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DTSTART;TZID=America/Los_Angeles:20230324T120000
DTEND;TZID=America/Los_Angeles:20230324T123000
DTSTAMP:20260517T024711
CREATED:20230307T193641Z
LAST-MODIFIED:20230327T173940Z
UID:24514-1679659200-1679661000@qcb.ucla.edu
SUMMARY:QCBio Research Seminar: Dongyuan Song (Li JJ)\, Grad Student\, Bioinformatics IDP
DESCRIPTION:TITLE: “ClusterDE: a post-clustering differentially expressed (DE) gene identification method robust to false-positive inflation caused by double-dipping” \nABSTRACT: In typical single-cell RNA-seq data analysis\, first\, a clustering algorithm is applied to cluster cells; then\, a statistical method is used to identify the differentially expressed (DE) genes between the cell clusters. However\, this common procedure uses the same data twice\,  an issue known as “double dipping”: the same gene expression data are used to define cell clusters and DE genes\, leading to false-positive DE genes even when the cell clusters are spurious. To overcome this challenge\, we propose ClusterDE\, a post-clustering DE method for controlling the false discovery rate (FDR) regardless of clustering quality. The core idea of ClusterDE is to generate in silico negative control data with only one cluster\, which can be used in contrast to real data for evaluating the whole clustering+DE procedure. Using comprehensive simulation and real data analysis\, we show that ClusterDE can not only has solid FDR control but also finds cell-type marker genes that are biologically meaningful. ClusterDE is fast\, transparent\, and adaptive to a wide range of clustering methods and statistical tests. \n\nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2023/03/Dongyuan-Song-32423.mp4
URL:https://qcb.ucla.edu/event/qcbio-research-seminar-dongyuan-song-li-jj-grad-student-bioinformatics-idp/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:Research Seminars
ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2023/03/UCLA.jpg
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DTSTART;TZID=America/Los_Angeles:20230324T123000
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DTSTAMP:20260517T024711
CREATED:20230319T153305Z
LAST-MODIFIED:20230327T174010Z
UID:24633-1679661000-1679662800@qcb.ucla.edu
SUMMARY:QCBio Research Seminar: Nicholas Wang (Boutros)\, Grad Student\, Bioinformatics
DESCRIPTION:TITLE: “Germline structural variants shape prostate cancer clinical and molecular evolution.” \nABSTRACT: Inherited genetic variation profoundly influences cancer risk and outcome. While the impact of germline single nucleotide polymorphisms has been well-studied in several cancer types\, the effects of germline structural variants (gSVs) on cancer biology and clinical outcomes is largely unknown. From our cohort of 300 men with localized\, intermediate risk prostate cancer\, we identified 6\,003 gSVs present in at least 3% of patients\, with 48 associated with recurrent somatic alterations or clinical outcome. Of these\, ~50% associated with expression of nearby genes or intersected with exons or regulatory regions. Using external cohorts\, we validated three gSVs that were strongly associated with poor clinical outcomes\, including an inversion at chr14q24.1 present in ~20% of patients. Notably\, a strong synergistic effect on outcome was observed in patients with somatic TP53 alterations or high genomic instability\, defining a new aggressive prostate cancer subtype with chr14INV as a novel\, recurrent biomarker. \nhttps://qcb.ucla.edu/wp-content/uploads/sites/14/2023/03/Nicholas-Wang-32423.mp4
URL:https://qcb.ucla.edu/event/qcbio-research-seminar-nicholas-wang-boutros-grad-student-bioinformatics-p/
LOCATION:ZOOM\, CA\, United States
CATEGORIES:Research Seminars
ATTACH;FMTTYPE=image/jpeg:https://wp-misc.lifesci.ucla.edu/qcb/wp-content/uploads/sites/14/2023/03/Nicholas-Wang.jpg
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