FastProject: a tool for low-dimensional analysis of single-cell RNA-Seq data.
FastProject: a tool for low-dimensional analysis of single-cell RNA-Seq data.
复制标题
DOI：
10.1186/s12859-016-1176-5
复制
发表时间：
2016-08-23
影响因子：
3
通讯作者：
Yosef N
中科院分区：
文献类型：
--
作者：
DeTomaso D;Yosef N
单细胞RNA-Seq新兴领域的一个关键挑战是表征细胞之间的表型多样性，并以信息丰富的方式可视化这些信息。处理高维数据时的一种常见技术是将数据投影到2维或3维以进行可视化。然而，有多种方法可以实现这一结果，一旦预测，就很难将生物学意义归因于观察到的特征。此外，在分析单细胞数据时，细胞之间的关系可能会被技术混杂因素（如可变的基因捕获率）所掩盖。为了帮助分析和解释单细胞RNA-Seq数据，我们开发了FastProject，这是一种软件工具，可以分析基因表达矩阵并生成动态输出报告，其中可以探索数据的二维投影。注释的基因集（称为基因“签名”）被纳入，以便在投影中的功能可以被理解的生物过程中，他们可能代表。FastProject提供了一种针对基因签名对每个细胞进行评分的新方法，以最大限度地减少遗漏转录本的影响，以及一种对签名-投影配对进行排名的方法，以便快速识别有意义的关联。此外，FastProject是用模块化架构编写的，旨在作为一个平台，用于整合和比较新的投影方法和基因选择算法。在这里，我们提出了FastProject，一个软件包的二维可视化的单细胞数据，它利用了过多的投影方法，并提供了一种方法来系统地调查这些低维表示的生物相关性，通过结合领域知识。本文的在线版本（doi：10.1186/s12859-016-1176-5）包含补充材料，可供授权用户使用。
A key challenge in the emerging field of single-cell RNA-Seq is to characterize phenotypic diversity between cells and visualize this information in an informative manner. A common technique when dealing with high-dimensional data is to project the data to 2 or 3 dimensions for visualization. However, there are a variety of methods to achieve this result and once projected, it can be difficult to ascribe biological significance to the observed features. Additionally, when analyzing single-cell data, the relationship between cells can be obscured by technical confounders such as variable gene capture rates. To aid in the analysis and interpretation of single-cell RNA-Seq data, we have developed FastProject, a software tool which analyzes a gene expression matrix and produces a dynamic output report in which two-dimensional projections of the data can be explored. Annotated gene sets (referred to as gene ‘signatures’) are incorporated so that features in the projections can be understood in relation to the biological processes they might represent. FastProject provides a novel method of scoring each cell against a gene signature so as to minimize the effect of missed transcripts as well as a method to rank signature-projection pairings so that meaningful associations can be quickly identified. Additionally, FastProject is written with a modular architecture and designed to serve as a platform for incorporating and comparing new projection methods and gene selection algorithms. Here we present FastProject, a software package for two-dimensional visualization of single cell data, which utilizes a plethora of projection methods and provides a way to systematically investigate the biological relevance of these low dimensional representations by incorporating domain knowledge. The online version of this article (doi:10.1186/s12859-016-1176-5) contains supplementary material, which is available to authorized users.