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DTSTART;TZID=America/Los_Angeles:20210402T110000
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SUMMARY:QCBio Research Seminar: Arjun Bhattacharya (Pasaniuc)
DESCRIPTION:TITLE: “Distal mediator-enriched placental transcriptome-wide association studies reveal genetic mechanisms supporting the  Developmental Origins of Health and Disease.” \nABSTRACT: As the master regulator of the intrauterine environment\, the placenta is core to the Developmental Origins of Health and Disease (DOHaD) but is understudied in large consortia of tissue-specific gene and trait regulation. We performed distal mediator-enriched transcriptome-wide association studies for 40 health outcomes across 5 categories\, using gene expression models trained from multi-omic data from the Extremely Low Gestational Age Newborn Study. I will discuss some of the novel methods we leverage in this analysis and the implications our computational and experimental results suggest on placental biology and health outcomes. \n\nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2021/03/Arjun-Bhattacharya-edited.mp4
URL:https://qcb.ucla.edu/event/qcbio-research-seminar-arjun-bhattacharya-pasaniuc/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:Research Seminars
ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2021/03/Arjun-Bhattacharya.jpg
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DTSTART;TZID=America/Los_Angeles:20210402T113000
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SUMMARY:QCBio Research Seminar: Xinzhou Ge (Li JJ)
DESCRIPTION:TITLE: “Clipper: p-value-free FDR control on high-throughput data from two conditions.” \nABSTRACT: High-throughput biological data analysis commonly involves identifying “interesting” features (e.g.\, genes\, genomic regions\, and proteins)\, whose values differ between two conditions\, from numerous features measured simultaneously. The most widely-used criterion to ensure the analysis reliability is the false discovery rate (FDR). Existing bioinformatics tools primarily control the FDR based on p-values. However\, obtaining valid p-values relies on either reasonable assumptions of data distribution or large numbers of replicates under both conditions\, two requirements that are often unmet in biological studies. To address this issue\, we propose Clipper\, a general statistical framework for FDR control without relying on p-values or specific data distributions. \nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2021/02/Xinzhou-Ge-edited.mp4
URL:https://qcb.ucla.edu/event/qcbio-research-seminars-zinzhou-ge-li-jj/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:Research Seminars
ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2021/02/Zinzhou-Ge.jpeg
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