Cytominer: Computational Ecosystem for Image-Based Profiling
Cytominer is a versatile computational ecosystem designed to support reproducible and version-controlled processing of image-based profiling experiments. It offers tools for image acquisition, analysis, and profiling, enabling biological discovery and data release. With a focus on single-cell and aggregated profiles, Cytominer provides a structured approach to normalize and generate consensus signatures. Human accessibility to genome sequencing and data handling has facilitated innovation in biological research, emphasizing the importance of robust protocols and mature data analysis tools. The collaborative nature of Cytominer encourages contributions from the scientific community, promoting continuous improvement and exploration in image-based data processing.
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Presentation Transcript
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
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
But also a set of tools... Processing tools 1. cytominer-database 2. pycytominer 3. cytominer-eval Infrastructure tools 1. cytominer-recipe 2. cytominer-weld
Cytominer-database Pycytominer Cytominer-eval
Cytominer-database Pycytominer Cytominer-eval cytominer-recipe
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
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
