DAMAGES: A Method for Predicting Rare Disease Risk Genes
Looking for distinctive gene expression patterns in different brain cell types offers a more efficient way to search for genetic alterations implicated in autism and reveals a molecular signature of the disorder.
Scientists Quantify Genetic Connections between Cancer and Developmental Disorders
A study led by Yufeng Shen suggests that cancer data could be used to pinpoint rare, damaging genetic alterations that increase the risk of developmental syndromes like autism.
Graduate Course Focuses on Foundations of Deep Sequencing
The new team-taught course provides an understanding of both the experimental principles of next-generation sequencing technologies and key statistical methods for analyzing the data they produce.
Mechanism of Kidney Transplant Tolerance Discovered
A new statistical approach for tracking expansion of rare T cell clones developed in Yufeng Shen's lab could make it possible to predict transplant rejection and provide evidence to guide the use of immuno- suppressive drugs.
Improving Single-Cell RNA-Seq at the Columbia Genome Center
Using the Fluidigm C1 System, Columbia researchers are developing methods for addressing the technical challenges of single-cell sequencing, and have begun generating some exciting data.