PO.BCS01.15 · 生物信息与计算
CASTLE:用于改进体细胞变异检出与基准评估标准的癌细胞系长读长测序面板
CASTLE: long-read sequencing panel of cancer cell lines to improve standards of somatic variant calling and benchmarking
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
目前大多数大规模全基因组测序项目依赖短读长测序来检出种系和体细胞结构变异(SV),然而由于可比对性的限制,它对体细胞变异图景的呈现并不完整。相比之下,长读长测序能够解析人类基因组中高度重复的区域,并将变异组装成连续的单倍型,因此是解析癌症基因组隐藏复杂性的一种有前景的方法。然而,目前用于基准评估和新方法开发的公开数据集数量仍然有限。
为推动癌症基因组学新型短读长和长读长工具的开发,我们创建了CASTLE面板,其基于对六对可商购获得的肿瘤/正常细胞系配对(HCC1954、HCC1937、H1437、H2009、Hs578T和HCC1395)进行的多技术全基因组测序。该面板包含两个肺癌和三个乳腺癌细胞系。基因组测序目前包括PacBio、Oxford Nanopore、Illumina、Hi-C和PoreC,在大多数情况下均来自同一DNA提取物或细胞系传代。
我们进一步使用集成(ensemble)方法为SNP、小indel和结构变异生成了高置信度的基准体细胞变异检出结果。对于结构变异,我们使用Severus、nanomonsv、SAVANA、Sniffles2、SvABA、GRIDSS和Manta生成初步变异检出结果;置信检出结果定义为至少受到(三种技术中的)两种技术支持且至少受到(11个检出工具中的)4个工具支持。对于小变异基准集,我们使用了Strelka2、DeepSomatic和ClairS的组合。
总体而言,我们发布了一项用于癌症基因组学开发和基准评估的新公共资源,并计划以更多基因组学和转录组学技术加以补充。数据和基准评估数据集在以下地址公开可用:https://github.com/CASTLE-Panel/castle。
查看英文原文 English abstract
Most current large-scale whole-genome sequencing projects rely on short-read sequencing to call germline and somatic SVs, however it provides an incomplete view of the somatic variation landscape because of mappability limitations. In contrast, long-read sequencing can resolve highly repetitive regions of the human genome, and assemble variants into contiguous haplotypes, and therefore is a promising approach to resolve the hidden complexity of a cancer genome. However there is still a limited number of publicly available datasets for benchmarking and development of new methods.
To motivate the development of new short- and long-read tools for cancer genomics, we created the CASTLE panel, based on multi-technology whole-genome sequencing of six commercially available tumor/normal cell line pairs (HCC1954, HCC1937, H1437, H2009, Hs578T and HCC1395). The panel represents two lung and three breast cancer cell lines. Genomic sequencing currently includes PacBio, Oxford Nanopore, Illumina, Hi-C and PoreC, in most cases sequenced from the same DNA extraction or cell line passage.
We further generated high-confidence benchmarking somatic variant calls for SNPs, small indels and structural variants using the ensemble method. For structural variants, We used Severus, nanomonsv, SAVANA, Sniffles2, SvABA, GRIDSS, and Manta to generate initial variant calls; confident calls were defined if supported by at least two (out of three) technologies and at least 4 (out of 11) callers. For small variant benchmarking sets, we used a combination of Strelka2, DeepSomatic and ClairS.
Overall, we release a new public resource for cancer genomic developments and benchmarking, which we are aiming to complement with additional genomic and transcriptomic technologies. The data and benchmarking datasets are openly available at: https://github.com/CASTLE-Panel/castle.
利益披露 Disclosure
M. Kolmogorov, None.