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SUMMARY:Talwar Puneet (CRC): "From Data to Insight – Fast and Reproducib
 le Analysis with R Shiny"
DTSTART;VALUE=DATE-TIME:20260601T120000Z
DTEND;VALUE=DATE-TIME:20260601T130000Z
DTSTAMP;VALUE=DATE-TIME:20260617T205215Z
UID:indico-event-601@indico.giga.uliege.be
DESCRIPTION:Abstract: Translating complex data into actionable insight req
 uires tools that are not only statistically rigorous\, but also fast\, tra
 nsparent\, and reproducible. In this talk\, From Data to Insight – Fast 
 and Reproducible Analysis with R Shiny\, I demonstrate how interactive app
 lications built in R Shiny can bridge the gap between advanced statistical
  modeling and practical decision-making. Using Shiny applications\, I will
  showcase workflows for generalized linear mixed models (GLMMs)\, featurin
 g the ability to replicate SAS results\, ensuring a seamless transition to
  open-source workflows. I will also present an interactive implementation 
 of generalized additive models for location\, scale\, and shape (GAMLSS)\,
  enabling flexible distributional modelling and intuitive diagnostics. Bey
 ond modelling\, dedicated applications for power and sensitivity analysis\
 , along with project dashboard\, demonstrate how Shiny can streamline rese
 arch workflows. The focus of this session is not only on statistical metho
 dology\, but on reproducibility\, scalability\, and cross-functional usabi
 lity. By combining robust statistical frameworks with interactive visualiz
 ation and automated reporting\, Shiny applications can accelerate analysis
  cycles\, reduce manual error\, and enhance transparency.\n\nBiosketch: Pu
 neet Talwar is a translational research scientist working at the intersect
 ion of neurobiology\, genomics\, and advanced data analytics. Trained as a
  Biotechnology Engineer\, he obtained his PhD in 2016 from the CSIR–Inst
 itute of Genomics and Integrative Biology (IGIB)\, in collaboration with t
 he Department of Neurology at the Institute of Human Behaviour & Allied Sc
 iences (IHBAS)\, New Delhi\, India. His doctoral research focused on ident
 ifying clinical\, genetic\, and proteomic biomarkers for Alzheimer’s dis
 ease using integrated clinical phenotyping\, computational\, and experimen
 tal approaches\, resulting in 14 international publications. His work high
 lighted the value of multimodal data in biomarker discovery. He also led p
 harmacogenomics research in Epilepsy as part of the Indian Genome Variatio
 n (IGV) Consortium. During his postdoctoral work at IHBAS\, he expanded in
 to neuroimaging-genetic and cognitive neurology research in Alzheimer’s 
 disease. Currently\, at GIGA-CRC Human Imaging (University of Liège)\, he
  leads multimodal studies integrating neuroimaging\, sleep physiology\, an
 d genetic risk markers to better understand mechanisms underlying neurodeg
 enerative disease progression within a multinational consortium. His exper
 tise spans translational neuroscience\, biomarker discovery\, and reproduc
 ible statistical modeling using R-based pipelines. A strong advocate of op
 en-source science\, he develops interactive Shiny applications to streamli
 ne complex analyses.\n\nInvited by: Gilles Vandewalle\n\nhttps://indico.gi
 ga.uliege.be/event/601/
LOCATION:CRC B-30/0-000 - FLUOR (Big meeting room)
URL:https://indico.giga.uliege.be/event/601/
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