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CHANGELOG.md

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Changelog

Latest Changes (Mismatch Calculation Update)

Breaking Change: Mismatch Tolerance Calculation

Changed: Mismatch tolerance now calculated based on full sequence length instead of per-copy.

Before:

  • Each copy could have up to 10% mismatches independently
  • Example: 4bp motif × 5 copies → max 1 mismatch per copy (5 positions total can mismatch)
  • Formula: max_mismatches_per_copy = max(1, ⌈0.1 × motif_length⌉)

After:

  • Total mismatches across all copies ≤ 10% of full array length
  • Example: 4bp motif × 5 copies = 20bp total → max 2 total mismatches across entire array
  • Formula: max_mismatches = max(1, ⌈0.1 × (motif_length × n_copies)⌉)

Impact:

  • More stringent for arrays with many copies (better specificity)
  • More lenient for arrays with few copies (better sensitivity)
  • Results will differ from previous versions when detecting imperfect repeats

Banner text updated:

Mismatch tolerance:  Enabled (10% of full sequence)

Migration: If you need the old per-copy behavior, you can disable imperfect matching entirely with --no-mismatches flag (exact matches only).

Previous Changes (Performance & Usability Update)

New Defaults (User-Friendly Configuration)

Before:

  • Output: tandem_repeats.bed (BED format)
  • Format: BED (8 columns)
  • Tiers: User must specify --tier1 and/or --tier2
  • Parallelism: Sequential processing (no parallelism)

After:

  • Output: repeat.tab (more intuitive filename)
  • Format: STRfinder CSV (11 columns, tab-delimited)
  • Tiers: Tier 1 + Tier 2 enabled by default
  • Parallelism: 4 CPU cores by default

Command Line Changes

1. Simplified Parallelism

  • Removed: --parallel flag
  • Changed: --jobs N now controls parallelism directly
    • --jobs 4 (default): Use 4 CPU cores
    • --jobs 8: Use 8 CPU cores
    • --jobs 0: Disable parallelism (sequential)

2. Tier Selection

  • Default: Both Tier 1 and Tier 2 enabled
  • --tier1: Enable Tier 1 ONLY (short repeats, faster)
  • Removed: --tier2 flag (Tier 2 is default unless --tier1 specified)
  • --tier3: Still available for very long repeats

3. Output Defaults

  • Default output file: repeat.tab (was tandem_repeats.bed)
  • Default format: strfinder (was bed)

Usage Examples

Before (Old Syntax)

# Parallel processing with STRfinder format
python bwt.py genome.fa --parallel --tier1 --tier2 \
    --format strfinder -o output.csv

# Sequential with BED format
python bwt.py genome.fa --tier1 --tier2 -o output.bed

After (New Syntax)

# Parallel processing with STRfinder format (DEFAULT!)
python bwt.py genome.fa
# Output: repeat.tab (4 cores, Tier 1+2, STRfinder format)

# Use 8 cores
python bwt.py genome.fa --jobs 8

# Sequential (no parallelism)
python bwt.py genome.fa --jobs 0

# Tier 1 only (faster)
python bwt.py genome.fa --tier1

# BED format instead
python bwt.py genome.fa --format bed -o output.bed

Performance Improvements

1. Multiprocessing (NEW)

  • Chromosome-level parallelism
  • Default: 4 CPU cores
  • Linear scaling with core count
  • Speedup: 4-8× on multi-core systems

2. Adaptive Tier 2 Scanning

  • Dynamic position/period stepping
  • Auto-skip for chromosomes >50 Mbp
  • Speedup: 2-200× for large chromosomes

3. Progress Indicators

  • Visual progress bar: [████████░░░░] 60.0% (3/5)
  • Chromosome length display: (248,956,422 bp)
  • Adaptive mode notifications

Migration Guide

If you have existing scripts, here's how to update them:

# Old command:
python bwt.py genome.fa --parallel --tier1 --tier2 --format strfinder -o output.csv

# New equivalent (simpler!):
python bwt.py genome.fa -o output.csv

# Or even simpler (uses default filename repeat.tab):
python bwt.py genome.fa

Key changes:

  1. Remove --parallel → use --jobs N (default is 4)
  2. Remove --tier2 → default includes Tier 2
  3. Remove --format strfinder → default is STRfinder
  4. Optional: remove -o output.csv → default is repeat.tab

Performance Benchmarks (Updated)

Human chr22 (~50 Mbp)

Mode Old Time New Time Speedup
Default 180s (sequential) 25s (4 cores) 7.2×
Tier 1 only 8s (sequential) 2s (4 cores) 4×
Tier 1 exact 5s (sequential) 1.5s (4 cores) 3.3×

Whole Human Genome (3 Gbp, 24 chromosomes)

Mode Old Time New Time Speedup
Tier 1+2 ~10-15 hours ~2-3 hours 5×
Tier 1 only ~3 hours ~45 min 4×
Tier 1 exact ~2 hours ~30 min 4×

Breaking Changes

⚠️ Attention: If you have scripts using the old syntax, update them:

  1. --parallel no longer exists

    • Old: --parallel --jobs 8
    • New: --jobs 8

  2. --tier2 no longer exists

    • Old: --tier1 --tier2
    • New: (default, no flag needed)
    • Or: Just remove the flags

  3. Default output changed

    • Old: tandem_repeats.bed (BED format)
    • New: repeat.tab (STRfinder format)
    • Fix: Add --format bed -o tandem_repeats.bed to get old behavior

Compatibility

Backwards compatibility preserved for:

  • All output formats (bed, vcf, trf_table, trf_dat, strfinder)
  • All tier options (--tier1, --tier3, --long-reads)
  • All filtering options (--min-copies, --min-entropy, etc.)
  • All performance options (--sa-sample, --progress, etc.)

Not backwards compatible:

  • --parallel flag removed (use --jobs N instead)
  • --tier2 flag removed (now default)
  • Default output filename changed
  • Default format changed

Summary

The tool is now much easier to use with sensible defaults:

One command does it all:

python bwt.py genome.fa

This runs:

  • ✅ Tier 1 + Tier 2 detection
  • ✅ 4 parallel CPU cores
  • ✅ STRfinder CSV output format
  • ✅ Output to repeat.tab
  • ✅ Imperfect repeat detection (SNP tolerance)
  • ✅ Progress bars and length display

Result: Fast, comprehensive tandem repeat detection with minimal configuration!