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A targeted solution for estimating the cell-type composition of bulk samples

机译：估计批量样品细胞型组成的靶向溶液

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摘要

To avoid false-positive findings and detect cell-type specific associations in methylation and transcription investigations with bulk samples, it is critical to know the proportions of the major cell-types. We present a novel approach that allows for precise estimation of cell-type proportions using only a few highly informative methylation markers. The most reliable estimates were obtained with 17 amplicons (34 CpGs) using the MuSiC estimator, for which the average correlations between the estimated and the true cell-type proportions were 0.889. Furthermore, the estimates were not significantly different from the true values (P?=?0.95) indicating that the estimator is unbiased and the standard deviation of the estimates further indicate high precision. Moreover, the overall variability of the estimates as measured by the Root Mean Squared Error (RMSE), which is a function of both bias and precision, was low (mean RMSE?=?0.038). Taken together, these results indicate that the approach produced reliable estimates that are both unbiased and highly precise. This cost-effective approach for estimating cell-type proportions in bulk samples allows for enhanced targeted analysis, which in turn will minimize the risk of reporting false-positive findings and allowing for detection of cell-type specific associations. The approach is applicable across platforms and can be extended to assess cell-type proportions for various tissues.
机译：为了避免使用批量样本的甲基化和转录调查中的假阳性发现并检测细胞型特异性关联，了解主要细胞类型的比例至关重要。我们提出了一种新的方法，其允许仅使用少数高度信息性甲基化标记来精确地估计细​​胞型比例。使用音乐估计器具有17个扩增子（34 CPG）获得最可靠的估计值，估计和真正的细胞型比例之间的平均相关性为0.889。此外，估计与真正值没有显着不同（P？= 0.95），表明估计器是不偏不倚的，并且估计的标准偏差进一步表明高精度。此外，由根均方误差（RMSE）测量的估计的整体变化是偏差和精度的函数，低（平均RMSE？= 0.038）。总之，这些结果表明该方法产生了可靠的估计，既不偏见，高度精确。这种具有估计批量样本中的细胞型比例的这种经济高效的方法允许增强的目标分析，这反过来将最小化报告假阳性发现并允许检测细胞类型特定关联的风险。该方法适用于平台，可以扩展以评估各种组织的细胞型比例。

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