Abstract:
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Traditional gene expression measurements were made on bulk tissue samples containing populations of cells. Recent laboratory advances have made possible the measurement of RNA levels in single cells. This new frontier offers exciting challenges and opportunities. I will describe some of these challenges and propose a new error model for single cell RNAseq that explicitly addresses the technical issues of dropout, amplification artifact, and cell size confounding. I will show that this model can be used in differential expression analysis. I will also show how addressing doe these technical biases allows us to better characterize the stochasticity of gene transcription. This is joint work with Cheng Jia, Yuchao Jiang, and Mingyao Li.
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