简化下一流分析管道用于循环染色体的基于免疫沉的表观基因组分析
Ze Zhang1,2,3,4, Paulo Da Silva Cordeiro1,2,3,4,5, Surya B Chhetri1,2,3,4
1Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
bioRxiv : the preprint server for biology
|January 9, 2026
概括
我们开发了SNAP,这是一个生物信息学管道,用于分析无细胞色素表观基因组. 该工具通过提供针对循环瘤DNA (ctDNA) 分析的优化质量控制来改善疾病检测和监测.
科学领域:
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
- 分子生物学分子生物学
背景情况:
- 循环染色体表观基因分析为疾病检测和监测提供了一种最少的侵入性方法.
- 现有的生物信息学管道并没有针对无细胞色素的独特特性进行优化.
研究的目的:
- 介绍SNAP (Streamlined Nextflow Analysis Pipeline),一种新的生物信息学工作流程,适用于使用基于免疫沉的方法进行无细胞染色体表观基因分析.
- 通过对循环染色素的优化分析,提高疾病检测和监测的准确性和可靠性.
主要方法:
- 开发了SNAP,一个可复制,可扩展和模块化的Nextflow管道.
- 集成了针对循环染色素的优化质量控制指标,包括丰富度得分和碎片计数.
- 综合循环瘤DNA (ctDNA) 含量估计和SNP指纹采集用于样本身份验证.
主要成果:
- 当应用到各种癌症类型的cfChIP-seq和cfMeDIP-seq数据时,SNAP显示了更好的分类性能和高数据保留率.
- 在骨肉瘤患者的独立验证证实了与ctDNA水平相关的瘤相关的表观遗传学特征的检测.
- 该管道成功识别了反映疾病生物学的表观遗传学特征.
结论:
- SNAP为无细胞色素表观基因组研究提供了一个强大而可扩展的框架.
- 该管道增强了对疾病检测,监测和了解疾病生物学的最小侵入性表观基因组分析的实用性.
- SNAP与云计算和高性能计算环境兼容,并可供公众使用.
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