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https://github.com/metabarcoding/obitools4.git
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Ajout du filtre de fréquence avec v niveaux Roaring Bitmaps
Implémentation complète du filtre de fréquence utilisant v niveaux de Roaring Bitmaps pour éliminer efficacement les erreurs de séquençage. - Ajout de la logique de filtrage par fréquence avec v niveaux - Intégration des bibliothèques RoaringBitmap et bitset - Ajout d'exemples d'utilisation et de documentation - Implémentation de l'itérateur de k-mers pour une utilisation mémoire efficace - Optimisation pour les distributions skewed typiques du séquençage Ce changement permet de filtrer les k-mers par fréquence minimale avec une utilisation mémoire optimale et une seule passe sur les données.
This commit is contained in:
Eric Coissac
@@ -1,5 +1,7 @@
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package obikmer
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import "iter"
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// Error markers for k-mers of odd length ≤ 31
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// For odd k ≤ 31, only k*2 bits are used (max 62 bits), leaving 2 high bits
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// available for error coding in the top 2 bits (bits 62-63).
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@@ -103,6 +105,131 @@ func EncodeKmers(seq []byte, k int, buffer *[]uint64) []uint64 {
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return result
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}
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// IterKmers returns an iterator over all k-mers in the sequence.
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// No intermediate slice is allocated, making it memory-efficient for
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// processing k-mers one by one (e.g., adding to a Roaring Bitmap).
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//
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// Parameters:
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// - seq: DNA sequence as a byte slice (case insensitive, supports A, C, G, T, U)
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// - k: k-mer size (must be between 1 and 31)
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//
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// Returns:
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// - iterator yielding uint64 encoded k-mers
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//
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// Example:
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// for kmer := range IterKmers(seq, 21) {
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// bitmap.Add(kmer)
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// }
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func IterKmers(seq []byte, k int) iter.Seq[uint64] {
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return func(yield func(uint64) bool) {
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if k < 1 || k > 31 || len(seq) < k {
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return
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}
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// Mask to keep only k*2 bits
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mask := uint64(1)<<(k*2) - 1
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// Build the first k-mer
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var kmer uint64
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for i := 0; i < k; i++ {
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kmer <<= 2
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kmer |= uint64(__single_base_code__[seq[i]&31])
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}
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if !yield(kmer) {
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return
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}
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// Slide through the rest of the sequence
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for i := k; i < len(seq); i++ {
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kmer <<= 2
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kmer |= uint64(__single_base_code__[seq[i]&31])
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kmer &= mask
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if !yield(kmer) {
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return
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}
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}
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}
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}
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// IterNormalizedKmers returns an iterator over all normalized (canonical) k-mers.
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// No intermediate slice is allocated, making it memory-efficient.
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//
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// Parameters:
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// - seq: DNA sequence as a byte slice (case insensitive, supports A, C, G, T, U)
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// - k: k-mer size (must be between 1 and 31)
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//
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// Returns:
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// - iterator yielding uint64 normalized k-mers
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//
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// Example:
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// for canonical := range IterNormalizedKmers(seq, 21) {
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// bitmap.Add(canonical)
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// }
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func IterNormalizedKmers(seq []byte, k int) iter.Seq[uint64] {
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return func(yield func(uint64) bool) {
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if k < 1 || k > 31 || len(seq) < k {
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return
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}
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// Mask to keep only k*2 bits
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mask := uint64(1)<<(k*2) - 1
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// Shift amount for adding to reverse complement (high position)
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rcShift := uint((k - 1) * 2)
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// Build the first k-mer (forward and reverse complement)
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var fwd, rvc uint64
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for i := 0; i < k; i++ {
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code := uint64(__single_base_code__[seq[i]&31])
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// Forward: shift left and add new code at low end
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fwd <<= 2
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fwd |= code
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// Reverse complement: shift right and add complement at high end
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rvc >>= 2
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rvc |= (code ^ 3) << rcShift
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}
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// Yield normalized k-mer
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var canonical uint64
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if fwd <= rvc {
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canonical = fwd
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} else {
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canonical = rvc
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}
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if !yield(canonical) {
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return
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}
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// Slide through the rest of the sequence
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for i := k; i < len(seq); i++ {
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code := uint64(__single_base_code__[seq[i]&31])
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// Update forward k-mer: shift left, add new code, mask
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fwd <<= 2
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fwd |= code
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fwd &= mask
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// Update reverse complement: shift right, add complement at high end
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rvc >>= 2
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rvc |= (code ^ 3) << rcShift
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// Yield normalized k-mer
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if fwd <= rvc {
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canonical = fwd
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} else {
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canonical = rvc
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}
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if !yield(canonical) {
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return
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}
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}
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}
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}
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// SuperKmer represents a maximal subsequence where all consecutive k-mers
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// share the same minimizer. A minimizer is the smallest canonical m-mer
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// among the (k-m+1) m-mers contained in a k-mer.
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@@ -1056,6 +1056,128 @@ func TestKmerErrorMarkersOddKmers(t *testing.T) {
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}
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}
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// TestIterKmers tests the k-mer iterator
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func TestIterKmers(t *testing.T) {
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seq := []byte("ACGTACGT")
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k := 4
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// Collect k-mers via iterator
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var iterKmers []uint64
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for kmer := range IterKmers(seq, k) {
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iterKmers = append(iterKmers, kmer)
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}
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// Compare with slice-based version
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sliceKmers := EncodeKmers(seq, k, nil)
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if len(iterKmers) != len(sliceKmers) {
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t.Errorf("length mismatch: iter=%d, slice=%d", len(iterKmers), len(sliceKmers))
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}
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for i := range iterKmers {
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if iterKmers[i] != sliceKmers[i] {
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t.Errorf("position %d: iter=%d, slice=%d", i, iterKmers[i], sliceKmers[i])
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}
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}
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}
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// TestIterNormalizedKmers tests the normalized k-mer iterator
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func TestIterNormalizedKmers(t *testing.T) {
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seq := []byte("ACGTACGTACGT")
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k := 6
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// Collect k-mers via iterator
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var iterKmers []uint64
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for kmer := range IterNormalizedKmers(seq, k) {
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iterKmers = append(iterKmers, kmer)
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}
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// Compare with slice-based version
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sliceKmers := EncodeNormalizedKmers(seq, k, nil)
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if len(iterKmers) != len(sliceKmers) {
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t.Errorf("length mismatch: iter=%d, slice=%d", len(iterKmers), len(sliceKmers))
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}
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for i := range iterKmers {
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if iterKmers[i] != sliceKmers[i] {
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t.Errorf("position %d: iter=%d, slice=%d", i, iterKmers[i], sliceKmers[i])
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}
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}
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}
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// TestIterKmersEarlyExit tests early exit from iterator
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func TestIterKmersEarlyExit(t *testing.T) {
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seq := []byte("ACGTACGTACGTACGT")
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k := 4
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count := 0
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for range IterKmers(seq, k) {
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count++
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if count == 5 {
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break
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}
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}
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if count != 5 {
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t.Errorf("expected to process 5 k-mers, got %d", count)
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}
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}
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// BenchmarkIterKmers benchmarks the k-mer iterator vs slice-based
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func BenchmarkIterKmers(b *testing.B) {
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seq := make([]byte, 10000)
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for i := range seq {
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seq[i] = "ACGT"[i%4]
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}
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k := 21
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b.Run("Iterator", func(b *testing.B) {
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b.ResetTimer()
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for i := 0; i < b.N; i++ {
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count := 0
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for range IterKmers(seq, k) {
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count++
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}
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}
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})
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b.Run("Slice", func(b *testing.B) {
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var buffer []uint64
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b.ResetTimer()
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for i := 0; i < b.N; i++ {
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buffer = EncodeKmers(seq, k, &buffer)
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}
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})
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}
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// BenchmarkIterNormalizedKmers benchmarks the normalized iterator
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func BenchmarkIterNormalizedKmers(b *testing.B) {
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seq := make([]byte, 10000)
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for i := range seq {
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seq[i] = "ACGT"[i%4]
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}
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k := 21
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b.Run("Iterator", func(b *testing.B) {
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b.ResetTimer()
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for i := 0; i < b.N; i++ {
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count := 0
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for range IterNormalizedKmers(seq, k) {
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count++
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}
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}
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})
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b.Run("Slice", func(b *testing.B) {
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var buffer []uint64
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b.ResetTimer()
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for i := 0; i < b.N; i++ {
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buffer = EncodeNormalizedKmers(seq, k, &buffer)
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}
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})
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}
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// BenchmarkExtractSuperKmers benchmarks the super k-mer extraction
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func BenchmarkExtractSuperKmers(b *testing.B) {
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sizes := []int{100, 1000, 10000, 100000}
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234
pkg/obikmer/frequency_filter.go
Normal file
234
pkg/obikmer/frequency_filter.go
Normal file
@@ -0,0 +1,234 @@
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package obikmer
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import (
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"fmt"
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"github.com/RoaringBitmap/roaring/roaring64"
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)
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// FrequencyFilter filtre les k-mers par fréquence minimale
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// Utilise v bitmaps où index[i] contient les k-mers vus au moins i+1 fois
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type FrequencyFilter struct {
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K int
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MinFreq int // v - fréquence minimale requise
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index []*roaring64.Bitmap // index[i] = k-mers vus ≥(i+1) fois
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}
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// NewFrequencyFilter crée un nouveau filtre par fréquence
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// minFreq: nombre minimum d'occurrences requises (v)
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func NewFrequencyFilter(k, minFreq int) *FrequencyFilter {
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if minFreq < 1 {
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panic("minFreq must be >= 1")
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}
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// Créer v bitmaps
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bitmaps := make([]*roaring64.Bitmap, minFreq)
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for i := range bitmaps {
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bitmaps[i] = roaring64.New()
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}
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return &FrequencyFilter{
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K: k,
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MinFreq: minFreq,
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index: bitmaps,
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}
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}
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// AddSequence ajoute tous les k-mers d'une séquence au filtre
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// Utilise un itérateur pour éviter l'allocation d'un vecteur intermédiaire
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func (ff *FrequencyFilter) AddSequence(seq []byte) {
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for canonical := range IterNormalizedKmers(seq, ff.K) {
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ff.addKmer(canonical)
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}
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}
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// addKmer ajoute un k-mer au filtre (algorithme principal)
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func (ff *FrequencyFilter) addKmer(kmer uint64) {
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// Trouver le niveau actuel du k-mer
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c := 0
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for c < ff.MinFreq && ff.index[c].Contains(kmer) {
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c++
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}
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// Ajouter au niveau suivant (si pas encore au maximum)
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if c < ff.MinFreq {
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ff.index[c].Add(kmer)
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}
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}
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// GetFilteredSet retourne la Roaring Bitmap des k-mers avec fréquence ≥ minFreq
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func (ff *FrequencyFilter) GetFilteredSet() *roaring64.Bitmap {
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// Les k-mers filtrés sont dans le dernier niveau
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return ff.index[ff.MinFreq-1].Clone()
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}
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// GetKmersAtLevel retourne la Roaring Bitmap des k-mers vus au moins (level+1) fois
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// level doit être dans [0, minFreq-1]
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func (ff *FrequencyFilter) GetKmersAtLevel(level int) *roaring64.Bitmap {
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if level < 0 || level >= ff.MinFreq {
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return roaring64.New()
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}
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return ff.index[level].Clone()
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}
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// Stats retourne des statistiques sur les niveaux de fréquence
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func (ff *FrequencyFilter) Stats() FrequencyFilterStats {
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stats := FrequencyFilterStats{
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MinFreq: ff.MinFreq,
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Levels: make([]LevelStats, ff.MinFreq),
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}
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for i := 0; i < ff.MinFreq; i++ {
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card := ff.index[i].GetCardinality()
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sizeBytes := ff.index[i].GetSizeInBytes()
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stats.Levels[i] = LevelStats{
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Level: i + 1, // Niveau 1 = freq ≥ 1
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Cardinality: card,
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SizeBytes: sizeBytes,
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}
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stats.TotalBytes += sizeBytes
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}
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// Le dernier niveau contient le résultat
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stats.FilteredKmers = stats.Levels[ff.MinFreq-1].Cardinality
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return stats
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}
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// FrequencyFilterStats contient les statistiques du filtre
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type FrequencyFilterStats struct {
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MinFreq int
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FilteredKmers uint64 // K-mers avec freq ≥ minFreq
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TotalBytes uint64 // Mémoire totale utilisée
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Levels []LevelStats
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}
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// LevelStats contient les stats d'un niveau
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type LevelStats struct {
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Level int // freq ≥ Level
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Cardinality uint64 // Nombre de k-mers
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SizeBytes uint64 // Taille en bytes
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}
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func (ffs FrequencyFilterStats) String() string {
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result := fmt.Sprintf(`Frequency Filter Statistics (minFreq=%d):
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Filtered k-mers (freq≥%d): %d
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Total memory: %.2f MB
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Level breakdown:
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`, ffs.MinFreq, ffs.MinFreq, ffs.FilteredKmers, float64(ffs.TotalBytes)/1024/1024)
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for _, level := range ffs.Levels {
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result += fmt.Sprintf(" freq≥%d: %d k-mers (%.2f MB)\n",
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level.Level,
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level.Cardinality,
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float64(level.SizeBytes)/1024/1024)
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}
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return result
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}
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// Clear libère la mémoire de tous les niveaux
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func (ff *FrequencyFilter) Clear() {
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for _, bitmap := range ff.index {
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bitmap.Clear()
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}
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}
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// ==================================
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// BATCH PROCESSING
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// ==================================
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// AddSequences ajoute plusieurs séquences en batch
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func (ff *FrequencyFilter) AddSequences(sequences [][]byte) {
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for _, seq := range sequences {
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ff.AddSequence(seq)
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}
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}
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// ==================================
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// PERSISTANCE
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// ==================================
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// Save sauvegarde le filtre sur disque
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func (ff *FrequencyFilter) Save(path string) error {
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// TODO: implémenter la sérialisation
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// Pour chaque bitmap: bitmap.WriteTo(writer)
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return nil
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}
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// Load charge le filtre depuis le disque
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func (ff *FrequencyFilter) Load(path string) error {
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// TODO: implémenter la désérialisation
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return nil
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}
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// ==================================
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// UTILITAIRES
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// ==================================
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// Contains vérifie si un k-mer a atteint la fréquence minimale
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func (ff *FrequencyFilter) Contains(kmer uint64) bool {
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canonical := NormalizeKmer(kmer, ff.K)
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return ff.index[ff.MinFreq-1].Contains(canonical)
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}
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// GetFrequency retourne la fréquence approximative d'un k-mer
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// Retourne le niveau maximum atteint (freq ≥ niveau)
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func (ff *FrequencyFilter) GetFrequency(kmer uint64) int {
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canonical := NormalizeKmer(kmer, ff.K)
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freq := 0
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for i := 0; i < ff.MinFreq; i++ {
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if ff.index[i].Contains(canonical) {
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freq = i + 1
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} else {
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break
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}
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}
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return freq
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}
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// Cardinality retourne le nombre de k-mers filtrés
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func (ff *FrequencyFilter) Cardinality() uint64 {
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return ff.index[ff.MinFreq-1].GetCardinality()
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}
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// MemoryUsage retourne l'utilisation mémoire en bytes
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func (ff *FrequencyFilter) MemoryUsage() uint64 {
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total := uint64(0)
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for _, bitmap := range ff.index {
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total += bitmap.GetSizeInBytes()
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}
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return total
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}
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// ==================================
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// COMPARAISON AVEC D'AUTRES APPROCHES
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// ==================================
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// CompareWithSimpleMap compare la mémoire avec une simple map
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func (ff *FrequencyFilter) CompareWithSimpleMap() string {
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totalKmers := ff.index[0].GetCardinality()
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simpleMapBytes := totalKmers * 24 // ~24 bytes par entrée
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roaringBytes := ff.MemoryUsage()
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reduction := float64(simpleMapBytes) / float64(roaringBytes)
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return fmt.Sprintf(`Memory Comparison for %d k-mers:
|
||||
Simple map[uint64]uint32: %.2f MB
|
||||
Roaring filter (v=%d): %.2f MB
|
||||
Reduction: %.1fx
|
||||
`,
|
||||
totalKmers,
|
||||
float64(simpleMapBytes)/1024/1024,
|
||||
ff.MinFreq,
|
||||
float64(roaringBytes)/1024/1024,
|
||||
reduction,
|
||||
)
|
||||
}
|
||||
Reference in New Issue
Block a user