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X-WR-CALDESC:Events for Institute for Quantitative and Computational Biosciences
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DTSTART;TZID=America/Los_Angeles:20221207T110000
DTEND;TZID=America/Los_Angeles:20221207T113000
DTSTAMP:20260517T051223
CREATED:20221109T215644Z
LAST-MODIFIED:20221202T183112Z
UID:22650-1670410800-1670412600@qcb.ucla.edu
SUMMARY:QCBio Research Seminar: Mark Xiang (Hoffmann)\, Graduate Student in Bioinformatics
DESCRIPTION:TITLE: “Heterogeneity in cell states: Is it important whether cell states are heritable or change rapidly?” \nABSTRACT: Cells of the same cell type show molecular and phenotypic heterogeneity. Is the particular cell state of a given cell heritable from one generation to the next?  Previous work in liver cancer cells indicates that the molecular network that controls cell death may change within hours\, but the data from B-cells shows that their cell state is durable and heritable.  In this project\, I address this question by formulating a model of B-cell-mediated antibody responses.  This model recapitulates the Darwinian selection process to produce high affinity antibodies against an antigen. I then test how heterogeneity in the cell states affects the antibody repertoire\, and then what the effect of heritability of those cell states might be. The preliminary results from model simulation will be presented and discussed.
URL:https://qcb.ucla.edu/event/qcbio-research-seminar-mark-xiang-hoffmann-graduate-student-in-bioinformatics/
LOCATION:Boyer Hall 159
CATEGORIES:Research Seminars
ATTACH;FMTTYPE=image/png:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2022/11/Mark_Xiang_Profile_Photo-1.png
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DTSTART;TZID=America/Los_Angeles:20221207T120000
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DTSTAMP:20260517T051223
CREATED:20221108T003622Z
LAST-MODIFIED:20221207T211458Z
UID:22610-1670414400-1670416200@qcb.ucla.edu
SUMMARY:QCBio Research Seminar: Guanao Yan (Li JJ)\, Graduate Student in Statistics
DESCRIPTION:TITLE: “scReadSim: a single-cell RNA-seq and ATAC-seq read simulator.” \nABSTRACT: Rapid advances of single-cell RNA-seq and ATAC-seq technologies have propelled the development of many computational tools\, benchmarking of which demands realistic simulators. However\, few simulators can generate sequencing reads\, and none of the existing read simulators aim to mimic real cells\, hindering the benchmarking of low-level computational tools that process reads. To fill this gap\, we propose scReadSim\, a single-cell RNA-seq and ATAC-seq read simulator that generates synthetic cells which mimic real cells. Trained on real data\, scReadSim can generate synthetic data in FASTQ and BAM formats. By deploying scReadSim on sci-ATAC-seq and 10x Multiome (ATAC+RNA) data\, we show that the scReadSim synthetic data resemble real data at both read and count levels. Moreover\, as a flexible simulator\, scReadSim enables users to arbitrarily specify open chromatin regions for the synthetic scATAC-seq reads\, and is also capable of allowing varying the cell number and sequencing depths for the synthetic data. To illustrate the versatile usage of scReadSim\, we include two exemplar benchmark studies to show that scReadSim provides unique molecular identifier (UMI) counts for benchmarking scRNA-seq deduplication tools and can accommodate user-specified open chromatin regions (“ground truths”) to generate single-cell ATAC-seq data. Our benchmark applications of scReadSim show that cellranger is a preferred scRNA-seq deduplication tool\, and MACS3 achieves top performance in scATAC-seq peak calling. \n\nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2022/11/video1156562562.mp4
URL:https://qcb.ucla.edu/event/qcbio-research-seminar-guanao-yan-li-jj-graduate-student-in-statistics/
LOCATION:Boyer 159\, 611 Charles E. Young Dr. E.\, Los Angeles\, CA\, 90095\, United States
CATEGORIES:Research Seminars
ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2022/11/Guanao.jpeg
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