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PaSD-qc: quality control for single cell whole-genome sequencing data using power spectral density estimation

机译:PaSD-qc:使用功率谱密度估算对单细胞全基因组测序数据进行质量控制

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摘要

Single cell whole-genome sequencing (scWGS) is providing novel insights into the nature of genetic heterogeneity in normal and diseased cells. However, the whole-genome amplification process required for scWGS introduces biases into the resulting sequencing that can confound downstream analysis. Here, we present a statistical method, with an accompanying package PaSD-qc (Power Spectral Density-qc), that evaluates the properties and quality of single cell libraries. It uses a modified power spectral density to assess amplification uniformity, amplicon size distribution, autocovariance and inter-sample consistency as well as to identify chromosomes with aberrant read-density profiles due either to copy alterations or poor amplification. These metrics provide a standard way to compare the quality of single cell samples as well as yield information necessary to improve variant calling strategies. We demonstrate the usefulness of this tool in comparing the properties of scWGS protocols, identifying potential chromosomal copy number variation, determining chromosomal and subchromosomal regions of poor amplification, and selecting high-quality libraries from low-coverage data for deep sequencing. The software is available free and open-source at .
机译:单细胞全基因组测序(scWGS)为正常细胞和患病细胞遗传异质性的性质提供了新颖的见解。但是,scWGS所需的全基因组扩增过程会在产生的测序中引入偏差,从而可能混淆下游分析。在这里,我们提出了一种统计方法以及随附的软件包PaSD-qc(功率谱密度-qc),用于评估单个细胞库的特性和质量。它使用修改后的功率谱密度来评估扩增均匀性,扩增子大小分布,自协方差和样本间一致性,并识别由于拷贝改变或扩增不良而导致的异常读密度分布的染色体。这些指标提供了一种标准的方法来比较单个细胞样品的质量以及产生改进变体检出策略所需的信息。我们证明了该工具在比较scWGS协议的属性,识别潜在的染色体拷贝数变异,确定扩增不良的染色体和亚染色体区域以及从低覆盖率数据中选择高质量文库进行深度测序方面的有用性。该软件可从处免费和开源。

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