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CelFiE-ISH: a probabilistic model for multi-cell type deconvolution from single-molecule DNA methylation haplotypes
Genome Biology ( IF 10.1 ) Pub Date : 2024-06-10 , DOI: 10.1186/s13059-024-03275-x
Irene Unterman 1 , Dana Avrahami 1, 2 , Efrat Katsman 1 , Timothy J Triche 3 , Benjamin Glaser 2 , Benjamin P Berman 1
Affiliation  

Deconvolution methods infer quantitative cell type estimates from bulk measurement of mixed samples including blood and tissue. DNA methylation sequencing measures multiple CpGs per read, but few existing deconvolution methods leverage this within-read information. We develop CelFiE-ISH, which extends an existing method (CelFiE) to use within-read haplotype information. CelFiE-ISH outperforms CelFiE and other existing methods, achieving 30% better accuracy and more sensitive detection of rare cell types. We also demonstrate the importance of marker selection and of tailoring markers for haplotype-aware methods. While here we use gold-standard short-read sequencing data, haplotype-aware methods will be well-suited for long-read sequencing.

中文翻译:


CelFiE-ISH:单分子 DNA 甲基化单倍型多细胞类型反卷积的概率模型



反卷积方法通过对包括血液和组织在内的混合样本的批量测量来推断定量细胞类型估计。 DNA 甲基化测序可测量每次读取的多个 CpG,但现有的反卷积方法很少利用这种读取内信息。我们开发了 CelFiE-ISH,它扩展了现有方法 (CelFiE) 以使用读内单倍型信息。 CelFiE-ISH 优于 CelFiE 和其他现有方法,对稀有细胞类型的检测精度提高了 30%,检测灵敏度更高。我们还证明了标记选择和定制标记对于单倍型感知方法的重要性。虽然我们在这里使用黄金标准的短读长测序数据,但单倍型感知方法将非常适合长读长测序。
更新日期:2024-06-10
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