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mfsd-analysis

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Actualizado1 de julio de 2026 a las 15:57

Reference for gbcms mFSD (fragment size distribution) — the opt-in --mfsd flag, MAF/VCF column gating, KS test + LLR statistics, and Rust-native ZSTD Parquet output. Use when touching mfsd.rs, parquet_writer.rs, the mFSD report, or column-count tests.

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SKILL.md

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name	mfsd-analysis
description	Reference for gbcms mFSD (fragment size distribution) — the opt-in --mfsd flag, MAF/VCF column gating, KS test + LLR statistics, and Rust-native ZSTD Parquet output. Use when touching mfsd.rs, parquet_writer.rs, the mFSD report, or column-count tests.

mFSD Analysis Patterns

Overview

mFSD (modified Fragment Size Distribution) analysis is opt-in via --mfsd.

Column Gating

Without --mfsd: 145 MAF columns (0 mfsd_*)
With --mfsd: 186 MAF columns (+41 mfsd_*)
VCF INFO: exactly 13 MFSD_* fields added only when --mfsd is set
Columns are absent when off, not NA-filled

Parquet Output

--mfsd-parquet requires --mfsd (validated at both CLI and Pydantic)
Written by write_fsd_parquet() in Rust via arrow/parquet crates
ZSTD(1) compression: parquet = { default-features = false, features = ["arrow", "zstd"] }
ref_sizes/alt_sizes are Rust-internal — no #[pyo3(get)]
Called from pipeline.py after count_bam_binned(), not inside the counting engine (count_bam is the feature-gated legacy parity oracle, not the production path)

Statistics (watch-outs)

KS p-value uses an asymptotic approximation — weak at the small ALT-fragment counts (n≈5–20) typical of low-input cfDNA.
LLR is a fragment-size Gaussian log-ratio (distinct from the PairHMM LLR); guard against ±∞ from tail fragments by using the closed-form log-ratio.

Key Files

rust/src/counting/mfsd.rs: KS test, LLR, pairwise comparisons
rust/src/counting/parquet_writer.rs: Arrow/ZSTD native Parquet
src/gbcms/io/output.py: MafWriter column gating
src/gbcms/report/mfsd_report.py: HTML report generator
tests/test_mfsd_flag.py: column count assertions

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name	mfsd-analysis
description	Reference for gbcms mFSD (fragment size distribution) — the opt-in --mfsd flag, MAF/VCF column gating, KS test + LLR statistics, and Rust-native ZSTD Parquet output. Use when touching mfsd.rs, parquet_writer.rs, the mFSD report, or column-count tests.

mFSD Analysis Patterns

Overview

mFSD (modified Fragment Size Distribution) analysis is opt-in via --mfsd.

Column Gating

Without --mfsd: 145 MAF columns (0 mfsd_*)
With --mfsd: 186 MAF columns (+41 mfsd_*)
VCF INFO: exactly 13 MFSD_* fields added only when --mfsd is set
Columns are absent when off, not NA-filled

Parquet Output

--mfsd-parquet requires --mfsd (validated at both CLI and Pydantic)
Written by write_fsd_parquet() in Rust via arrow/parquet crates
ZSTD(1) compression: parquet = { default-features = false, features = ["arrow", "zstd"] }
ref_sizes/alt_sizes are Rust-internal — no #[pyo3(get)]
Called from pipeline.py after count_bam_binned(), not inside the counting engine (count_bam is the feature-gated legacy parity oracle, not the production path)

Statistics (watch-outs)

KS p-value uses an asymptotic approximation — weak at the small ALT-fragment counts (n≈5–20) typical of low-input cfDNA.
LLR is a fragment-size Gaussian log-ratio (distinct from the PairHMM LLR); guard against ±∞ from tail fragments by using the closed-form log-ratio.

Key Files

rust/src/counting/mfsd.rs: KS test, LLR, pairwise comparisons
rust/src/counting/parquet_writer.rs: Arrow/ZSTD native Parquet
src/gbcms/io/output.py: MafWriter column gating
src/gbcms/report/mfsd_report.py: HTML report generator
tests/test_mfsd_flag.py: column count assertions