500: Trajectory inference across conditions: differential expression and differential progression
Kelly Street (Dana-Farber Cancer Institute) Research Fellow
Koen Van den Berge (University of California, Berkeley) Postdoc
Hector Roux de Bezieux (University of California, Berkeley) Ph.D. Student
11:00 AM - 11:55 AM EDT on Friday, 31 July
WORKSHOP
In single-cell RNA-sequencing (scRNA-seq), gene expression is assessed at the level of single cells. In dynamic biological systems, it may not be appropriate to assign cells to discrete groups, but rather a continuum of cell states may be observed, e.g. the differentiation of a stem cell population into mature cell types. This is often represented as a trajectory in reduced dimension.
Many methods have been suggested for trajectory inference. However, in this setting, it is often unclear how one should handle multiple biological groups or conditions, e.g. constructing and comparing the differentiation trajectory of a wild type versus a knock-out stem cell population.
In this workshop, we will explore methods for comparing multiple conditions in a trajectory inference analysis. We start by integrating datasets from multiple conditions into a single trajectory. By comparing the conditions along the trajectory's path, we can detect large-scale changes, indicative of differential progression. We also demonstrate how to detect subtler changes by finding genes that exhibit different behaviors between these conditions along a differentiation path.
The "Differential Topology" vignette from the Slingshot package provides a more complete problem description and proposes a few analytical approaches, which will serve as the basis of our workshop.
Moderator: Erica Feick
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