BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Institute for Quantitative and Computational Biosciences - ECPv6.16.2//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://qcb.ucla.edu
X-WR-CALDESC:Events for Institute for Quantitative and Computational Biosciences
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/Los_Angeles
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20220313T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20221106T090000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20230312T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20231105T090000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20240310T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20241103T090000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230623T163000
DTEND;TZID=America/Los_Angeles:20230623T170000
DTSTAMP:20260517T000150
CREATED:20230621T151413Z
LAST-MODIFIED:20230627T233954Z
UID:24821-1687537800-1687539600@qcb.ucla.edu
SUMMARY:BIG Summer Research Seminar: Brunilda Balliu\, Assistant Professor in the Departments of Pathology & Laboratory Medicine and Computational Medicine at UCLA
DESCRIPTION:TITLE: “FastGxC: a statistical framework for mapping context-specific regulatory variants using bulk and single-cell RNA-seq data.” \nABSTRACT: Recent studies suggest that context-specific eQTLs underlie genetic risk factors for complex diseases. However\, methods for identifying them are still nascent\, limiting their comprehensive characterization and downstream interpretation of disease-associated variants. In this talk\, I will introduce FastGxC\, a method to efficiently and powerfully map context-specific eQTLs by leveraging the correlation structure of bulk multi-tissue and single-cell RNA-seq studies. We applied FastGxC to simulated and real bulk and single-cell RNA-Seq data sets and show that FastGxC is orders of magnitude more powerful and computationally efficient than existing eQTL mapping approaches\, making previously yearlong computations possible in minutes. In addition\, FastGxC provides a three-fold increase in precision to identify relevant tissues and cell types for GWAS variants than standard eQTL mapping approaches. \n\nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2023/06/Brunilda-Balliu-62323.mp4
URL:https://qcb.ucla.edu/event/big-summer-research-seminar-brunilda-balliu-assistant-professor-in-the-departments-of-pathology-laboratory-medicine-and-computational-medicine-at-ucla/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:Research Seminars
ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2023/06/Brunilda-Balliu-PhD-11r5x7.jpg
END:VEVENT
END:VCALENDAR