In recent years, there has been a significant increase in whole genome sequencing data of individual genomes produced by research projects as well as direct to consumer service providers. While many of these sources provide their users with an interpretation of the data, there is a lack of free, open tools for generating reports exploring the data in an easy to understand manner. GenomeChronicler was developed as part of the Personal Genome Project UK (PGP-UK) to address this need. PGP-UK provides genomic, transcriptomic, epigenomic and self-reported phenotypic data under an open-access model with full ethical approval. As a result, the reports generated by GenomeChronicler are intended for research purposes only and include information relating to potentially beneficial and potentially harmful variants, but without clinical curation. GenomeChronicler can be used with data from whole genome or whole exome sequencing, producing a genome report containing information on variant statistics, ancestry and known associated phenotypic traits. Example reports are available from the PGP-UK data page (personalgenomes.org.uk/data). The objective of this method is to leverage existing resources to find known phenotypes associated with the genotypes detected in each sample. The provided trait data is based primarily upon information available in SNPedia, but also collates data from ClinVar, GETevidence, and gnomAD to provide additional details on potential health implications, presence of genotype in other PGP participants and population frequency of each genotype. The analysis can be run in a self-contained environment without requiring internet access, making it a good choice for cases where privacy is essential or desired: any third party project can embed GenomeChronicler within their off-line safe-haven environments. GenomeChronicler can be run for one sample at a time, or in parallel making use of the Nextflow workflow manager. The source code is available from GitHub (https://github.com/PGP-UK/GenomeChronicler), container recipes are available for Docker and Singularity, as well as a pre-built container from SingularityHub (https://singularity-hub.org/collections/3664) enabling easy deployment in a variety of settings. Users without access to computational resources to run GenomeChronicler can access the software from the Lifebit CloudOS platform (https://lifebit.ai/cloudos) enabling the production of reports and variant calls from raw sequencing data in a scalable fashion.

近年来，由研究项目产生并直接提供给消费者服务提供商的单个基因组的全基因组测序数据已大大增加。尽管许多此类资源为用户提供了对数据的解释，但缺少免费，开放的工具来生成以易于理解的方式浏览数据的报告。GenomeChronicler是英国个人基因组计划（PGP-UK）的一部分，旨在满足这一需求。PGP-UK在完全获得伦理批准的开放访问模型下提供基因组，转录组，表观基因组和自我报告的表型数据。因此，GenomeChronicler生成的报告仅用于研究目的，包括与潜在有益和潜在有害变体有关的信息，但没有临床治疗方法。GenomeChronicler可以与来自全基因组或整个外显子组测序的数据一起使用，生成基因组报告，其中包含有关变异统计，祖先和已知相关表型性状的信息。示例报告可从PGP-UK数据页面（personalgenomes.org.uk/数据）。该方法的目的是利用现有资源来查找与每个样本中检测到的基因型相关的已知表型。主要取决于在SNPedia资料所提供的性状数据为基础，同时也整理从ClinVar，GETevidence和gnomAD数据对潜在的健康影响，在其他PGP参与者基因型的存在和各基因型频率人口提供更多细节。该分析可以在独立的环境中运行，而无需访问互联网，因此对于隐私至关重要或需要隐私的情况是一个不错的选择：任何第三方项目都可以将GenomeChronicler嵌入其离线安全避风港环境中。GenomeChronicler可以一次运行一个样本，也可以使用Nextflow工作流管理器并行运行。https://github.com/PGP-UK/GenomeChronicler），适用于Docker和Singularity的容器配方以及SingularityHub（https://singularity-hub.org/collections/3664），可以在各种设置中轻松部署。无需访问计算资源即可运行GenomeChronicler的用户可以从Lifebit CloudOS平台访问该软件（https://lifebit.ai/cloudos），从而能够以可扩展的方式根据原始测序数据生成报告和变体调用。