcodeR significantly improved speed, accuracy, and reproducibility of FCB while avoiding selective loss of unusual cell subsets when debarcoding microtiter plates of cell lines and heterogenous mixtures of primary cells. DebarcodeR is available on Github as an R package that works with flowCore and Cytoverse packages at github.com/cytolab/DebarcodeR.

中文翻译：

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DebarcodeR 提高了荧光细胞条形码的容量和准确性

荧光细胞条形码 (FCB) 通过用不同浓度的光谱不同染料共价标记细胞，能够有效收集数十到数百个流式细胞仪样本。FCB 的一个关键考虑因素是平衡染料条形码的密度、样品中细胞的复杂性以及所需的去条形码精度。不幸的是，由于缺乏有效平衡这些常见细胞计数需求的自动化计算工具，条形码工作台和计算方法并没有从细胞计数的高维革命中受益。DebarcodeR 通过提供一个计算去条码框架并通过改进实验方法来解决这些未满足的需求。自适应回归模型解释了不同细胞类型之间的差异染料吸收，高斯混合模型提供了一种可靠的方法来概率性地将细胞分配给样品。分配容差参数可让用户在高细胞回收率和准确分配之间取得平衡。对实验方法的改进包括：(1) 包含一个“外标”对照，其中所有细胞的池被染色的每种条形码染料的单个水平和 (2) 一个“内标”，其中每个细胞都被染色单个水平一种单独的染料。DebarcodeR 显着提高了 FCB 的速度、准确性和可重复性，同时在对细胞系微量滴定板和原代细胞异质混合物进行脱条时避免选择性丢失异常细胞亚群。