Custom Analyzing immune cell communities on a massive scale with single-cell RNA-Seq

Date: This event took place on April 21, 2016

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Here we present Monocle 2, a state-of-the art software toolkit for large-scale single-cell RNA-Seq datasets. Monocle 2 helps users classify and counts cells by type, find markers for cryptic cellular subtypes or states, and dissects transitions between cellular states at ultra-high pseudotemporal resolution. The algorithm can pinpoint cellular decisions and identify genes that are regulated in response to them, helping to dissect the complex regulatory architecture governing communities of cells.

The human immune system consists of a complex community of cells that collaboratively defend the host from pathogens. During transplant rejection, donor immune cells fail to recognize the recipient’s cells as self. Dr Cole Trapnell will present preliminary work tracking the responses of diverse cell types in a model of graft-versus-host disease using single-cell RNA-Seq. Using Monocle 2, he is able to discriminate and quantify T cells in a mixed lymphocyte reaction, distinguish multiple activation outcomes, and track kinetics for genes regulated during T cell activation at pseudotemporal resolution. Monocle 2 is a scalable, robust, and easy-to-use software platform applicable to nearly any single-cell RNA-Seq experiment to unveil key cellular states and the genes that govern them.

In this webcast you will learn :

  • How the 10x single cell sequencing product works.
  • How the system may be applied to profiling a complex cell population.
  • Learn how single cell data is analysed.
  • What single cell sequencing may reveal from your samples.
  • How to integrate single cell analysis into your lab.

You will also have the opportunity to ask questions of our speaker, live during the broadcast!

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Speakers

  • Dr Cole Trapnell, University of Washington

    Dr Cole Trapnell, University of Washington

    Dr. Trapnell studies cell differentiation, reprogramming and cell-cell communication. He received his bachelor’s degree and Ph.D. in Computer Science from the University of Maryland. He trained as a postdoc at Harvard in the Department of Stem Cell and Regenerative Biology. He wrote TopHat, Cufflinks and co-developed Bowtie and Monocle.

  • Moderator: Neil Bowdler

    Neil Bowdler is a freelance science reporter. He has worked for BBC TV, Radio and Online. His work includes the BBC special ‘How to put a human on Mars’ which won a WAN-IFRA World Digital Media Award. Previously he worked as the Warsaw correspondent of The Guardian. He studied at Cambridge University.