ASN's Mission

ASN leads the fight to prevent, treat, and cure kidney diseases throughout the world by educating health professionals and scientists, advancing research and innovation, communicating new knowledge, and advocating for the highest quality care for patients.

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Kidney Week

Advances in Research Conference: Single-Cell Biology

Support is provided by an educational grant from Chinook Therapeutics, Inc.

Course Description

Rapid technological advances in single-cell sequencing have enabled multimodal profiling of different aspects of a cell, including its transcriptome, genome, and epigenome and their spatial organization. These single-cell datasets have enhanced our understanding of cell heterogeneity, developmental dynamics, and the gene regulatory networks that drive cell identity. However, the rapid pace of development of single-cell approaches poses challenges for researchers who want to apply these methods. This program provides a cutting-edge review of all major single-cell technologies and their application so that investigators can better understand how to use these techniques in their own research.

All presentations will be available on-demand starting one week prior to the program through December 4. This program will feature four live, interactive sessions on October 20-21 which will be available on-demand after the live sessions. Note: There is no syllabus.

ASN designates this blended learning activity for a maximum of 15.5 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity. (The credits total has been updated based on actual time.)

Course Objective(s)

Upon completion of the program, the participant will be able to: 1) describe the strengths and limitations of current single-cell-omic technologies; 2) formulate strategies to apply spatial transcriptomics to kidney research; 3) distinguish the types of information generated by single-cell transcriptomic, epigenomic, metabolomic, and proteomic studies; and 4) apply coding procedures to analyze single-cell RNA sequencing datasets using R studio.

Course Chair(s)

  • Benjamin D. Humphreys, MD, PhD, FASN
  • Katalin Susztak, MD, PhD


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