Brandon Le

UCR Genomics Core assists state with COVID variant tracking

UCR published an article by Jules Bernstein on April 6, 2022 titled “UCR Genomics Core assists state with COVID variant tracking.” The article highlights work by the IIGB Genomics and Bioinformatics Cores in sequencing and processing COVID-19 samples at UC Riverside in collaboration with the California Department of Public Health (CDPH) to help prepare the state for potential surges by new variants of the disease. Check out the original article here

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Parse Biosciences Seminar

UCR Institute for Integrative Genome Biology hosts a seminar by Parse Biosciences titled “Single Cell 3.0 - The Next Evolution of Single Cell Genomics”. Scalable single-cell RNA sequencing (scRNA-seq) up to 1 MILLION cells is readily available with the Evercode technology. The core of this approach, split-pool combinatorial barcoding, was originally demonstrated in a 2018 Science paper with SPLiT-seq and substantially improved for wide-scale adoption. Our speakers will describe the Evercode technology, its implication on single-cell experiments, and the drastic improvements achieved since the original publication.

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IIGB Seminar

UCR Institute for Integrative Genome Biology hosted a seminar titled “What Can the IIGB Cores Do For You?”. This seminar was presented by Coordinators and staff members in three major cores, discussing services and personnel that are provided to the UCR community: Genomics Core Metabolomics Core Bioinformatics Core Presentation slides for the Bioinformatics Core can be accessed here: Bioinformatics Core

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Past Workshops

A listing of past workshops held by the Bioinformatics Core Date Time Location Instructor Affiliation Description Material Oct. 12, 2017 9:00 AM - 10:30AM University Laboratory Building Neerja Katiyar UCR Module 1: (Overview and pre-processing of NGS data) Introduction to Sequencing technologies - Sanger, Illumina, PacBio Demultiplexing raw data Understanding quality scores of FASTQ files Quality control (FASTQC) How to check for contamination in your data?

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