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Statistics or biology: the zero-inflation controversy about scRNA-seq data

Single-cell RNA sequencing (scRNA-seq) technologies have revolutionized biomedical sciences by enabling genome-wide profiling of gene expression levels at an unprecedented single-cell resolution. A distinct characteristic of scRNA-seq data is the vast proportion of zeros unseen in bulk RNA-seq data. Researchers view these zeros differently: some regard zeros as biological signals representing no or low gene expression, while others regard zeros as false signals or missing data to be corrected.

Single-cell RNA-seq reveals cell type–specific molecular and genetic associations to lupus

Single-cell sequencing is transforming our understanding of complex tissues but their application to large population cohorts has been limited. Large sample sizes are particularly important for studying complex autoimmune diseases such as lupus where patients present a variety of symptoms and may respond very differently to current treatments. By using genetic information encoded in each single cell, we’ve previously developed a method called mux-seq to enable single-cell profiling of large populations. 

UCLA Scientists Develop New Algorithms to Study Genomic Data

UCLA Samueli Newsroom

UCLA computer scientists and genetics specialists in collaboration with their colleagues from several other institutions have developed a new genomic data computational method. Their improved algorithms can analyze genomic data up to 1,800 times faster than previous techniques, making it possible to analyze the genetic information of 1 million individuals in just one day.

UCLA SwabSeq funded by BARDA to develop “agnostic” virus test

Biomedical Advanced Research and Development Authority (BARDA)’s Division of Research, Innovation and Ventures (DRIVe) is collaborating with multiple industries and academic partners, including the University of California, Los Angeles, to advance the ability to quickly respond to public health emergencies with a new diagnostic capability that covers all existing and new respiratory RNA viruses in a single test.

UCLA Health researchers analyze LA’s ‘stunningly diverse’ genetic ancestry to bring ethnic equity to precision medicine

UCLA Health | JLMillman@mednet.ucla.edu

Analyzing genetic ancestry data from a large genomic repository – the UCLA ATLAS Precision Health Biobank – researchers have found a highly diverse patient population that’s consistent with the global diversity of Los Angeles – one of the most ethnically diverse cities in the world and an ideal location to pursue personalized, precision medicine for underrepresented populations.

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