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X-WR-CALDESC:Events for Institute for Quantitative and Computational Biosciences
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DTSTART;TZID=America/Los_Angeles:20210702T140000
DTEND;TZID=America/Los_Angeles:20210702T143000
DTSTAMP:20260518T013450
CREATED:20210630T133436Z
LAST-MODIFIED:20210720T145203Z
UID:18304-1625234400-1625236200@qcb.ucla.edu
SUMMARY:QCBio Research Seminar in collaboration with B.I.G. Summer: Jingyi Jessica Li
DESCRIPTION:TITLE: “Applications of generalized additive models and copulas to single-cell RNAseq computational method development: PseudotimeDE and scDesign2” \nABSTRACT:\nPart 1: PseudotimeDE: inference of differential gene expression along cell pseudotime with well-calibrated p-values from single-cell RNA sequencing data \nTo investigate molecular mechanisms underlying cell state changes\, a crucial analysis is to identify differentially expressed (DE) genes along the pseudotime inferred from single-cell RNA-sequencing data. However\, existing methods do not account for pseudotime inference uncertainty\, and they have either ill-posed p-values or restrictive models. Here we propose PseudotimeDE\, a DE gene identification method that adapts to various pseudotime inference methods\, accounts for pseudotime inference uncertainty\, and outputs well-calibrated p-values. Comprehensive simulations and real-data applications verify that PseudotimeDE outperforms existing methods in false discovery rate control and power. \nPart 2: scDesign2: a transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured \nA pressing challenge in single-cell transcriptomics is to benchmark experimental protocols and computational methods. A solution is to use computational simulators\, but existing simulators cannot simultaneously achieve three goals: preserving genes\, capturing gene correlations\, and generating any number of cells with varying sequencing depths. To fill this gap\, we propose scDesign2\, a transparent simulator that achieves all three goals and generates high-fidelity synthetic data for multiple single-cell gene expression count-based technologies. In particular\, scDesign2 is advantageous in its transparent use of probabilistic models and its ability to capture gene correlations via copulas. \n\nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2021/06/Jessica-Li-7.2.21-edited.mp4
URL:https://qcb.ucla.edu/event/qcbio-research-seminar-in-collaboration-with-b-i-g-summer-jingyi-jessica-li/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:Research Seminars
ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2021/06/7.2.21-Jessica-Li.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20210709T140000
DTEND;TZID=America/Los_Angeles:20210709T143000
DTSTAMP:20260518T013450
CREATED:20210630T133900Z
LAST-MODIFIED:20210630T133904Z
UID:18309-1625839200-1625841000@qcb.ucla.edu
SUMMARY:QCBio Research Seminar in collaboration with B.I.G. Summer: Paivi Pajukanta
DESCRIPTION:TITLE: “Integrating single cell omics and deep phenotype data to discover genes underlying cardiometabolic disorders” \nABSTRACT: Obesity predisposes to cardiometabolic disorders (CMDs)\, such as type 2 diabetes\, multiple dyslipidemias\, and non-alcoholic fatty liver disease (NAFLD). We are interested in how cell-type level gene expression contributes to CMDs and impacts cross talk between cardiometabolic tissues. We hypothesized that obesity-induced inflammatory changes in adipose tissue alter the cell-type composition and key functions of this obesity responsive tissue\, which drives ectopic deposition of fat into the liver. To this end\, we have generated adipose and liver single nucleus RNA-seq reference data sets\, and leveraged the cell-type markers identified in these reference data sets to decompose cell-type proportions in bulk adipose tissue and liver RNA-seq cohorts. This decomposition has allowed us to identify which adipose tissue and liver cell-types are associated with human CMDs. Moving forward\, our goal is to discover genetic and biological mechanisms underlying CMDs at the single cell resolution.
URL:https://qcb.ucla.edu/event/qcbio-research-seminar-in-collaboration-with-b-i-g-summer-paivi-pajukanta/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:Research Seminars
ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2021/06/paivi-copy.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20210716T140000
DTEND;TZID=America/Los_Angeles:20210716T143000
DTSTAMP:20260518T013450
CREATED:20210709T221802Z
LAST-MODIFIED:20210720T145037Z
UID:18333-1626444000-1626445800@qcb.ucla.edu
SUMMARY:QCBio Research Seminar in collaboration with B.I.G. Summer: Hilary Coller
DESCRIPTION:TITLE: “Is there a Quiescence Histone Code?” \nABSTRACT: Many of the cells in our bodies are quiescent\, that is\, temporarily not dividing. Under certain physiological conditions such as during tissue repair and maintenance\, quiescent cells receive the appropriate stimulus and are induced to enter the cell cycle. The ability of cells to successfully transition into and out of a quiescent state is crucial for many biological processes including wound healing\, stem cell maintenance\, and immunological responses. Histone modifications have been shown to play a role in chromatin packing and accessibility\, nucleosome mobility\, gene expression\, and chromosome arrangement. We have been testing the role of the H4K20me3 mark as a regulator of quiescence in cultured cells and in mice. Our data implicate this histone mark in chromatin compaction\, cell proliferation\, chromosome positioning\, expression of critical cell cycle regulatory proteins\, and mouse growth during development. Moving forward\, our goal is to test whether H4K20me3 is part of a histone code that ensures proper chromosome compaction and positioning to establish and maintain a quiescent state.
URL:https://qcb.ucla.edu/event/qcbio-research-seminar-in-collaboration-with-b-i-g-summer-hilary-coller/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:Research Seminars
ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2021/07/7.16.21-Hilary-Coller-V2.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20210724T140000
DTEND;TZID=America/Los_Angeles:20210724T143000
DTSTAMP:20260518T013450
CREATED:20210720T144701Z
LAST-MODIFIED:20210726T170612Z
UID:18460-1627135200-1627137000@qcb.ucla.edu
SUMMARY:QCBio Research Seminar in collaboration with B.I.G. Summer: Harold Pimentel
DESCRIPTION:TITLE: “Model driven design and analysis of quantitative phenotype screens” \nABSTRACT: Increasingly\, CRISPR screens are coupled with flow cytometry (FACS) to sort cells and quantify the \nimpact of genetic perturbations on a continuous phenotype. While FACS provides much more \nquantitative information than simple survival screens\, it introduces a number of experimental and \nstatistical challenges. Furthermore\, as experimentalists push these screens in limited primary cells \nor in vivo\, they lack principled guidelines on how experimental parameters including multiplicity of \ninfection\, guide RNA coverage\, or FACS bin cutoffs affect statistical power. We present models for \nboth experimental design and inference of gene regulation in these screens. We show that \ncommonly used parameters are far from optimal and screens can be performed with a 20 times \nreduction in cells at comparable accuracy. Our inference procedure models biological replicates\, \ninfers the latent protein distribution\, and infers experimental parameters. Together these analyses \nprovide a holistic framework for designing and analyzing highly parallel FACS screens. \nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2021/07/Harold-Pimentel-edited.mp4
URL:https://qcb.ucla.edu/event/qcbio-research-seminar-in-collaboration-with-b-i-g-summer-harold-pimentel/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:Research Seminars
ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2021/07/7.23.21-Harold-Pimentel.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20210730T140000
DTEND;TZID=America/Los_Angeles:20210730T143000
DTSTAMP:20260518T013450
CREATED:20210720T144936Z
LAST-MODIFIED:20210730T223229Z
UID:18464-1627653600-1627655400@qcb.ucla.edu
SUMMARY:QCBio Research Seminar in collaboration with B.I.G. Summer: David Wong
DESCRIPTION:TITLE: “Salivary exRNA for Gastric Cancer Detection” \nABSTRACT: Biomarkers are needed for non-invasive early detection of gastric cancer (GC). We investigated whether salivary extracellular RNA (exRNA) biomarkers can be used as an efficient and economical clinical evaluation tool for GC. Unstimulated whole saliva samples were prospectively collected from 294 subjects (163 GC and 131 non-GC controls) who underwent endoscopic evaluation at the Samsung Medical Center in Korea. The salivary transcriptomes of 63 GC and 31 non-GC controls were profiled\, and mRNA biomarker candidates were verified with RT-qPCR. In parallel\, microRNA biomarkers were profiled and verified with saliva samples from 10 GC and 10 controls. Candidate biomarkers were validated with RT-qPCR in an independent cohort of 100/100 saliva samples from GC and non-GC patients. Validated individual markers were configured into a best performance panel. We identified 30 mRNA and 15 miRNA candidates whose expression pattern associated with the presence of gastric cancer. Among them\, 12 mRNA and 6 miRNA candidates were verified with the discovery cohort by RT-qPCR and further validated with the independent cohort (n=200). The configured biomarker panel consisted of 3 mRNAs (SPINK7\, PPL and SEMA4B) and 2 miRNAs (miR-140-5p and miR-301a)\, which were all significantly down-regulated in GC group\, yielded an AUC of 0.81 (95%CI\, 0.72-0.89). When combined with demographic factors\, the performance of the panel reached an AUC of 0.87 (95%CI\, 0.80-0.93). We have discovered and validated a panel of salivary exRNA biomarkers with credible clinical performance for the detection of GC. Our study demonstrates the credential of salivary exRNA biomarker as a potential screening and risk-assessing tool for GC. \nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2021/07/David-Wong-edited.mp4
URL:https://qcb.ucla.edu/event/qcbio-research-seminar-in-collaboration-with-b-i-g-summer-david-wong/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:Research Seminars
ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2021/07/7.30.21-David-Wong.jpg
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