-
Notifications
You must be signed in to change notification settings - Fork 7
Home
Welcome to the ISMB2018_SingleCellTranscriptomeTutorial wiki!
Tyler Faits, Boston University, United States
Matan Hofree, Broad Institute, United States
Ayshwarya Subramanian, Broad Institute, United States
Alex Tsankov, Broad Institute, United States
Single cell transcriptomics has emerged as a powerful tool to identify and interrogate novel cell types in homeostatic and perturbed states. Unlike bulk transcriptomics, single cell data provides resolution at the level of individual cells while working with much smaller quantities of RNA. As such, analysis of single cell RNA sequencing (scRNA-seq) data presents challenges of scale and technical noise, while providing the resolution necessary to pursue novel questions that earlier technologies did not allow.
The objective of the tutorial is to provide an overview of the laboratory and computational challenges involved in generating and analyzing scRNA-seq data. Participants will be introduced to popular molecular technologies for generating scRNA-seq data, and gain hands-on experience with existing software tools and computational methods for its analysis. The tutorial will briefly introduce approaches for preprocessing of scRNA-seq data, including demultiplexing, sequence alignment, and quality control. Then, starting from a cell x gene expression matrix, participants will learn standard methods to infer heterogeneity by identifying clusters of cells and perform analyses to assign cell identity and function. Participants will also be introduced to specialized analytical methods for exploring expression signatures of cell states, cellular differentiation trajectories, inference of cellular localization, and modern methods targeted towards better understanding of cancer biology. Analyses will be performed by executing commands in RStudio as well as leveraging newly developed point-and-click graphical R/Shiny interfaces.
Familiarity with basic RNA-Seq data analysis and working knowledge of R.
The tutorial will utilize web/cloud-based computing infrastructure with all software preinstalled, such that the only user requirement will be a personal laptop with the Google Chrome web browser installed. From within the Chrome web browser, users will access RStudio and additional web-based utilities for computation.
| Time | Presenter | Topic |
|---|---|---|
| 9:00-9:45 | Ayshwarya | Introduction - Single cell RNAseq what is it good for? |
| 9:45-10:15 | Alex | Theory I - QC and basic analysis |
| 10:15-11:00 | Ayshwarya | Hands on 1 - Basic analyses of scRNA-seq data |
| 11:00-11:15 | Coffee Break | |
| 11:15-11:40 | Matan | Theory II - Batch correction, Pathway anaylsis, Diffusion Maps |
| 11:40-12:10 | Ayshwarya, Matan | Hands on 2 - Cell-type assignment, Diffusion Maps |
| 12:10-12:40 | Tyler | Interactive tools for visualization and analysis of scRNA-seq |
| 12:40-1:00 | Matan | Specialized scRNA-seq applications, learning more, available resources, data repositories, etc |
Base URL for Rstudio instances: 35.168.111.32