Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, 08826, Republic of Korea.
Genome4me Inc., Seoul, 08826, Republic of Korea.
Exp Mol Med. 2023 Aug;55(8):1734-1742. doi: 10.1038/s12276-023-01049-2. Epub 2023 Aug 1.
The detection of somatic DNA variants in tumor samples with low tumor purity or sequencing depth remains a daunting challenge despite numerous attempts to address this problem. In this study, we constructed a substantially extended set of actual positive variants originating from a wide range of tumor purities and sequencing depths, as well as actual negative variants derived from sequencer-specific sequencing errors. A deep learning model named AIVariant, trained on this extended dataset, outperforms previously reported methods when tested under various tumor purities and sequencing depths, especially low tumor purity and sequencing depth.
尽管已经进行了多次尝试来解决这个问题，但在肿瘤样本中检测低肿瘤纯度或测序深度的体细胞 DNA 变体仍然是一项艰巨的挑战。在这项研究中，我们构建了一个由广泛的肿瘤纯度和测序深度的实际阳性变体以及来自特定测序错误的实际阴性变体组成的扩展数据集。在这个扩展数据集上训练的名为 AIVariant 的深度学习模型在各种肿瘤纯度和测序深度下进行测试时，性能优于之前报道的方法，尤其是在低肿瘤纯度和测序深度下。
