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Data-analysis strategies for image-based cell profiling

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Type
Workflow
Supported image dimension
2D
3D
multi-channel
time-series
Interaction Level
Automated
Semi-automated
Description

Workflow of data-analysis strategies for image-based cell profiling.

  1. Image analysis (image correction, image segmentation, feature extraction)
  2. Image quality control
  3. Preprocessing extracted features
  4. Dimensionality reduction
  5. Single-cell data aggregation
  6. Measuring profile similarity
  7. Assay quality assessment
  8. Downstream analysis

Examples of publications where the workflow has been used at least partly:

  • Image-based multivariate profiling of drug responses from single cells
  • Phenotypic profiling of the human genome by time-lapse microscopy reveals cell division genes
  • Mapping genetic interactions in human cancer cells with RNAi and multiparametric phenotyping
  • Cell shape and the microenvironment regulate nuclear translocation of NF‐κB in breast epithelial and tumor cells
  • Genome-wide RNAi Screening Identifies Protein Modules Required for 40S Subunit Synthesis in Human Cells
  • Cell Painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes
  • Systematic morphological profiling of human gene and allele function via Cell Painting
has topic
High content screening
Download Page
http://www.nature.com/nmeth/journal/v14/n9/full/nmeth.4397.html
Reference Publication Link
http://www.nature.com/nmeth/journal/v14/n9/full/nmeth.4397.html
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