TSCAN: Pseudo-Time Reconstruction and Evaluation in Single-Cell RNA-Seq Analysis

• Activity Number: 434
• Type: Contributed
• Date/Time: Tuesday, August 2, 2016 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistics in Genomics and Genetics
• Author(s): Zhicheng Ji* and Hongkai Ji
• Companies: Johns Hopkins Bloomberg School of Public Health and Johns Hopkins Bloomberg School of Public Health
• Keywords: Single-cell ; RNA-seq ; computational biology ; gene expression ; genomics ; data mining

Abstract

Constructing a pseudo-temporal path to order cells is a useful way to study gene expression dynamics in analyzing single-cell RNA-seq data. Currently, a limited number of computational tools are available for this task, and quantitative methods for comparing different tools are lacking. TSCAN is a software tool developed to better support in silico pseudo-Time reconstruction in Single-Cell RNA-seq ANalysis. TSCAN uses a cluster-based minimum spanning tree (MST) approach to order cells. Cells are first grouped into clusters and an MST is then constructed to connect cluster centers. Pseudo-time is obtained by projecting each cell onto the tree, and the ordered sequence of cells can be used to study dynamic changes of gene expression along the pseudo-time. Clustering cells before MST construction reduces the complexity of the tree space and often leads to improved cell ordering. With a graphical user interface, TSCAN also allows users to conveniently adjust the ordering based on prior knowledge. Furthermore, quantitative measures are developed to objectively evaluate and compare different pseudo-time reconstruction methods. TSCAN is available at https://github.com/zji90/TSCAN.