FIFA for FFPE Filtering

README last updated March 17, 2026

To access the help manual, run:

/path/to/fifa/src/cli.py --help

Note: For convenience, the user can create a symlink between /path/to/fifa/src/cli.py and the command fifa

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The tool can be run on three different modes:

1) Extract

For each SNV specified in a VCF file, extract features using the sample's VCF and BAM file. Creates a table of features that can be used to make predictions, or to train a new EBM model.

/path/to/fifa/src/cli.py extract -s [SAMPLE NAME] -c [COHORT] -v [VCF PATH] -b [BAM PATH] -r [REF SEQ] -o [OUTPUT DIR] -n [NUMBER OF THREADS ALLOCATED]

Optional Parameters:

• Variants can be labeled with a user-specified flag. Use -l for this purpose:

  -l [INFO FIELD WITH VARIANT LABEL] [TRUTH VALUE]  (default: None, None)
  -l 'INFO/Label' 'Real'
  

• If intending to run the original feature extraction script, please include the flag "-p". The original script does not properly paralelize processes across resources, so in practice there's no real reason to use it other than for testing resource allocation / resource efficiency.

  -p  # Include this flag to enable the original scheme.
  

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2) Predict

/path/to/fifa/src/cli.py predict -s [SAMPLE NAME] -v [VCF PATH] -f [FEATURES PATH] -o [OUTPUT DIR FOR VCF WITH ANNOTATIONS] -m [PATHS TO EBM MODELS]

Notes on Model Paths:

If multiple models are submitted, they will automatically be merged together. Current FIFA models are:

• NYGC1: /path/to/fifa/models/ebm_hyperparams_NYGC1.pkl
• NYGC2: /path/to/fifa/models/ebm_hyperparams_NYGC2.pkl
• HTMCP: /path/to/fifa/models/ebm_hyperparams_CGCI-HTMCP.pkl
• BLGSP: /path/to/fifa/models/ebm_hyperparams_CGCI-BLGSP.pkl

To merge one of the core FIFA models, the user can provide either the path or simply specify the cohort by name [NYGC1, NYGC2, HTMCP, BLGSP]

Optional Parameters:

• Add annotations from the RNA pileups to the output VCF. Will automatically rescue variants erroneously discarded by FIFA:

  -r [PATH TO RNA PILEUPS]

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3) Retrain

Train a new EBM model using a new cohort Note : Data must be labeled.

/path/to/fifa/src/cli.py retrain -o [OUTPUT PATH] -d [DIRECTORY CONTAINING NEW SAMPLES] -l [CSV FILE WITH TRUE LABELS]

Note: The program assumes that the directory contains a series of files in the format "[SAMPLE]_extracted_features.csv". For example, see :

/path/to/fifa/data/1395_tumor_ffpe_wgs_extracted_features.csv

Optional Parameters:

-hp  # FLAG; CONDUCT HYPERPARAMETER GRID-SEARCH WHEN TRAINING THE NEW EBM

4) Merge Models

Additional script for merging models together, and saving them as a new model. Produces preliminary metrics on the HCC1395 chr1 variants.

/path/to/fifa/src/cli.py merge -o [OUTPUT PATH FOR FIFA MODEL] -m [PATHS TO INPUT MODELS]