Department of Informatics, Systems, and Communication, University of Milano - Bicocca, Milan, Italy.
Georgia State University, Atlanta, GA, USA.
BMC Bioinformatics. 2020 Dec 9;21(Suppl 1):413. doi: 10.1186/s12859-020-03736-7.
Cancer progression reconstruction is an important development stemming from the phylogenetics field. In this context, the reconstruction of the phylogeny representing the evolutionary history presents some peculiar aspects that depend on the technology used to obtain the data to analyze: Single Cell DNA Sequencing data have great specificity, but are affected by moderate false negative and missing value rates. Moreover, there has been some recent evidence of back mutations in cancer: this phenomenon is currently widely ignored.
We present a new tool, gpps, that reconstructs a tumor phylogeny from Single Cell Sequencing data, allowing each mutation to be lost at most a fixed number of times. The General Parsimony Phylogeny from Single cell (gpps) tool is open source and available at https://github.com/AlgoLab/gpps .
gpps provides new insights to the analysis of intra-tumor heterogeneity by proposing a new progression model to the field of cancer phylogeny reconstruction on Single Cell data.
癌症进展重建是一个重要的发展，源于系统发生学领域。在这种情况下，代表进化历史的系统发生重建呈现出一些特殊的方面，这取决于用于获取要分析的数据的技术：单细胞 DNA 测序数据具有很强的特异性，但受到中度假阴性和缺失值率的影响。此外，最近有证据表明癌症存在回突现象：这种现象目前被广泛忽视。
我们提出了一种新的工具 gpps，它可以从单细胞测序数据中重建肿瘤系统发生，允许每个突变最多丢失固定次数。单细胞通用简约系统发生（gpps）工具是开源的，可在 https://github.com/AlgoLab/gpps 获得。
gpps 通过向单细胞数据的癌症系统发生重建领域提出一种新的进展模型，为分析肿瘤内异质性提供了新的见解。
