On the viability of unsupervised T-cell receptor sequence clustering for epitope preference
On the viability of unsupervised T-cell receptor sequence clustering for epitope preference
复制标题
DOI：
10.1093/bioinformatics/bty821
复制
发表时间：
2019-05-01
期刊：
影响因子：
5.8
通讯作者：
Laukens, Kris
中科院分区：
文献类型：
--
作者：
Meysman, Pieter;De Neuter, Nicolas;Laukens, Kris
T细胞受体(TCR)负责识别细胞表面的表位。将TCR序列与其靶向特定表位的能力联系起来目前是一个悬而未决的问题，但也是人们非常感兴趣的问题之一。事实上，目前尚不清楚TCR序列在不再结合同一表位之前会有多大的不同。有许多方法可以定义两个TCR序列之间的相似性，这一事实使这个问题变得复杂起来。我们在TCR序列无监督聚类的背景下对这两个问题进行了研究。结果我们给出了各种距离度量在两个大型独立数据集上的性能，分别具有412和2835个TCR序列。我们的结果证实了针对相同表位的结构上不同的TCR组的存在。此外，我们提出了几个建议来执行无监督的T细胞受体序列聚类。可用性和实现在https://github.com/pmeysman/TCRclusteringPaper.Supplementary信息中提供了用Python3实现的源代码生物信息学在线上提供了补充数据。
Motivation The T-cell receptor (TCR) is responsible for recognizing epitopes presented on cell surfaces. Linking TCR sequences to their ability to target specific epitopes is currently an unsolved problem, yet one of great interest. Indeed, it is currently unknown how dissimilar TCR sequences can be before they no longer bind the same epitope. This question is confounded by the fact that there are many ways to define the similarity between two TCR sequences. Here we investigate both issues in the context of TCR sequence unsupervised clustering.Results We provide an overview of the performance of various distance metrics on two large independent datasets with 412 and 2835 TCR sequences respectively. Our results confirm the presence of structural distinct TCR groups that target identical epitopes. In addition, we put forward several recommendations to perform unsupervised T-cell receptor sequence clustering.Availability and implementation Source code implemented in Python 3 available at https://github.com/pmeysman/TCRclusteringPaper.Supplementary informationSupplementary data are available at Bioinformatics online.