For the full class schedule, descriptions, and to register, please visit the UConn Recreation website (https://recreation.uconn.edu/group-fitness-schedule/).

Interpersonal Group for Undergraduate Students Undergraduate Students Interpersonal Groups focuses on promoting emotional wellbeing as you balance academics, relationships, family, and personal responsibilities. Groups offer a supportive confidential space to share your concerns, practice skills and get feedback.To join this group therapy session, please call SHaW at 860-486-4700 (tel:860-486-4705). This session is held by Maritza Lugo-Stalker,  (https://studenthealth.uconn.edu/person/maritza-lugo-stalker/)   For many concerns that students face – like overwhelming stress, anxiety, difficult relationships, depression, academic difficulties, and more – group therapy is the best option for support and healing. Facilitated by Student Health and Wellness (SHaW) counselors, our therapy groups encourage peer support, promote emotional wellbeing, and increase a felt sense of connection. Participants often find that they feel less alone in their struggles, and walk away with newfound support and ideas for coping.

Janet L. Pritchard will discuss her current creative research project in landscape photography, Abiding River: Connecticut River Views & Stories. As a landscape photographer, her reliance on research sets her work apart. As a UCHI Fellow this year, Pritchard is drafting her project as a book. Fellowship time allows her to keep more balls in the air as she mentally juggles thousands of photographs to decide which to include against what she needs to finish. The nature of this landscape is different than that of her previous project on Yellowstone National Park; thus, the river book's structure must reflect that. Her presentation will trace work this fall as she immerses herself in the process.Before photography, Janet L. Pritchard was an outdoor education instructor and spent her youth between the Northeast and Rocky Mountain West in the US. She describes herself as geographically bilingual. Her methodology, described as historical empathy, relies on archival materials to guide her depictions of complex landscapes as expressions of time and place, situating landscapes at the intersection of nature and culture. Pritchard was awarded a John Simon Guggenheim Fellowship in 2019. She exhibits widely, and her recent project on Yellowstone National Park, titled More than Scenery: Yellowstone, an American Love Story, was published in 2022. She is a professor and graduate advisor in the Department of Art & Art History at the University of Connecticut.Joscha Jelitzki is a scholar of German Jewish literature, and a PhD candidate in German and Judaic Studies at UConn at the Department of Literatures, Cultures, and Languages. Before joining UCHI as the Richard Brown Dissertation Fellow, he completed his research in Vienna as the 2024 Franz Werfel Fellow. He previously studied in Berlin, Frankfurt (Oder), and Jerusalem, and worked as an assistant from 2016–2019 for the critical edition of the works of Hannah Arendt. His focus is on modern German and Austrian Jewish literature and thought, theories of sexuality and secularization. He has published articles on Martin Buber and literature, the biblical figure of Job in modern Jewish literature, and on German-Jewish gangsta-rap.

The event will be held on December 4th from 4-6pm in the Student Union Room 304ABC. For more information, visit the Office of Sustainability website at https://sustainability.uconn.edu (https://sustainability.uconn.edu)This is an Honors Event. See tags below for category information. #UHLevent11000

Synthetic control removes spurious discoveries from double dipping in scRNA-seq post-clustering analyses   Presented by Dongyuan Song, Asst. Professor, Department of Genetics and Genome Sciences, University of Connecticut School of MedicineWednesday, December 4, 2024, 4:00 PM, AUST 202 Coffee will be served at 3:30 pm in the Noether Lounge (AUST 326)Webex Meeting Link (https://uconn-cmr.webex.com/uconn-cmr/j.php?MTID=m43de287e0bb19ad8fd185dd7379ffe69)Abstract: In typical single-cell RNA-seq (scRNA-seq) analyses, it is common to cluster cells into putative types and then employ statistical differential expression (DE) tests to identify genes that are differentially expressed across these clusters. This process, which involves using the same data twice, is known as "double dipping" and can lead to an inflated false discovery rate (FDR) in identifying cell-type marker genes. While methods have been proposed to address this issue, existing approaches assume that genes are all independent, which is unrealistic for real scRNA-seq datasets. Therefore, these methods fail to effectively control FDR in real data analyses. Here, we introduce ClusterDE, a novel post-clustering DE method designed to control FDR of identified DE genes, even under a gene-gene dependency structure. The core of ClusterDE involves generating synthetic null data as an in silico negative control that contains only one cell type. Through extensive simulations and real data analyses, we demonstrate that existing methods fail to control the FDR due to their unrealistic assumptions. Conversely, ClusterDE consistently manages to control the FDR when its assumptions are satisfied, which aligns with the conditions of most real datasets.Bio: Dr. Dongyuan Song is the new assistant professor of Genetics and Genome Sciences at UConn Health. He got his Ph.D. in Bioinformatics, advised by Professor Jingyi Jessica Li in the Department of Statistics and Data Science, UCLA. Before that, he obtained an M.S. in Computational Biology from the Department of Biostatistics at Harvard School of Public Health, advised by Professor Rafael Irizarry at Dana-Farber Cancer Institute. His research interest is developing novel statistical methods for analyzing single-cell and spatial omics data.