Image-Based Profiling with Cytominer: Enhancing Research Reproducibility

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"Explore Cytominer, a computational ecosystem for processing image-based profiling experiments, supporting reproducibility and version control. Learn about the steps involved, tools available, and the importance of human accessibility in driving scientific innovation."

  • Cytominer
  • Image Profiling
  • Research Reproducibility
  • Computational Ecosystem
  • Scientific Innovation

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  1. Cytominer: a computational ecosystem supporting reproducible and version-controlled processing of image-based profiling experiments Gregory Way gway@broadinstitute.org October 2020 Slides: http://broad.io/cytodata-cytominer Juan Caicedo Allen Goodman Claire McQuin Tim Becker Erin Weisbart Frances Hubis Mohammad Rohban Adeniyi Adeboye Hillary Tsang Niranj Chandrasekaran Beth Cimini Anne Carpenter Shantanu Singh

  2. Not a tool, but a way of life Step 0: Step 1: Image acquisition Step 2: Step 3: Step 4: Biological discovery and data release Experimental design and sample prep Image analysis (cell segmentation and morphology feature extraction) Image profiling (data processing and normalization) Level 2 Single cell profiles Level 3 Aggregated profiles Level 4a/b Normalized profiles Level 5 Consensus signatures Level 1 Images

  3. But also a set of tools... Processing tools 1. cytominer-database 2. pycytominer 3. cytominer-eval Infrastructure tools 1. cytominer-recipe 2. cytominer-weld

  4. Cytominer-database Pycytominer Cytominer-eval

  5. Cytominer-database Pycytominer Cytominer-eval cytominer-recipe

  6. cytominer-weld

  7. Human accessibility drives innovation Access to genome sequencing Reduced cost after the Human Genome Project Genome-scale analyses more routine Access to mature RNAseq data handling/processing Robust wetlab/drylab protocols Established, benchmarked, and expanded Huge consortia address data as the new oil Sept 10, 2020: GTEx completed 10 year effort Access to software Biologists pend time studying their favorite system E.g. CellProfiler 2003 Access to data (and reproducible code) Open source/data/science Must build infrastructure and support ecosystem Spend time extracting value from data! 7

  8. Juan Caicedo Allen Goodman Claire McQuin Tim Becker Erin Weisbart Frances Hubis Mohammad Rohban Adeniyi Adeboye Hillary Tsang Niranj Chandrasekaran Beth Cimini Anne Carpenter Shantanu Singh Thank you! Contributions welcome

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