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https://github.com/metabarcoding/obitools4.git
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This change introduces the core functionality for identifying, validating, and statistically evaluating primer pairs within the corpus. It includes new data structures for primer parameters, amplicon statistics, and sequence handling, along with methods for assigning taxa to sequences. Comprehensive tests are added to ensure the accuracy of the pair evaluation against expected outputs.
361 lines
10 KiB
Go
361 lines
10 KiB
Go
package obiprimer
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import (
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"cmp"
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"fmt"
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"math"
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"slices"
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"sync"
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"git.metabarcoding.org/obitools/obitools4/obitools4/pkg/obidefault"
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"git.metabarcoding.org/obitools/obitools4/obitools4/pkg/obithermo"
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)
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// PairStats describes one primer pair and its quality indices. Primers are
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// written 5'->3' and ordered so that Primer1 < Primer2 (as in ecoPrimers).
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type PairStats struct {
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Primer1, Primer2 string
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Good1, Good2 bool // primer conserved in the examples and rare in the counterexamples
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Examples int // example sequences amplified
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CounterExamples int
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Yule float32 // Examples/|E| - CounterExamples/|C|
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ExampleTaxa int // taxa amplified among the examples
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CounterTaxa int // taxa amplified among the counterexamples
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Bc float32 // coverage: ExampleTaxa over all the example taxa
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Identified int // example taxa with an amplicon no other taxon shares
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Bs float32 // specificity: Identified over ExampleTaxa
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MinLen, MaxLen int
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MeanLen float64
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Tm1, Tm2 float64 // melting temperature of the primers against their perfect target
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MinTm1, MinTm2 float64 // lowest melting temperature over the example amplicons
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GC1, GC2 int
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}
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// Score is the ranking criterion of ecoPrimers.
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func (p PairStats) Score() float32 { return p.Yule * p.Bs }
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// ampRecord is an amplicon of a retained pair, in one sequence.
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type ampRecord struct {
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pair int32
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seq int32
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hash uint64
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tm1, tm2 float32 // NaN when unavailable
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}
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// ampHash hashes the amplicon between the two primers read from the side of
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// the first primer of the pair (reverse complemented when the upstream match is
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// the second primer), so that identical amplicons give the same value
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// whatever their strand. Non ACGT bases hash as a fifth symbol.
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func ampHash(raw []byte, from, to int, reverse bool) uint64 {
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const prime = 1099511628211
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h := uint64(14695981039346656037) ^ uint64(to-from)
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h *= prime
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if !reverse {
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for _, b := range raw[from:to] {
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h = (h ^ uint64(baseCode[b])) * prime
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}
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return h
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}
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for i := to - 1; i >= from; i-- {
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c := baseCode[raw[i]]
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if c < 4 {
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c = 3 - c
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}
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h = (h ^ uint64(c)) * prime
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}
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return h
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}
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// FindPairs searches the primer pairs from the approximate occurrences of the
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// strict words (see MatchApat) and evaluates them.
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//
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// A pair is a pair of conserved primers, at least one of them good, that
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// delimit an amplicon of the allowed length. It is retained when it amplifies
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// more than Sensitivity of the examples and less than FalsePositive of the
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// counterexamples, and its specificity Bs reaches MinSpecificity. The result
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// is sorted by decreasing Yule*Bs.
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//
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// model computes the melting temperatures; nil leaves them NaN.
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func FindPairs(c *Corpus, taxa *Taxa, wm []WordMatches, p PairParams, model *obithermo.Model) ([]PairStats, error) {
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if err := p.validate(); err != nil {
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return nil, err
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}
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if taxa == nil || len(taxa.Of) != len(c.Seqs) {
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return nil, fmt.Errorf("obiprimer: taxa do not match the corpus")
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}
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ps := selectPrimers(c, wm, p)
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if len(ps.primers) == 0 {
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return nil, nil
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}
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// Phase 1: which pairs amplify enough examples and few enough counterexamples.
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counts := c.Counts()
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acc := ps.countPairs(c, p)
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sens, fpq := float32(p.Sensitivity), float32(p.FalsePositive)
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var kept []pairKey
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for k, a := range acc {
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q := float32(a.examples) / float32(counts.Examples)
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qfp := float32(0)
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if counts.CounterExamples > 0 {
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qfp = float32(a.counters) / float32(counts.CounterExamples)
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}
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if q > sens && qfp < fpq {
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kept = append(kept, k)
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}
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}
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slices.SortFunc(kept, func(a, b pairKey) int {
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return cmp.Or(cmp.Compare(a.p1, b.p1), cmp.Compare(a.p2, b.p2),
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boolCmp(a.a1, b.a1), boolCmp(a.a2, b.a2))
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})
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index := make(map[pairKey]int32, len(kept))
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for i, k := range kept {
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index[k] = int32(i)
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}
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// Phase 2: the amplicons of the retained pairs only.
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records := ps.collectAmplicons(c, p, index, model)
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byPair := make([][]ampRecord, len(kept))
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for _, r := range records {
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byPair[r.pair] = append(byPair[r.pair], r)
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}
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var out []PairStats
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for i, k := range kept {
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st, ok := ps.evaluate(c, taxa, p, k, acc[k], byPair[i], model)
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if ok {
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out = append(out, st)
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}
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}
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slices.SortFunc(out, func(a, b PairStats) int {
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return cmp.Or(-cmp.Compare(a.Score(), b.Score()), cmp.Compare(a.Primer1, b.Primer1), cmp.Compare(a.Primer2, b.Primer2))
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})
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return out, nil
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}
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func boolCmp(a, b bool) int {
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switch {
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case a == b:
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return 0
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case !a:
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return -1
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}
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return 1
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}
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// collectAmplicons gathers, in parallel, one record per amplicon of a retained pair.
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func (ps *primerSet) collectAmplicons(c *Corpus, p PairParams, index map[pairKey]int32, model *obithermo.Model) []ampRecord {
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lp := p.PrimerLength
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workers := obidefault.ParallelWorkers()
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parts := make([][]ampRecord, workers)
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// oriented[primer][0] is the reverse complement of the word, [1] the word itself.
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oriented := make([][2][]byte, len(ps.primers))
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for i, pr := range ps.primers {
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oriented[i][0] = []byte(orientedWord(pr.Word, lp, false))
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oriented[i][1] = []byte(orientedWord(pr.Word, lp, true))
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}
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nan := float32(math.NaN())
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jobs := make(chan int)
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var wg sync.WaitGroup
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for w := range workers {
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wg.Add(1)
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go func() {
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defer wg.Done()
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var site1, site2 [32]byte
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for s := range jobs {
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raw := c.Seqs[s].Sequence()
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n := len(raw)
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isExample := c.Roles[s] == Example
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ps.forEachOccurrence(c, s, p, func(o occurrence) {
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pi, ok := index[o.key]
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if !ok {
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return
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}
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rec := ampRecord{pair: pi, seq: int32(s), tm1: nan, tm2: nan}
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if isExample {
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rec.hash = ampHash(raw, int(o.up.pos)+lp, int(o.down.pos), o.swapped)
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if model != nil {
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fp := oriented[o.up.primer][b2i(!o.up.reverse)]
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rp := oriented[o.down.primer][b2i(o.down.reverse)]
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fsite, rsite := site1[:lp], site2[:lp]
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okF := windowAsIs(fsite, raw, int(o.up.pos), n, p.Circular)
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okR := windowRevComp(rsite, raw, int(o.down.pos), n, p.Circular)
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tmF, tmR := nan, nan
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if okF {
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if t, err := model.Tm(fp, fsite); err == nil {
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tmF = float32(t)
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}
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}
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if okR {
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if t, err := model.Tm(rp, rsite); err == nil {
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tmR = float32(t)
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}
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}
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if o.swapped {
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rec.tm1, rec.tm2 = tmR, tmF
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} else {
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rec.tm1, rec.tm2 = tmF, tmR
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}
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}
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}
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parts[w] = append(parts[w], rec)
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})
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}
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}()
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}
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for s := range c.Seqs {
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jobs <- s
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}
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close(jobs)
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wg.Wait()
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var all []ampRecord
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for _, part := range parts {
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all = append(all, part...)
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}
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return all
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}
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func b2i(b bool) int {
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if b {
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return 1
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}
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return 0
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}
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const upper = "ACGT"
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// windowAsIs copies the len(dst) bases at pos as upper-case ACGT; it reports
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// false if one of them is not A, C, G or T.
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func windowAsIs(dst, raw []byte, pos, n int, circular bool) bool {
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for t := range dst {
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i := pos + t
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if circular {
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i %= n
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}
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c := baseCode[raw[i]]
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if c > 3 {
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return false
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}
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dst[t] = upper[c]
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}
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return true
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}
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// windowRevComp writes the reverse complement of the len(dst) bases at pos.
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func windowRevComp(dst, raw []byte, pos, n int, circular bool) bool {
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l := len(dst)
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for t := range dst {
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i := pos + l - 1 - t
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if circular {
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i %= n
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}
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c := baseCode[raw[i]]
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if c > 3 {
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return false
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}
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dst[t] = upper[3-c]
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}
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return true
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}
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// evaluate computes the indices of one retained pair. It reports false when the
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// pair must be dropped (no taxon amplified, or specificity under the threshold).
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func (ps *primerSet) evaluate(c *Corpus, taxa *Taxa, p PairParams, k pairKey, a *pairAcc,
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recs []ampRecord, model *obithermo.Model) (PairStats, bool) {
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exTaxa := map[int32]struct{}{}
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coTaxa := map[int32]struct{}{}
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ampTaxon := map[uint64]int32{} // amplicon -> its taxon, or -2 when shared
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for _, r := range recs {
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t := taxa.Of[r.seq]
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if t < 0 {
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continue
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}
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if c.Roles[r.seq] != Example {
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coTaxa[t] = struct{}{}
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continue
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}
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exTaxa[t] = struct{}{}
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if prev, seen := ampTaxon[r.hash]; !seen {
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ampTaxon[r.hash] = t
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} else if prev != t {
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ampTaxon[r.hash] = -2
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}
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}
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if len(exTaxa) == 0 {
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return PairStats{}, false
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}
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identified := map[int32]struct{}{}
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for _, t := range ampTaxon {
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if t >= 0 {
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identified[t] = struct{}{}
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}
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}
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counts := c.Counts()
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st := PairStats{
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Examples: int(a.examples),
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CounterExamples: int(a.counters),
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ExampleTaxa: len(exTaxa),
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CounterTaxa: len(coTaxa),
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Identified: len(identified),
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MinLen: int(a.minLen),
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MaxLen: int(a.maxLen),
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MeanLen: float64(a.sumLen) / float64(a.amplicons),
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}
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q := float32(a.examples) / float32(counts.Examples)
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qfp := float32(0)
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if counts.CounterExamples > 0 {
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qfp = float32(a.counters) / float32(counts.CounterExamples)
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}
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st.Yule = q - qfp
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st.Bc = float32(st.ExampleTaxa) / float32(taxa.ExampleTaxa)
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st.Bs = float32(st.Identified) / float32(st.ExampleTaxa)
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if st.Bs < float32(p.MinSpecificity) {
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return PairStats{}, false
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}
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lp := p.PrimerLength
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st.Primer1 = orientedWord(ps.primers[k.p1].Word, lp, k.a1)
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st.Primer2 = orientedWord(ps.primers[k.p2].Word, lp, k.a2)
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st.Good1, st.Good2 = ps.primers[k.p1].Good, ps.primers[k.p2].Good
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st.GC1, st.GC2 = obithermo.GCCount([]byte(st.Primer1)), obithermo.GCCount([]byte(st.Primer2))
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st.Tm1, st.Tm2, st.MinTm1, st.MinTm2 = math.NaN(), math.NaN(), math.NaN(), math.NaN()
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if model != nil {
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st.Tm1, _ = model.SelfTm([]byte(st.Primer1))
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st.Tm2, _ = model.SelfTm([]byte(st.Primer2))
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m1, m2 := float32(math.Inf(1)), float32(math.Inf(1))
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for _, r := range recs {
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if c.Roles[r.seq] != Example {
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continue
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}
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if r.tm1 == r.tm1 { // not NaN
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m1 = min(m1, r.tm1)
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}
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if r.tm2 == r.tm2 {
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m2 = min(m2, r.tm2)
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}
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}
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if !math.IsInf(float64(m1), 1) {
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st.MinTm1 = float64(m1)
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}
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if !math.IsInf(float64(m2), 1) {
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st.MinTm2 = float64(m2)
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}
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}
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if st.Primer2 < st.Primer1 {
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st.Primer1, st.Primer2 = st.Primer2, st.Primer1
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st.Good1, st.Good2 = st.Good2, st.Good1
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st.GC1, st.GC2 = st.GC2, st.GC1
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st.Tm1, st.Tm2 = st.Tm2, st.Tm1
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st.MinTm1, st.MinTm2 = st.MinTm2, st.MinTm1
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}
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return st, true
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}
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