Config File

How to Create a YAML Configuration File for Your Project

This guide provides step-by-step instructions on how to create a YAML file for configuring your ALE analysis. YAML (YAML Ain't Markup Language) is a human-readable format commonly used for configuration files.

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Step 1: Open a Text Editor

You can use any text editor to create a YAML file. Popular options include:

• Visual Studio Code
• Notepad++
• Sublime Text
• nano or vim (for terminal users)

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Step 2: Save the File with a .yaml or .yml Extension

When you create the file, save it with an appropriate name, such as config.yaml. Ensure the file extension is .yaml or .yml.

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Step 3: Copy the YAML Template Below

Below is the YAML template for your project. Copy this content into your file:

# Project Folder
project:
  analysis_info: "analysis_info.xlsx"
  experiment_info: "experiment_info.xlsx"


# ALE Parameters
# DO NOT CHANGE THESE IF YOU ARE NOT AN ALE EXPERT!
parameters:
  
  # If enabled pools multiple experiments from same paper into one experiment;
  pool_experiments: False

  # TFCE is a method for multiple comparison correction (Frahm et al., 2022)
  tfce_enabled: True

  # if enabled ALE map (and therefore all following maps) will be masked by ICBM 10% GM mask
  gm_masking: True

  # Size of bins used in MA histogram
  bin_steps: 0.0001 # Default: 0.0001
  
  # If enabled uses xgboost models to predict cutoffs instead of monte carlo simulation (Frahm et al., 2024)
  cutoff_predict_enabled: True

  # P-value required for significance
  # !! ONLY IF CUTOFF PREDICT IS DISABLED, OTHERWISE WON'T HAVE EFFECT !!
  significance_threshold: 0.05 # Default: 0.05

  # Preliminary cluster forming threshold used in cluster-level family wise error correction
  # !! ONLY IF CUTOFF PREDICT IS DISABLED, OTHERWISE WON'T HAVE EFFECT !!
  cluster_forming_threshold: 0.001 # Default: 0.001

  # Iterations used for monte-carlo based multiple comparison correction 
  # !! ONLY IF CUTOFF PREDICT IS DISABLED, OTHERWISE WON'T HAVE EFFECT !!
  monte_carlo_iterations: 5000 # Default: 5000

  # N subsamples calculated for probabilistic ALE algorithm
  subsample_n: 2500 # Default: 2500

  # Iterations used in classic contrast algorithm
  contrast_permutations: 10000 # Default: 10000

  # Correction Method on which to base contrast algorithm
  contrast_correction_method: "cFWE" # Default: "cFWE"; Options: "cFWE", "vFWE", "tfce"

  # Sub-Iterations used in balanced contrast algorithm
  difference_iterations: 1000 # Default: 1000

  # Number of parallel processes used for many different steps in the ALE algorith - maximum depends on your machine
  nprocesses: 2 # Default: 2



# DO NOT CHANGE THESE IF YOU ARE NOT AN ALE EXPERT

# MA_Clustering Parameters
# DO NOT CHANGE THESE IF YOU ARE NOT AN ALE EXPERT!
clustering_parameters:
  max_clusters: 10 # Default: 10
  subsample_fraction: 0.9 # Default: 0.9
  sampling_iterations: 1000 # Default: 1000
  null_iterations: 5000 # Default: 5000
  correlation_type: "spearman" # Default: "spearman"; Options: "spearman", "pearson"
  clustering_method: "hierarchical" # Default: "hierarchical"; Options: "hierarchical", "kmeans"
  linkage_method: "complete" # Default: "complete"; Options: "complete", "average", "ward"
  use_pooled_std: False # Default: False
# DO NOT CHANGE THESE IF YOU ARE NOT AN ALE EXPERT

Step 4: Save the File

After pasting the content change the names of your experiment and analysis info file and save the file with the name config.yaml.