STRidER, the STRs for Identity ENFSI Reference Database, is a curated, freely publicly available online allele frequency database, quality control (QC) and software platform for autosomal Short Tandem Repeats (STRs) developed under the endorsement of the International Society for Forensic Genetics. Continuous updates comprise additional STR loci and populations in the frequency database and many further STR-related aspects. One significant innovation is the autosomal STR data QC provided prior to publication of datasets. Such scrutiny was lacking previously, leaving QC to authors, reviewers and editors, which led to an unacceptably high error rate in scientific papers. The results from scrutinizing 184 STR datasets containing >177,000 individual genotypes submitted in the first two years of STRidER QC since 2017 revealed that about two-thirds of the STR datasets were either being withdrawn by the authors after initial feedback or rejected based on a conservative error rate. Almost no error-free submissions were received, which clearly shows that centralized QC and data curation are essential to maintain the high-quality standard required in forensic genetics. While many errors had minor impact on the resulting allele frequencies, multiple error categories were commonly found within single datasets. Several datasets contained serious flaws. We discuss the factors that caused the errors to draw the attention to redundant pitfalls and thus contribute to better quality of autosomal STR datasets and allele frequency reports.

中文翻译：

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关于常染色体 STR 种群数据集两年质量控制的 STRidER 报告

STRidER，即身份 ENFSI 参考数据库的 STR，是在国际法医遗传学协会的支持下开发的一个精心策划的、免费公开可用的在线等位基因频率数据库、质量控制 (QC) 和常染色体短串联重复序列 (STR) 软件平台。持续更新包括频率数据库中的其他 STR 基因座和种群以及许多其他与 STR 相关的方面。一项重大创新是在数据集发布之前提供的常染色体 STR 数据 QC。以前缺乏这种审查，将质量控制留给作者、审稿人和编辑，这导致科学论文的错误率高得令人无法接受。仔细检查 184 个 STR 数据集的结果，其中包含 >177，自 2017 年以来在 STRidER QC 的前两年提交的 000 个个体基因型显示，大约三分之二的 STR 数据集要么在最初的反馈后被作者撤回，要么基于保守的错误率被拒绝。几乎没有收到无错误的提交，这清楚地表明集中 QC 和数据管理对于保持法医遗传学所需的高质量标准至关重要。虽然许多错误对产生的等位基因频率的影响很小，但在单个数据集中通常会发现多个错误类别。几个数据集包含严重缺陷。我们讨论了导致错误的因素，以引起对冗余陷阱的注意，从而有助于提高常染色体 STR 数据集和等位基因频率报告的质量。