Help & Reference — starfish documentation
  • Installation
  • User Guide
  • Examples
  • API
  • More
      • Installation
        • Using virtual environments
        • Installing starfish
        • Installing starfish on Windows
        • Jupyter notebook
      • User Guide
        • Formatting Data
        • Loading Data
        • Manipulating Images
        • Correcting Images
        • Enhancing Signal & Removing Background Noise
        • Normalizing Intensities
          • Whether to normalize
          • How to normalize
            • Normalizing Intensity Distributions
            • Normalizing Intensity Values
        • Finding and Decoding Spots
          • Spot-Based Decoding
          • Pixel-Based Decoding
          • What Decoding Pipeline Should I Use?
        • Segmenting Cells
          • Thresholding and Watershed
          • Manually Defining Cells
          • Machine-Learning Methods
        • Assigning Spots to Cells
        • Assessing Performance Metrics
        • Other Utilities
        • Feature Identification and Assignment
      • Tutorials and Examples
        • Quick Start
          • Quick Start
            • Prerequisites
            • Starfish Pipeline
        • Data Formatting
          • Format Structured Data
            • Create some synthetic data to form into a trivial experiment.
            • Directory contents
            • Contents of coordinates.csv
            • Convert structured data into SpaceTx Format
            • Output directory contents
            • Merge outputs by modifying experiment.json
            • Don’t forget to replace the fake codebook.json
            • Load up the experiment
          • Formatting with TileFetcher
            • Create some synthetic data to form into a trivial experiment.
            • Directory contents
            • Define FetchedTile subclass
            • Define TileFetcher subclass
            • Run write_experiment_json()
            • Don’t forget to replace the fake codebook.json
            • Load up the experiment
        • Data Formatting Examples Using TileFetcher
          • Format BaristaSeq
          • Format In Situ Sequencing Mouse x Human Experiment
          • Format In-Situ Sequencing Data
          • Format Imaging Cytof Data
          • Format MERFISH data
          • Format SeqFISH Data
          • Format osmFISH Data
          • Format STARmap data
        • Data Loading
          • Loading Data
            • Loading Experiments
            • Loading Fields of View
            • Loading Images
          • Loading Data through TileFetchers
            • Create some synthetic 5D data
            • Write as a series of 3D tiffs.
            • Now build a FetchedTile and TileFetcher based on this data.
            • Load the data as an ImageStack.
        • Tutorials
          • Feature Identification
          • Segmenting Cells
          • Assigning Spots to Cells
          • Tissue Corrections
          • Removing autofluorescence
            • Clipping
          • Image Registration
          • Image Corrections
          • Illumination Correction
          • Chromatic Aberration
          • Deconvolution of Optical Point Spread Functions
            • Learning the PSF from image data
          • Example Image Correction Pipeline
          • Loading ImageJ ROI Sets
          • Image Manipulations
          • Cropping
            • Crop on Load
            • Selecting Images
          • Projection
          • Normalizing Intensity Values
          • Pixel-Based Decoding
          • Using ilastik in starfish
          • Calling Out to ilastik Trained Pixel Classifier
          • Loading ilastik Probability Map
          • Transforming Probability Map to Masks
          • Assigning Spots to Cells
          • Normalizing Intensity Distributions
          • Spot-Based Decoding
            • Spot Finding
            • Trace Building
            • Spot Decoding
            • Comparison of FindSpotsAlgorithms
          • Watershed Segmentation
          • Example of Custom Watershed Pipeline
          • Pre-defined Watershed Segmentation Pipeline
        • How Tos
          • Visualizing Data
            • Start with the quick start tutorial
            • Using the GUI
            • Adding additional layers
            • Naming your layers with napari commands
            • Directly visualizing SpotFindingResults
          • Finding Spots with LocalMaxPeakFinder
          • Plotting Intensity Distribution
          • Showing Image of ImageStack Plane
          • Finding Spots with TrackpyLocalMaxPeakFinder
          • Decoding Spots with SimpleLookupDecoder
          • Clipping
          • Finding Spots with BlobDetector
          • Clipping Value To Zero
          • Decoding Spots with PerRoundMaxChannel
          • Assessing SpotFindingResults
          • When to Use Each TraceBuildingStrategies
          • Clipping Percentile To Zero
          • Matching Histograms
            • How to match histograms across channels
            • How to match histograms across channels and rounds
            • How to match histograms across z-planes
            • Risk of using MatchHistograms inappropriately
          • Decoding Spots with MetricDistance
        • Example Pipelines
          • ISS Processing Workflow
          • Processing sequential smFISH in 3D
            • Define image filters
            • Define a spot detection method
            • Construct the pipeline
            • Load data, run pipeline, display results
          • STARmap processing example
            • Visualize raw data
            • Visualize the codebook
            • Registration
            • Equalize channel intensities
            • Find spots
            • Decode spots
          • Reproduce published osmFISH results with starfish
            • Load Data into starfish from the cloud
            • Filter and visualize data
            • Decode the processed data into spatially resolved gene expression
            • Compare to pySMFISH peak calls
          • Reproduce published MERFISH results with starfish
            • Load Data
            • Visualize codebook
            • Visualize raw data
            • Filter and scale raw data before decoding into spatially resolved gene expression
            • Visualize processed data
            • Decode the processed data into spatially resolved gene expression profiles
            • Compare to results from paper
            • Visualize results
          • BaristaSeq Processing Workflow
            • Load Data
            • Select one plane
            • Register the data
            • Project into 2D
            • Correct Channel Misalignment
            • Remove Registration Artifacts
            • Correct for bleed-through from Illumina SBS reagents
            • Remove image background
            • Scale images to equalize spot intensities across channels
            • Detect Spots
          • Reproduce DARTFISH results with starfish
            • Load Data
            • Visualize codebook
            • Visualize raw data
            • Filter and scale raw data before decoding into spatially resolved gene expression
            • Decode the processed data into spatially resolved gene expression profiles
            • Compare to benchmark results
            • Visualize results
            • Parameter and QC analysis
      • Help & Reference
        • Data Model
          • Field of View
          • Processing Model
          • Dual Coordinate Systems
          • Next Steps
        • SpaceTx Format
          • SpaceTx Image Format Specification
            • Introduction
            • Format Specification
            • Experiment
            • Manifest
            • Field of View
            • Codebook
          • JSON Schemas
            • Validation
              • Usage
              • Examples
        • Available datasets
        • Working with Starfish Outputs
          • Output Formats
            • IntensityTable
              • Data
              • Table Metadata
              • Feature Metadata
              • Implementation
              • Serialization
            • ExpressionMatrix
              • Data
              • Metadata
              • Implementation
              • Serialization
            • DecodedSpots
              • Required Columns
              • Optional Columns
              • Implementation
              • Serialization
            • SegmentationMask
              • Implementation
              • Serialization
        • Processing With AWS
          • Prerequisites
          • Set up your data
            • Upload your Data
            • Create a Recipe File
          • Set up your Batch Jobs
            • Create a custom IAM Role
            • Register your Jobs
          • Run your Batch Jobs
        • Configuration
          • Default values
          • Main environment variables
            • STARFISH_CONFIG
            • STARFISH_VALIDATION_STRICT
            • STARFISH_VERBOSE
          • Backend environment variables
            • SLICEDIMAGE_CACHING_SIZE_LIMIT
            • SLICEDIMAGE_CACHING_DIRECTORY
            • SLICEDIMAGE_CACHING_DEBUG
        • Glossary
        • Request Support
      • API
        • Data Structures
          • Experiment
          • Field of View
          • ImageStack
          • Codebook
          • ExpressionMatrix
          • IntensityTable
          • DecodedIntensityTable
          • BinaryMaskCollection
          • LabelImage
        • slicedimage
        • Data Formatting
          • Converting Structured Data
          • Tile Fetcher Interface
        • Image Manipulation
          • Filtering
          • Learn Transform
          • Apply Transform
          • Segmentation
        • Spots
          • Detecting Pixels
          • Finding Spots
          • Decoding Spots
          • Target Assignment
        • Morphology Transformations
          • Binarize
          • Filter
          • Merge
          • Segment
        • Types
          • Coordinates
          • Physical Coordinates
          • Axes
          • Features
          • SpotAttributes
          • Levels
        • Validation
          • Validators
          • Helpers
          • Error messages
        • Utilities
          • Configuration
            • StarfishConfig
            • environ
          • Provenance Logging
            • Example
        • Interactive Image Viewer: display()
        • Plotting Utilities
        • Datasets
      • Developer Guide
        • How can I contribute?
        • Installing starfish for developers
        • Creating a new algorithm for an existing pipeline_component
        • Reporting bugs
        • Code contributions
        • Notebook contributions
        • Debugging Errors
        • Upgrading to a new version
        • Reporting bugs
      • About
        • Citing Starfish
        • License
  • Help & Reference

Help & Reference¶

  • Data Model
  • SpaceTx Format
  • Available datasets
  • Working with Starfish Outputs
  • Processing With AWS
  • Configuration
  • Glossary
  • Request Support