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利用星座图在低深度全基因组测序中确定肿瘤倍性并可视化等位基因拷贝数

Tumor ploidy determination in low-pass whole genome sequencing and allelic copy number visualization using the Constellation Plot.

作者信息

Johnson Sarah H, Smadbeck James B, Zenka Roman M, Barrett Michael T, Gaitatzes Athanasios, Solanki Arnav, Florio Angela B, Borad Mitesh J, Cheville John C, Vasmatzis George

机构信息

Biomarker Discovery Program, Mayo Clinic, Rochester, MN, 55905, USA.

Center for Individualized Medicine, Mayo Clinic, Rochester, MN, 55905, USA.

出版信息

Genome Biol. 2025 May 20;26(1):132. doi: 10.1186/s13059-025-03599-2.

Abstract

Ploidy determination across the genome has been challenging for low-pass-WGS tumor-only samples. We present BACDAC, a method that calculates tumor ploidy down to 1.2X effective tumor coverage. Allele fraction patterns displayed in the Constellation Plot verify tumor ploidy and reveal subclonal populations. BACDAC outputs a metric, 2NLOH, that when combined with ploidy better distinguishes near-diploid from high-ploidy tumors. Validated using TCGA, BACDAC had good agreement with other methods and 88% agreement with experimental methods. Discrepancies occur mainly when BACDAC predicts diploidy with subclones rather than high-ploidy. Applied to 653 low-pass-WGS samples spanning 12 cancer subtypes, BACDAC calls 40% as high-ploidy.

摘要

对于仅采用低深度全基因组测序(low-pass-WGS)的肿瘤样本而言,确定全基因组的倍性颇具挑战性。我们提出了BACDAC方法,该方法可将肿瘤倍性计算至有效肿瘤覆盖度低至1.2X。星座图(Constellation Plot)中显示的等位基因分数模式可验证肿瘤倍性并揭示亚克隆群体。BACDAC输出一个指标,即2NLOH,当与倍性相结合时,能更好地区分近二倍体肿瘤和高倍体肿瘤。经肿瘤基因组图谱(TCGA)验证,BACDAC与其他方法具有良好的一致性,与实验方法的一致性为88%。差异主要出现在BACDAC预测存在亚克隆的二倍体而非高倍体时。将BACDAC应用于涵盖12种癌症亚型的653个低深度全基因组测序样本时,它将40%的样本判定为高倍体。

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