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DTSTAMP:20260407T181224Z
UID:3689342c-8883-4f07-a33a-911df5305f77
DTSTART:20260518T070000Z
DTEND:20260520T150000Z
DESCRIPTION:Educators: \nIlia Kats\, Arber Qoku\, Florin Walter (HD-HuB)\n\
 nDate: \n2026-05-18 - 2026-05-20\n\nLocation: \nDKFZ Heidelberg (Im Neuenh
 eimer Feld 370\, basement\, seminar room)\n\nContents:\nThe course will in
 troduce participants to integrative analysis of multi-omics data with a fo
 cus on interpretable factor models. We will start with basic data handling
 \, covering the data formats and common workflows for multi-omics data. Af
 ter a general introduction to Bayesian factor models\, participants will b
 ecome familiar with MOFA\, the de facto factor analysis method for multi-o
 mics data to date\, as well as its extension to spatial data\, MEFISTO. We
  will then cover several possibilities to incorporate prior domain knowled
 ge in the analysis. Each day is split into a theory and a practical part. 
 In the theory part\, the basic principles behind the methods will be discu
 ssed. During the practical participants will run analyses on small dataset
 s. Time permitting\, participants may also analyze their own data.The cour
 se targets scientists with prior experience in bioinformatics and single-c
 ell data analysis and a working knowledge of Python.\n\nLearning goals:\n\
 nUnderstand the principles of integrative multi-omics data analysis\nApply
  interpretable factor models to multi-omics and single-cell datasets\nPrer
 equisites:\n\nExperience in single-cell data analysis\, including familiar
 ity with cell × gene matrices\, sparse matrices\, PCA\, UMAP\, and basic 
 statistical concepts (e.g. probability distributions).\nBasic proficiency 
 in Python\, including prior use of the scientific Python stack (NumPy\, Sc
 iPy\, Pandas).\nKeywords:\nMulti-omics\, single-cell\, MOFA\, MEFISTO\, Mu
 VI\n\nTools:\nMOFA-FLEX
LOCATION:Deutsches Krebsforschungszentrum (DKFZ)\, 280 Im Neuenheimer Feld
SUMMARY:Integrative Analysis of Multi-Omics Data
URL;VALUE=URI:https://www.denbi.de/training-courses-2026/2046-integrative-a
 nalysis-of-multi-omics-data
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