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SUMMARY:Introduction to Integrative Analysis of Multi-Omics Data
DTSTART:20260518T080000Z
DTEND:20260520T150000Z
DTSTAMP:20260513T011600Z
UID:indico-event-1578@indico.dkfz.de
CONTACT:Daniela.Beyer@dkfz.de\;4729
DESCRIPTION:Speakers: Ilia Kats (Deutsches Krebsforschungszentrum)\n\nCour
 se Description \nThe course will introduce participants to integrative an
 alysis of multi-omics data with a focus on interpretable factor models. We
  will start with basic data handling\, covering the data formats and commo
 n workflows for multi-omics data. After a general introduction to Bayesian
  factor models\, participants will become familiar with MOFA\, the de fact
 o factor analysis method for multi-omics data to date\, as well as its ext
 ension to spatial data\, MEFISTO. We will then cover several possibilities
  to incorporate prior domain knowledge in the analysis. Each day is split 
 into a theory and a practical part. In the theory part\, the basic princip
 les behind the methods will be discussed. During the practical part partic
 ipants will run analyses on small datasets. Time permitting\, participants
  may also analyze their own data. The course targets scientists with prior
  experience in bioinformatics and single-cell data analysis and a working 
 knowledge of Python. 🎯 Learning Goals:1. Understand the principles of 
 integrative multi-omics data analysis 2. Apply interpretable factor models
  to multi-omics and single-cell datasets 🔑 Prerequisites:1. Experience 
 in single-cell data analysis\, including familiarity with cell × gene mat
 rices\, sparse matrices\, PCA\, UMAP\, and basic statistical concepts (e.g
 . probability distributions). 2. Basic proficiency in Python\, including p
 rior use of the scientific Python stack (NumPy\, SciPy\, Pandas). ℹ️ 
 🔒 Registration note:Please note that places are limited and participant
 s will be selected. We will inform you as soon as possible whether you hav
 e been allocated a place. Day 1theory - Introduction to AnnData\, MuData\,
  scanpy\, data handling - Introduction to multimodal data integration \np
 ractical - Multimodal integration with Muon (weighted nearest-neighbors)\
 , MultiVI (?) Day 2theory - Introduction to Bayesian factor models - Intro
 duction to MOFA and MEFISTO \npractical - Multimodal integration with th
 e MOFA model - Multimodal integration of spatial data with the MEFISTO mod
 el Day 3theory - Integrating prior information: MuVI\, SOFA \npractical 
 - Continuing with MEFISTO/NSF - Multimodal integration with the MuVI model
  - Combining prior information and spatial data\n\nTrainers\nDr. Ilia Kats
 \nArber Qoku\nProf. Dr. Oliver Stegle\nFlorin Walter\n\n \nVENUE\nThe tra
 ining will take place at Heidelberg University's guest house in the baseme
 nt seminar room - INF 370\, right across the DKFZ Casino.\n\nORGANIZER (le
 gally resonsible)\n \n\nThis event is subject to the DKFZ data protection
  policy \n\n \nIN COOPERATION WITH\n \n\n\nHOST\nDr. Ilia Kats\n\nhttps
 ://indico.dkfz.de/event/1578/
IMAGE;VALUE=URI:https://indico.dkfz.de/event/1578/logo-1142726090.png
LOCATION:Seminar Room of the University Guesthouse (German Cancer Research
  Center / Communication Center)
URL:https://indico.dkfz.de/event/1578/
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