动机：随着新测序技术的出现，单倍型解析的基因组组装体的产生一直到染色体规模已经变得可行。这些程序集捕获了两个亲本单倍型的完整遗传信息，增加了结构变异（SV）的调用敏感性，并实现了SV的直接基因分型和定相。但是，现有的SV调用程序仅设计用于单倍体基因组装配，不支持基因分型或仅检测有限的SV类集。结果：我们介绍了我们的方法SVIM-asm，用于检测和鉴定来自单倍体和二倍体基因组装配体的六种常见SVs。与其他现有的用于二倍体程序集的SV调用程序DipCall相比，SVIM-asm检测到更多的SV类，并且在HG002个人的两个最近发布的组件上的插入和缺失检测中达到了更高的F1分数。可用性和实现：SVIM-asm已在Python中实现，可以通过bioconda轻松安装。其源代码可在github.com/eldariont/svim-asm上找到。联系人：vingron@molgen.mpg.de补充信息：补充数据可在线获得。 Motivation: With the availability of new sequencing technologies, the generation of haplotype-resolved genome assemblies up to chromosome scale has become feasible. These assemblies capture the complete genetic information of both parental haplotypes, increase structural variant (SV) calling sensitivity and enable direct genotyping and phasing of SVs. Yet, existing SV callers are designed for haploid genome assemblies only, do not support genotyping or detect only a limited set of SV classes. Results: We introduce our method SVIM-asm for the detection and genotyping of six common classes of SVs from haploid and diploid genome assemblies. Compared against the only other existing SV caller for diploid assemblies, DipCall, SVIM-asm detects more SV classes and reached higher F1 scores for the detection of insertions and deletions on two recently published assemblies of the HG002 individual. Availability and Implementation: SVIM-asm has been implemented in Python and can be easily installed via bioconda. Its source code is available at github.com/eldariont/svim-asm. Contact: vingron@molgen.mpg.de Supplementary information: Supplementary data are available online.