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CLASTR:细胞库 STR 相似性搜索工具 - 细胞系鉴定的宝贵帮手。

CLASTR: The Cellosaurus STR similarity search tool - A precious help for cell line authentication.

机构信息

CALIPHO Group, SIB Swiss Institute of Bioinformatics, CMU, Geneva, Switzerland.

Microbiology and Molecular Medicine Department, Faculty of Medicine, University of Geneva, Geneva, Switzerland.

出版信息

Int J Cancer. 2020 Mar 1;146(5):1299-1306. doi: 10.1002/ijc.32639. Epub 2019 Oct 4.

DOI:10.1002/ijc.32639
PMID:31444973
Abstract

Despite an increased awareness of the problematic of cell line cross-contamination and misidentification, it remains nowadays a major source of erroneous experimental results in biomedical research. To prevent it, researchers are expected to frequently test the authenticity of the cell lines they are working on. STR profiling was selected as the international reference method to perform cell line authentication. While the experimental protocols and manipulations for generating a STR profile are well described, the available tools and workflows to analyze such data are lacking. The Cellosaurus knowledge resource aimed to improve the situation by compiling all the publicly available STR profiles from the literature and other databases. As a result, it grew to become the largest database in terms of human STR profiles, with 6,474 distinct cell lines having an associated STR profile (release July 31, 2019). Here we present CLASTR, the Cellosaurus STR similarity search tool enabling users to compare one or more STR profiles with those available in the Cellosaurus cell line knowledge resource. It aims to help researchers in the process of cell line authentication by providing numerous functionalities. The tool is publicly accessible on the SIB ExPASy server (https://web.expasy.org/cellosaurus-str-search) and its source code is available on GitHub under the GPL-3.0 license.

摘要

尽管人们越来越意识到细胞系交叉污染和错误鉴定的问题,但它仍然是当今生物医学研究中错误实验结果的主要来源。为了防止这种情况发生,研究人员应该经常测试他们正在使用的细胞系的真实性。STR 分析被选为进行细胞系鉴定的国际参考方法。虽然生成 STR 图谱的实验方案和操作已经得到很好的描述,但缺乏分析此类数据的可用工具和工作流程。Cellosaurus 知识资源旨在通过编译文献和其他数据库中所有公开可用的 STR 图谱来改善这种情况。结果,它成长为拥有 6474 个不同细胞系相关 STR 图谱的最大数据库(2019 年 7 月 31 日发布)。在这里,我们介绍了 CLASTR,这是 Cellosaurus STR 相似性搜索工具,它使用户能够将一个或多个 STR 图谱与 Cellosaurus 细胞系知识资源中的图谱进行比较。它旨在通过提供众多功能帮助研究人员进行细胞系鉴定。该工具可在 SIB ExPASy 服务器(https://web.expasy.org/cellosaurus-str-search)上公开访问,其源代码可在 GitHub 上根据 GPL-3.0 许可证获得。

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