遇见数据集

SPARC single-cell protein data

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data.europa2023-05-30 更新2025-05-31 收录
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This data set contains protein measurements from single cell and 100 cells from early human neural differentiation cells. Cells were harvested at time points 0 h, 24 h and 48 h. Protein data measurements were carried out using PEA and quantitative values on protein concentrations were measures using qPCR. Following the completion of the qPCR run we visually inspected the amplification curves. Samples showing evidence of failed or poor amplification reactions were excluded from further analysis. Next, the raw Cq data (log 2 scale) was exported and processed. First, samples were excluded if no signal was detected in any of control assays (extension control, incubation control, or detection control), or if the signal in any of the controls was greater or less than 2 standard deviations (SD) of the mean value across all samples measured on a 96.96 IFC Biomark chip. Next, the remaining Cq values were normalized for intra-plate variation with the extension control (Cqassay—CqExtCtl) yielding dCq values. Then, for each assay, the dCq values were subtracted from the negative control computed as the lysis buffer mean + 2 × SD. This ensures that observed signals for each assay in the presence of a cell are at least 2 SDs away from any signals observed in the absence of any antigen. Resulting values below zero were set to zero and the signal was deemed undetected. The cumulative protein sum was calculated by summing across all proteins measured (n = 92) per cell.

本数据集包含人类早期神经分化细胞的单细胞及100细胞样本的蛋白质检测数据。样本采集时间点为0 h、24 h与48 h。蛋白质组数据的检测采用PEA(Protein Extension Assay),蛋白质浓度的定量值通过qPCR(定量聚合酶链式反应)获取。qPCR反应完成后,我们对扩增曲线进行了目视检查。存在扩增失败或扩增效率不佳迹象的样本将被排除,不纳入后续分析。随后导出原始Cq数据(以log₂为刻度)并进行处理。首先,若对照实验(延伸对照、孵育对照或检测对照)中未检测到任何信号,或任一对照的信号超出96.96 IFC Biomark芯片上所有测量样本均值的±2倍标准差(SD)范围,则该样本将被排除。随后,剩余的Cq值以延伸对照进行板内变异标准化,通过公式Cq_assay — Cq_ExtCtl计算得到dCq值。接着,针对每一项检测,将dCq值从以裂解缓冲液均值+2×SD计算得到的阴性对照值中减去。该操作可确保在存在细胞的情况下,每项检测的观测信号与无抗原条件下的观测信号之间至少相差2倍标准差。所得数值若低于0则将其置为0,并将该信号判定为未检测到。通过对每个细胞的所有被测蛋白质(n=92)进行求和,计算得到累积蛋白质总量。

提供机构:
Uppsala universitet
创建时间:
2022-03-24
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