Department of Immunology.
Life Sciences Core Facilities, Weizmann Institute of Science, Rehovot 76100, Israel.
Bioinformatics. 2017 Sep 15;33(18):2924-2929. doi: 10.1093/bioinformatics/btx286.
While growing numbers of T cell receptor (TCR) repertoires are being mapped by high-throughput sequencing, existing methods do not allow for computationally connecting a given TCR sequence to its target antigen, or relating it to a specific pathology. As an alternative, a manually-curated database can relate TCR sequences with their cognate antigens and associated pathologies based on published experimental data.
We present McPAS-TCR, a manually curated database of TCR sequences associated with various pathologies and antigens based on published literature. Our database currently contains more than 5000 sequences of TCRs associated with various pathologic conditions (including pathogen infections, cancer and autoimmunity) and their respective antigens in humans and in mice. A web-based tool allows for searching the database based on different criteria, and for finding annotated sequences from the database in users' data. The McPAS-TCR website assembles information from a large number of studies that is very hard to dissect otherwise. Initial analyses of the data provide interesting insights on pathology-associated TCR sequences.
Free access at http://friedmanlab.weizmann.ac.il/McPAS-TCR/ .
虽然高通量测序正在绘制越来越多的 T 细胞受体 (TCR) 库，但现有的方法无法在计算上连接给定的 TCR 序列与其靶抗原，或将其与特定的病理学联系起来。作为替代方案，基于已发表的实验数据，人工 curated 的数据库可以将 TCR 序列与其同源抗原和相关病理学联系起来。
我们提出了 McPAS-TCR，这是一个基于已发表文献的人工 curated 的 TCR 序列与各种病理学和抗原相关的数据库。我们的数据库目前包含超过 5000 个人类和小鼠 TCR 序列，这些 TCR 序列与各种病理状况（包括病原体感染、癌症和自身免疫）及其各自的抗原有关。一个基于网络的工具允许根据不同的标准搜索数据库，并在用户的数据中找到数据库中注释的序列。McPAS-TCR 网站汇集了大量研究的信息，否则很难将这些信息分解。对数据的初步分析提供了与病理学相关的 TCR 序列的有趣见解。
可免费访问 http://friedmanlab.weizmann.ac.il/McPAS-TCR/。
