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SUMMARY:Single cell RNA-seq: how to adapt Seurat to analyze your dataset – *Peer-to-Peer* Spring Season\, 2023
DESCRIPTION:Registration Required -  *Attendance in person*\n\nWelcome to 
 the Peer-to-Peer Teaching Spring Season 2023. These sessions are taught by 
 our own community members to fill knowledge gaps and keep up with the 
 accelerated pace at which bioinformatics grows as well as other data 
 analysis methodologies. \n\nThis session dedicated to single cell RNAseq 
 data analysis\, will be led by our colleague Ana Lledo Delgado\, MD. who is 
 a postdoctoral associate in the Dr. Herold lab at the Immunobiology 
 Department.\n\n \n\nDescription:\n\nOmics data is transforming the way we 
 understand science and opening new insights to many different scientific 
 fields. Single cell RNA sequencing (scRNA-seq) allows us to analyze gene 
 expression patterns in individual cells\, providing a more detailed 
 understanding of the cellular heterogeneity and diversity within a tissue 
 or organism.\n\nSeurat is a widely used R package developed to accomplish 
 the full analysis of annotated scRNA-seq data. Experiments with complex 
 designs (e.g.\, multiple conditions\, time points\, intersection between 
 conditions) can sometimes be difficult to analyze with this established 
 package. In this workshop you will learn how to overcome some of these 
 difficulties and fine-tune the original Seurat code\, so it may address the 
 specificities of your own experimental design.\n\n \n\nYou will learn how 
 to:\n\n process human PBMCs with different hashtag using Seurat 
 package.\n\n add different metadata to the main data frame to analyze 
 multiple conditions.\n\n follow the main steps in the data process before 
 comparing different conditions (normalization\, scale\, find clusters\, run 
 UMAP\, perform batch correction…)\n\n join different files to have a 
 unique file to analyze.\n\n make different clusters or subclusters to 
 validate or to discover new information.\n\n find the differentially 
 expressed genes based on the conditions that you want to define.\n\n 
 \n\nRequirements: this workshop will be a demonstration. No need to bring 
 your laptop. Previous knowledge of R/Rstudio is helpful but not necessary. 
 Registration is required to attend.\n\n
LOCATION:C-103\, SHM\, 333 Cedar St\, New Haven\, 06510\, Medical School
ORGANIZER;CN="Vermetha Polite":MAILTO:vermetha.polite@yale.edu
CATEGORIES:Bioinformatics, Peer-to-Peer Teaching
CONTACT;CN="Vermetha Polite":MAILTO:vermetha.polite@yale.edu
STATUS:CONFIRMED
UID:LibCal-10248513
URL:https://schedule.yale.edu/event/10248513
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