"bufio"
"bytes"
"encoding/gob"
+ "encoding/json"
+ "errors"
"flag"
"fmt"
"io"
"io/ioutil"
+ "math"
"net/http"
_ "net/http/pprof"
"os"
"strconv"
"strings"
"sync/atomic"
+ "unsafe"
"git.arvados.org/arvados.git/sdk/go/arvados"
"github.com/arvados/lightning/hgvs"
+ "github.com/james-bowman/nlp"
"github.com/kshedden/gonpy"
+ "github.com/sirupsen/logrus"
log "github.com/sirupsen/logrus"
"golang.org/x/crypto/blake2b"
+ "gonum.org/v1/gonum/mat"
)
+const annotationMaxTileSpan = 100
+
type sliceNumpy struct {
- filter filter
- threads int
+ filter filter
+ threads int
+ chi2Cases []bool
+ chi2PValue float64
+ pvalueMinFrequency float64
+ maxFrequency float64
+ pcaComponents int
+ minCoverage int
+ minCoverageAll bool
+ includeVariant1 bool
+ debugTag tagID
+
+ cgnames []string
+ samples []sampleInfo
+ trainingSet []int // samples index => training set index, or -1 if not in training set
+ trainingSetSize int
+ pvalue func(onehot []bool) float64
+ pvalueCallCount int64
}
func (cmd *sliceNumpy) RunCommand(prog string, args []string, stdin io.Reader, stdout, stderr io.Writer) int {
- var err error
- defer func() {
- if err != nil {
- fmt.Fprintf(stderr, "%s\n", err)
- }
- }()
+ err := cmd.run(prog, args, stdin, stdout, stderr)
+ if err != nil {
+ fmt.Fprintf(stderr, "%s\n", err)
+ return 1
+ }
+ return 0
+}
+
+func (cmd *sliceNumpy) run(prog string, args []string, stdin io.Reader, stdout, stderr io.Writer) error {
flags := flag.NewFlagSet("", flag.ContinueOnError)
flags.SetOutput(stderr)
pprof := flags.String("pprof", "", "serve Go profile data at http://`[addr]:port`")
runlocal := flags.Bool("local", false, "run on local host (default: run in an arvados container)")
+ arvadosRAM := flags.Int("arvados-ram", 750000000000, "amount of memory to request for arvados container (`bytes`)")
+ arvadosVCPUs := flags.Int("arvados-vcpus", 96, "number of VCPUs to request for arvados container")
projectUUID := flags.String("project", "", "project `UUID` for output data")
priority := flags.Int("priority", 500, "container request priority")
+ preemptible := flags.Bool("preemptible", true, "request preemptible instance")
inputDir := flags.String("input-dir", "./in", "input `directory`")
outputDir := flags.String("output-dir", "./out", "output `directory`")
ref := flags.String("ref", "", "reference name (if blank, choose last one that appears in input)")
mergeOutput := flags.Bool("merge-output", false, "merge output into one matrix.npy and one matrix.annotations.csv")
hgvsSingle := flags.Bool("single-hgvs-matrix", false, "also generate hgvs-based matrix")
hgvsChunked := flags.Bool("chunked-hgvs-matrix", false, "also generate hgvs-based matrix per chromosome")
- flags.IntVar(&cmd.threads, "threads", 16, "number of memory-hungry assembly threads")
+ onehotSingle := flags.Bool("single-onehot", false, "generate one-hot tile-based matrix")
+ onehotChunked := flags.Bool("chunked-onehot", false, "generate one-hot tile-based matrix per input chunk")
+ samplesFilename := flags.String("samples", "", "`samples.csv` file with training/validation and case/control groups (see 'lightning choose-samples')")
+ caseControlOnly := flags.Bool("case-control-only", false, "drop samples that are not in case/control groups")
+ onlyPCA := flags.Bool("pca", false, "run principal component analysis, write components to pca.npy and samples.csv")
+ flags.IntVar(&cmd.pcaComponents, "pca-components", 4, "number of PCA components to compute / use in logistic regression")
+ maxPCATiles := flags.Int("max-pca-tiles", 0, "maximum tiles to use as PCA input (filter, then drop every 2nd colum pair until below max)")
+ debugTag := flags.Int("debug-tag", -1, "log debugging details about specified tag")
+ flags.BoolVar(&cmd.minCoverageAll, "min-coverage-all", false, "apply -min-coverage filter based on all samples, not just training set")
+ flags.IntVar(&cmd.threads, "threads", 16, "number of memory-hungry assembly threads, and number of VCPUs to request for arvados container")
+ flags.Float64Var(&cmd.chi2PValue, "chi2-p-value", 1, "do Χ² test (or logistic regression if -samples file has PCA components) and omit columns with p-value above this threshold")
+ flags.Float64Var(&cmd.pvalueMinFrequency, "pvalue-min-frequency", 0.01, "skip p-value calculation on tile variants below this frequency in the training set")
+ flags.Float64Var(&cmd.maxFrequency, "max-frequency", 1, "do not output variants above this frequency in the training set")
+ flags.BoolVar(&cmd.includeVariant1, "include-variant-1", false, "include most common variant when building one-hot matrix")
cmd.filter.Flags(flags)
- err = flags.Parse(args)
+ err := flags.Parse(args)
if err == flag.ErrHelp {
- err = nil
- return 0
+ return nil
} else if err != nil {
- return 2
+ return err
+ } else if flags.NArg() > 0 {
+ return fmt.Errorf("errant command line arguments after parsed flags: %v", flags.Args())
}
if *pprof != "" {
}()
}
+ if cmd.chi2PValue != 1 && *samplesFilename == "" {
+ return fmt.Errorf("cannot use provided -chi2-p-value=%f because -samples= value is empty", cmd.chi2PValue)
+ }
+
+ cmd.debugTag = tagID(*debugTag)
+
if !*runlocal {
runner := arvadosContainerRunner{
Name: "lightning slice-numpy",
Client: arvados.NewClientFromEnv(),
ProjectUUID: *projectUUID,
- RAM: 750000000000,
- VCPUs: 96,
+ RAM: int64(*arvadosRAM),
+ VCPUs: *arvadosVCPUs,
Priority: *priority,
KeepCache: 2,
APIAccess: true,
+ Preemptible: *preemptible,
}
- err = runner.TranslatePaths(inputDir, regionsFilename)
+ err = runner.TranslatePaths(inputDir, regionsFilename, samplesFilename)
if err != nil {
- return 1
+ return err
}
runner.Args = []string{"slice-numpy", "-local=true",
"-pprof=:6060",
"-merge-output=" + fmt.Sprintf("%v", *mergeOutput),
"-single-hgvs-matrix=" + fmt.Sprintf("%v", *hgvsSingle),
"-chunked-hgvs-matrix=" + fmt.Sprintf("%v", *hgvsChunked),
+ "-single-onehot=" + fmt.Sprintf("%v", *onehotSingle),
+ "-chunked-onehot=" + fmt.Sprintf("%v", *onehotChunked),
+ "-samples=" + *samplesFilename,
+ "-case-control-only=" + fmt.Sprintf("%v", *caseControlOnly),
+ "-min-coverage-all=" + fmt.Sprintf("%v", cmd.minCoverageAll),
+ "-pca=" + fmt.Sprintf("%v", *onlyPCA),
+ "-pca-components=" + fmt.Sprintf("%d", cmd.pcaComponents),
+ "-max-pca-tiles=" + fmt.Sprintf("%d", *maxPCATiles),
+ "-chi2-p-value=" + fmt.Sprintf("%f", cmd.chi2PValue),
+ "-pvalue-min-frequency=" + fmt.Sprintf("%f", cmd.pvalueMinFrequency),
+ "-max-frequency=" + fmt.Sprintf("%f", cmd.maxFrequency),
+ "-include-variant-1=" + fmt.Sprintf("%v", cmd.includeVariant1),
+ "-debug-tag=" + fmt.Sprintf("%d", cmd.debugTag),
}
runner.Args = append(runner.Args, cmd.filter.Args()...)
var output string
output, err = runner.Run()
if err != nil {
- return 1
+ return err
}
fmt.Fprintln(stdout, output)
- return 0
+ return nil
}
- infiles, err := allGobFiles(*inputDir)
+ infiles, err := allFiles(*inputDir, matchGobFile)
if err != nil {
- return 1
+ return err
}
if len(infiles) == 0 {
err = fmt.Errorf("no input files found in %s", *inputDir)
- return 1
+ return err
}
sort.Strings(infiles)
- var cgnames []string
var refseq map[string][]tileLibRef
var reftiledata = make(map[tileLibRef][]byte, 11000000)
in0, err := open(infiles[0])
if err != nil {
- return 1
+ return err
}
matchGenome, err := regexp.Compile(cmd.filter.MatchGenome)
if err != nil {
err = fmt.Errorf("-match-genome: invalid regexp: %q", cmd.filter.MatchGenome)
- return 1
+ return err
+ }
+
+ if *samplesFilename != "" {
+ cmd.samples, err = loadSampleInfo(*samplesFilename)
+ if err != nil {
+ return err
+ }
+ } else if *caseControlOnly {
+ return fmt.Errorf("-case-control-only does not make sense without -samples")
}
- taglen := -1
- DecodeLibrary(in0, strings.HasSuffix(infiles[0], ".gz"), func(ent *LibraryEntry) error {
+ cmd.cgnames = nil
+ var tagset [][]byte
+ err = DecodeLibrary(in0, strings.HasSuffix(infiles[0], ".gz"), func(ent *LibraryEntry) error {
if len(ent.TagSet) > 0 {
- taglen = len(ent.TagSet[0])
+ tagset = ent.TagSet
}
for _, cseq := range ent.CompactSequences {
if cseq.Name == *ref || *ref == "" {
}
for _, cg := range ent.CompactGenomes {
if matchGenome.MatchString(cg.Name) {
- cgnames = append(cgnames, cg.Name)
+ cmd.cgnames = append(cmd.cgnames, cg.Name)
}
}
for _, tv := range ent.TileVariants {
return nil
})
if err != nil {
- return 1
+ return err
}
in0.Close()
if refseq == nil {
err = fmt.Errorf("%s: reference sequence not found", infiles[0])
- return 1
+ return err
}
- if taglen < 0 {
+ if len(tagset) == 0 {
err = fmt.Errorf("tagset not found")
- return 1
+ return err
}
- if len(cgnames) == 0 {
- err = fmt.Errorf("no genomes found matching regexp %q", cmd.filter.MatchGenome)
- return 1
+
+ taglib := &tagLibrary{}
+ err = taglib.setTags(tagset)
+ if err != nil {
+ return err
}
- sort.Strings(cgnames)
+ taglen := taglib.TagLen()
+ sort.Strings(cmd.cgnames)
- {
- labelsFilename := *outputDir + "/labels.csv"
- log.Infof("writing labels to %s", labelsFilename)
- var f *os.File
- f, err = os.Create(labelsFilename)
- if err != nil {
- return 1
+ if len(cmd.cgnames) == 0 {
+ return fmt.Errorf("fatal: 0 matching samples in library, nothing to do")
+ }
+ cmd.trainingSet = make([]int, len(cmd.cgnames))
+ if *samplesFilename == "" {
+ cmd.trainingSetSize = len(cmd.cgnames)
+ for i, name := range cmd.cgnames {
+ cmd.samples = append(cmd.samples, sampleInfo{
+ id: trimFilenameForLabel(name),
+ isTraining: true,
+ })
+ cmd.trainingSet[i] = i
}
- defer f.Close()
- for i, name := range cgnames {
- _, err = fmt.Fprintf(f, "%d,%q\n", i, trimFilenameForLabel(name))
- if err != nil {
- err = fmt.Errorf("write %s: %w", labelsFilename, err)
- return 1
+ } else if len(cmd.cgnames) != len(cmd.samples) {
+ return fmt.Errorf("mismatched sample list: %d samples in library, %d in %s", len(cmd.cgnames), len(cmd.samples), *samplesFilename)
+ } else {
+ for i, name := range cmd.cgnames {
+ if s := trimFilenameForLabel(name); s != cmd.samples[i].id {
+ return fmt.Errorf("mismatched sample list: sample %d is %q in library, %q in %s", i, s, cmd.samples[i].id, *samplesFilename)
}
}
- err = f.Close()
+ if *caseControlOnly {
+ for i := 0; i < len(cmd.samples); i++ {
+ if !cmd.samples[i].isTraining && !cmd.samples[i].isValidation {
+ if i+1 < len(cmd.samples) {
+ copy(cmd.samples[i:], cmd.samples[i+1:])
+ copy(cmd.cgnames[i:], cmd.cgnames[i+1:])
+ }
+ cmd.samples = cmd.samples[:len(cmd.samples)-1]
+ cmd.cgnames = cmd.cgnames[:len(cmd.cgnames)-1]
+ i--
+ }
+ }
+ }
+ cmd.chi2Cases = nil
+ cmd.trainingSetSize = 0
+ for i := range cmd.cgnames {
+ if cmd.samples[i].isTraining {
+ cmd.trainingSet[i] = cmd.trainingSetSize
+ cmd.trainingSetSize++
+ cmd.chi2Cases = append(cmd.chi2Cases, cmd.samples[i].isCase)
+ } else {
+ cmd.trainingSet[i] = -1
+ }
+ }
+ if cmd.pvalue == nil {
+ cmd.pvalue = func(onehot []bool) float64 {
+ return pvalue(onehot, cmd.chi2Cases)
+ }
+ }
+ }
+
+ if cmd.minCoverageAll {
+ cmd.minCoverage = len(cmd.cgnames)
+ } else {
+ cmd.minCoverage = cmd.trainingSetSize
+ }
+ if cmd.filter.MinCoverage < 1 {
+ cmd.minCoverage = int(math.Ceil(cmd.filter.MinCoverage * float64(cmd.minCoverage)))
+ }
+
+ if len(cmd.samples[0].pcaComponents) > 0 {
+ cmd.pvalue = glmPvalueFunc(cmd.samples, cmd.pcaComponents)
+ // Unfortunately, statsmodel/glm lib logs stuff to
+ // os.Stdout when it panics on an unsolvable
+ // problem. We recover() from the panic in glm.go, but
+ // we also need to commandeer os.Stdout to avoid
+ // producing large quantities of logs.
+ stdoutWas := os.Stdout
+ defer func() { os.Stdout = stdoutWas }()
+ os.Stdout, err = os.Open(os.DevNull)
if err != nil {
- err = fmt.Errorf("close %s: %w", labelsFilename, err)
- return 1
+ return err
}
}
+ // cgnamemap[name]==true for samples that we are including in
+ // output
+ cgnamemap := map[string]bool{}
+ for _, name := range cmd.cgnames {
+ cgnamemap[name] = true
+ }
+
+ err = writeSampleInfo(cmd.samples, *outputDir)
+ if err != nil {
+ return err
+ }
+
log.Info("indexing reference tiles")
type reftileinfo struct {
variant tileVariantID
seqname string // chr1
pos int // distance from start of chromosome to starttag
tiledata []byte // acgtggcaa...
+ excluded bool // true if excluded by regions file
+ nexttag tagID // tagID of following tile (-1 for last tag of chromosome)
}
isdup := map[tagID]bool{}
reftile := map[tagID]*reftileinfo{}
for seqname, cseq := range refseq {
pos := 0
+ lastreftag := tagID(-1)
for _, libref := range cseq {
+ if cmd.filter.MaxTag >= 0 && libref.Tag > tagID(cmd.filter.MaxTag) {
+ continue
+ }
tiledata := reftiledata[libref]
if len(tiledata) == 0 {
err = fmt.Errorf("missing tiledata for tag %d variant %d in %s in ref", libref.Tag, libref.Variant, seqname)
- return 1
+ return err
}
+ foundthistag := false
+ taglib.FindAll(bufio.NewReader(bytes.NewReader(tiledata[:len(tiledata)-1])), nil, func(tagid tagID, offset, _ int) {
+ if !foundthistag && tagid == libref.Tag {
+ foundthistag = true
+ return
+ }
+ if dupref, ok := reftile[tagid]; ok {
+ log.Printf("dropping reference tile %+v from %s @ %d, tag not unique, also found inside %+v from %s @ %d", tileLibRef{Tag: tagid, Variant: dupref.variant}, dupref.seqname, dupref.pos, libref, seqname, pos+offset+1)
+ delete(reftile, tagid)
+ } else {
+ log.Printf("found tag %d at offset %d inside tile variant %+v on %s @ %d", tagid, offset, libref, seqname, pos+offset+1)
+ }
+ isdup[tagid] = true
+ })
if isdup[libref.Tag] {
log.Printf("dropping reference tile %+v from %s @ %d, tag not unique", libref, seqname, pos)
} else if reftile[libref.Tag] != nil {
variant: libref.Variant,
tiledata: tiledata,
pos: pos,
+ nexttag: -1,
}
+ if lastreftag >= 0 {
+ reftile[lastreftag].nexttag = libref.Tag
+ }
+ lastreftag = libref.Tag
}
pos += len(tiledata) - taglen
}
log.Printf("loading regions from %s", *regionsFilename)
mask, err = makeMask(*regionsFilename, *expandRegions)
if err != nil {
- return 1
+ return err
}
log.Printf("before applying mask, len(reftile) == %d", len(reftile))
log.Printf("deleting reftile entries for regions outside %d intervals", mask.Len())
- for tag, rt := range reftile {
+ for _, rt := range reftile {
if !mask.Check(strings.TrimPrefix(rt.seqname, "chr"), rt.pos, rt.pos+len(rt.tiledata)) {
- delete(reftile, tag)
+ rt.excluded = true
}
}
log.Printf("after applying mask, len(reftile) == %d", len(reftile))
}
+ type hgvsColSet map[hgvs.Variant][2][]int8
+ encodeHGVS := throttle{Max: len(refseq)}
+ encodeHGVSTodo := map[string]chan hgvsColSet{}
tmpHGVSCols := map[string]*os.File{}
- bufHGVSCols := map[string]*bufio.Writer{}
- encodeHGVSCols := map[string]*gob.Encoder{}
if *hgvsChunked {
for seqname := range refseq {
var f *os.File
f, err = os.Create(*outputDir + "/tmp." + seqname + ".gob")
if err != nil {
- return 1
+ return err
}
defer os.Remove(f.Name())
bufw := bufio.NewWriterSize(f, 1<<24)
enc := gob.NewEncoder(bufw)
tmpHGVSCols[seqname] = f
- bufHGVSCols[seqname] = bufw
- encodeHGVSCols[seqname] = enc
+ todo := make(chan hgvsColSet, 128)
+ encodeHGVSTodo[seqname] = todo
+ encodeHGVS.Go(func() error {
+ for colset := range todo {
+ err := enc.Encode(colset)
+ if err != nil {
+ encodeHGVS.Report(err)
+ for range todo {
+ }
+ return err
+ }
+ }
+ return bufw.Flush()
+ })
}
}
if *mergeOutput || *hgvsSingle {
toMerge = make([][]int16, len(infiles))
}
+ var onehotIndirect [][2][]uint32 // [chunkIndex][axis][index]
+ var onehotChunkSize []uint32
+ var onehotXrefs [][]onehotXref
+ if *onehotSingle || *onlyPCA {
+ onehotIndirect = make([][2][]uint32, len(infiles))
+ onehotChunkSize = make([]uint32, len(infiles))
+ onehotXrefs = make([][]onehotXref, len(infiles))
+ }
+ chunkStartTag := make([]tagID, len(infiles))
throttleMem := throttle{Max: cmd.threads} // TODO: estimate using mem and data size
throttleNumpyMem := throttle{Max: cmd.threads/2 + 1}
log.Info("generating annotations and numpy matrix for each slice")
+ var errSkip = errors.New("skip infile")
var done int64
for infileIdx, infile := range infiles {
infileIdx, infile := infileIdx, infile
throttleMem.Go(func() error {
seq := make(map[tagID][]TileVariant, 50000)
- cgs := make(map[string]CompactGenome, len(cgnames))
+ cgs := make(map[string]CompactGenome, len(cmd.cgnames))
f, err := open(infile)
if err != nil {
return err
if tv.Ref {
continue
}
+ // Skip tile with no
+ // corresponding ref tile, if
+ // mask is in play (we can't
+ // determine coordinates for
+ // these)
if mask != nil && reftile[tv.Tag] == nil {
- // Don't waste
- // time/memory on
- // masked-out tiles.
continue
}
+ // Skip tile whose
+ // corresponding ref tile is
+ // outside target regions --
+ // unless it's a potential
+ // spanning tile.
+ if mask != nil && reftile[tv.Tag].excluded &&
+ (int(tv.Tag+1) >= len(tagset) ||
+ (bytes.HasSuffix(tv.Sequence, tagset[tv.Tag+1]) && reftile[tv.Tag+1] != nil && !reftile[tv.Tag+1].excluded)) {
+ continue
+ }
+ if tv.Tag == cmd.debugTag {
+ log.Printf("infile %d %s tag %d variant %d hash %x", infileIdx, infile, tv.Tag, tv.Variant, tv.Blake2b[:3])
+ }
variants := seq[tv.Tag]
if len(variants) == 0 {
variants = make([]TileVariant, 100)
seq[tv.Tag] = variants
}
for _, cg := range ent.CompactGenomes {
- if !matchGenome.MatchString(cg.Name) {
+ if cmd.filter.MaxTag >= 0 && cg.StartTag > tagID(cmd.filter.MaxTag) {
+ return errSkip
+ }
+ if !cgnamemap[cg.Name] {
continue
}
// pad to full slice size
// to avoid out-of-bounds
// checks later
- if sliceSize := int(cg.EndTag - cg.StartTag); len(cg.Variants) < sliceSize {
+ if sliceSize := 2 * int(cg.EndTag-cg.StartTag); len(cg.Variants) < sliceSize {
cg.Variants = append(cg.Variants, make([]tileVariantID, sliceSize-len(cg.Variants))...)
}
cgs[cg.Name] = cg
}
return nil
})
- if err != nil {
- return err
+ if err == errSkip {
+ return nil
+ } else if err != nil {
+ return fmt.Errorf("%04d: DecodeLibrary(%s): %w", infileIdx, infile, err)
}
- tagstart := cgs[cgnames[0]].StartTag
- tagend := cgs[cgnames[0]].EndTag
+ tagstart := cgs[cmd.cgnames[0]].StartTag
+ tagend := cgs[cmd.cgnames[0]].EndTag
+ chunkStartTag[infileIdx] = tagstart
// TODO: filters
throttleCPU := throttle{Max: runtime.GOMAXPROCS(0)}
for tag, variants := range seq {
tag, variants := tag, variants
- throttleCPU.Acquire()
- go func() {
- defer throttleCPU.Release()
+ throttleCPU.Go(func() error {
+ alleleCoverage := 0
count := make(map[[blake2b.Size256]byte]int, len(variants))
rt := reftile[tag]
count[blake2b.Sum256(rt.tiledata)] = 0
}
- for _, cg := range cgs {
+ for cgidx, cgname := range cmd.cgnames {
+ if !cmd.minCoverageAll && !cmd.samples[cgidx].isTraining {
+ continue
+ }
+ cg := cgs[cgname]
idx := int(tag-tagstart) * 2
for allele := 0; allele < 2; allele++ {
v := cg.Variants[idx+allele]
if v > 0 && len(variants[v].Sequence) > 0 {
count[variants[v].Blake2b]++
+ alleleCoverage++
}
+ if v > 0 && tag == cmd.debugTag {
+ log.Printf("tag %d cg %s allele %d tv %d hash %x count is now %d", tag, cgname, allele, v, variants[v].Blake2b[:3], count[variants[v].Blake2b])
+ }
+ }
+ }
+ if alleleCoverage < cmd.minCoverage*2 {
+ idx := int(tag-tagstart) * 2
+ for _, cg := range cgs {
+ cg.Variants[idx] = 0
+ cg.Variants[idx+1] = 0
+ }
+ if tag == cmd.debugTag {
+ log.Printf("tag %d alleleCoverage %d < min %d, sample data wiped", tag, alleleCoverage, cmd.minCoverage*2)
}
+ return nil
}
+
// hash[i] will be the hash of
// the variant(s) that should
// be at rank i (0-based).
for i, h := range hash {
rank[h] = tileVariantID(i + 1)
}
+ if tag == cmd.debugTag {
+ for h, r := range rank {
+ log.Printf("tag %d rank(%x) = %v", tag, h[:3], r)
+ }
+ }
// remap[v] will be the new
// variant number for original
// variant number v.
for i, tv := range variants {
remap[i] = rank[tv.Blake2b]
}
+ if tag == cmd.debugTag {
+ for in, out := range remap {
+ if out > 0 {
+ log.Printf("tag %d remap %d => %d", tag, in, out)
+ }
+ }
+ }
variantRemap[tag-tagstart] = remap
if rt != nil {
- rt.variant = rank[blake2b.Sum256(rt.tiledata)]
+ refrank := rank[blake2b.Sum256(rt.tiledata)]
+ if tag == cmd.debugTag {
+ log.Printf("tag %d reftile variant %d => %d", tag, rt.variant, refrank)
+ }
+ rt.variant = refrank
}
- }()
+ return nil
+ })
}
throttleCPU.Wait()
- annotationsFilename := fmt.Sprintf("%s/matrix.%04d.annotations.csv", *outputDir, infileIdx)
- log.Infof("%04d: writing %s", infileIdx, annotationsFilename)
+ var onehotChunk [][]int8
+ var onehotXref []onehotXref
+
+ var annotationsFilename string
+ if *onlyPCA {
+ annotationsFilename = "/dev/null"
+ } else {
+ annotationsFilename = fmt.Sprintf("%s/matrix.%04d.annotations.csv", *outputDir, infileIdx)
+ log.Infof("%04d: writing %s", infileIdx, annotationsFilename)
+ }
annof, err := os.Create(annotationsFilename)
if err != nil {
return err
annow := bufio.NewWriterSize(annof, 1<<20)
outcol := 0
for tag := tagstart; tag < tagend; tag++ {
- rt, ok := reftile[tag]
- if !ok {
- if mask == nil {
- outcol++
- }
- // Excluded by specified
- // regions, or reference does
- // not use any variant of this
- // tile. (TODO: log this?
- // mention it in annotations?)
+ rt := reftile[tag]
+ if rt == nil && mask != nil {
+ // With no ref tile, we don't
+ // have coordinates to say
+ // this is in the desired
+ // regions -- so it's not.
+ // TODO: handle ref spanning
+ // tile case.
continue
}
- fmt.Fprintf(annow, "%d,%d,%d,=,%s,%d,,,\n", tag, outcol, rt.variant, rt.seqname, rt.pos)
- variants := seq[tag]
- reftilestr := strings.ToUpper(string(rt.tiledata))
+ if rt != nil && rt.excluded {
+ // TODO: don't skip yet --
+ // first check for spanning
+ // tile variants that
+ // intersect non-excluded ref
+ // tiles.
+ continue
+ }
+ if cmd.filter.MaxTag >= 0 && tag > tagID(cmd.filter.MaxTag) {
+ break
+ }
remap := variantRemap[tag-tagstart]
+ if remap == nil {
+ // was not assigned above,
+ // because minCoverage
+ outcol++
+ continue
+ }
maxv := tileVariantID(0)
for _, v := range remap {
if maxv < v {
maxv = v
}
}
+ if *onehotChunked || *onehotSingle || *onlyPCA {
+ onehot, xrefs := cmd.tv2homhet(cgs, maxv, remap, tag, tagstart, seq)
+ if tag == cmd.debugTag {
+ log.WithFields(logrus.Fields{
+ "onehot": onehot,
+ "xrefs": xrefs,
+ }).Info("tv2homhet()")
+ }
+ onehotChunk = append(onehotChunk, onehot...)
+ onehotXref = append(onehotXref, xrefs...)
+ }
+ if *onlyPCA {
+ outcol++
+ continue
+ }
+ if rt == nil {
+ // Reference does not use any
+ // variant of this tile
+ //
+ // TODO: diff against the
+ // relevant portion of the
+ // ref's spanning tile
+ outcol++
+ continue
+ }
+ fmt.Fprintf(annow, "%d,%d,%d,=,%s,%d,,,\n", tag, outcol, rt.variant, rt.seqname, rt.pos)
+ variants := seq[tag]
+ reftilestr := strings.ToUpper(string(rt.tiledata))
+
done := make([]bool, maxv+1)
variantDiffs := make([][]hgvs.Variant, maxv+1)
for v, tv := range variants {
v := remap[v]
- if v == rt.variant || done[v] {
+ if v == 0 || v == rt.variant || done[v] {
continue
} else {
done[v] = true
}
- if len(tv.Sequence) < taglen || !bytes.HasSuffix(rt.tiledata, tv.Sequence[len(tv.Sequence)-taglen:]) {
+ if len(tv.Sequence) < taglen {
+ continue
+ }
+ // if reftilestr doesn't end
+ // in the same tag as tv,
+ // extend reftilestr with
+ // following ref tiles until
+ // it does (up to an arbitrary
+ // sanity-check limit)
+ reftilestr := reftilestr
+ endtagstr := strings.ToUpper(string(tv.Sequence[len(tv.Sequence)-taglen:]))
+ for i, rt := 0, rt; i < annotationMaxTileSpan && !strings.HasSuffix(reftilestr, endtagstr) && rt.nexttag >= 0; i++ {
+ rt = reftile[rt.nexttag]
+ if rt == nil {
+ break
+ }
+ reftilestr += strings.ToUpper(string(rt.tiledata[taglen:]))
+ }
+ if mask != nil && !mask.Check(strings.TrimPrefix(rt.seqname, "chr"), rt.pos, rt.pos+len(reftilestr)) {
+ continue
+ }
+ if !strings.HasSuffix(reftilestr, endtagstr) {
fmt.Fprintf(annow, "%d,%d,%d,,%s,%d,,,\n", tag, outcol, v, rt.seqname, rt.pos)
continue
}
- if lendiff := len(rt.tiledata) - len(tv.Sequence); lendiff < -1000 || lendiff > 1000 {
+ if lendiff := len(reftilestr) - len(tv.Sequence); lendiff < -1000 || lendiff > 1000 {
fmt.Fprintf(annow, "%d,%d,%d,,%s,%d,,,\n", tag, outcol, v, rt.seqname, rt.pos)
continue
}
diffs, _ := hgvs.Diff(reftilestr, strings.ToUpper(string(tv.Sequence)), 0)
+ for i := range diffs {
+ diffs[i].Position += rt.pos
+ }
for _, diff := range diffs {
- diff.Position += rt.pos
fmt.Fprintf(annow, "%d,%d,%d,%s:g.%s,%s,%d,%s,%s,%s\n", tag, outcol, v, rt.seqname, diff.String(), rt.seqname, diff.Position, diff.Ref, diff.New, diff.Left)
}
if *hgvsChunked {
// =ref or a different variant in that
// position, or (-1) is lacking
// coverage / couldn't be diffed.
- hgvsCol := map[hgvs.Variant][2][]int8{}
+ hgvsCol := hgvsColSet{}
for _, diffs := range variantDiffs {
for _, diff := range diffs {
if _, ok := hgvsCol[diff]; ok {
continue
}
hgvsCol[diff] = [2][]int8{
- make([]int8, len(cgnames)),
- make([]int8, len(cgnames)),
+ make([]int8, len(cmd.cgnames)),
+ make([]int8, len(cmd.cgnames)),
}
}
}
- for row, name := range cgnames {
+ for row, name := range cmd.cgnames {
variants := cgs[name].Variants[(tag-tagstart)*2:]
for ph := 0; ph < 2; ph++ {
v := variants[ph]
}
}
}
- encodeHGVSCols[rt.seqname].Encode(hgvsCol)
+ for diff, colpair := range hgvsCol {
+ allele2homhet(colpair)
+ if !cmd.filterHGVScolpair(colpair) {
+ delete(hgvsCol, diff)
+ }
+ }
+ if len(hgvsCol) > 0 {
+ encodeHGVSTodo[rt.seqname] <- hgvsCol
+ }
}
outcol++
}
return err
}
- log.Infof("%04d: preparing numpy", infileIdx)
- throttleNumpyMem.Acquire()
- rows := len(cgnames)
- cols := 2 * outcol
- out := make([]int16, rows*cols)
- for row, name := range cgnames {
- out := out[row*cols:]
- outcol := 0
- for col, v := range cgs[name].Variants {
- tag := tagstart + tagID(col/2)
- if mask != nil && reftile[tag] == nil {
- continue
- }
- if variants, ok := seq[tag]; ok && len(variants) > int(v) && len(variants[v].Sequence) > 0 {
- out[outcol] = int16(variantRemap[tag-tagstart][v])
- } else {
- out[outcol] = -1
- }
- outcol++
+ if *onehotChunked {
+ // transpose onehotChunk[col][row] to numpy[row*ncols+col]
+ rows := len(cmd.cgnames)
+ cols := len(onehotChunk)
+ log.Infof("%04d: preparing onehot numpy (rows=%d, cols=%d, mem=%d)", infileIdx, rows, cols, rows*cols)
+ throttleNumpyMem.Acquire()
+ out := onehotcols2int8(onehotChunk)
+ fnm := fmt.Sprintf("%s/onehot.%04d.npy", *outputDir, infileIdx)
+ err = writeNumpyInt8(fnm, out, rows, cols)
+ if err != nil {
+ return err
}
- }
- seq = nil
- cgs = nil
- debug.FreeOSMemory()
- throttleNumpyMem.Release()
-
- if *mergeOutput || *hgvsSingle {
- log.Infof("%04d: matrix fragment %d rows x %d cols", infileIdx, rows, cols)
- toMerge[infileIdx] = out
- }
- if !*mergeOutput {
- fnm := fmt.Sprintf("%s/matrix.%04d.npy", *outputDir, infileIdx)
- err = writeNumpyInt16(fnm, out, rows, cols)
+ fnm = fmt.Sprintf("%s/onehot-columns.%04d.npy", *outputDir, infileIdx)
+ err = writeNumpyInt32(fnm, onehotXref2int32(onehotXref), 4, len(onehotXref))
if err != nil {
return err
}
debug.FreeOSMemory()
+ throttleNumpyMem.Release()
+ }
+ if *onehotSingle || *onlyPCA {
+ onehotIndirect[infileIdx] = onehotChunk2Indirect(onehotChunk)
+ onehotChunkSize[infileIdx] = uint32(len(onehotChunk))
+ onehotXrefs[infileIdx] = onehotXref
+ n := len(onehotIndirect[infileIdx][0])
+ log.Infof("%04d: keeping onehot coordinates in memory (n=%d, mem=%d)", infileIdx, n, n*8*2)
}
+ if !(*onehotSingle || *onehotChunked || *onlyPCA) || *mergeOutput || *hgvsSingle {
+ log.Infof("%04d: preparing numpy (rows=%d, cols=%d)", infileIdx, len(cmd.cgnames), 2*outcol)
+ throttleNumpyMem.Acquire()
+ rows := len(cmd.cgnames)
+ cols := 2 * outcol
+ out := make([]int16, rows*cols)
+ for row, name := range cmd.cgnames {
+ outidx := row * cols
+ for col, v := range cgs[name].Variants {
+ tag := tagstart + tagID(col/2)
+ if cmd.filter.MaxTag >= 0 && tag > tagID(cmd.filter.MaxTag) {
+ break
+ }
+ if rt := reftile[tag]; mask != nil && (rt == nil || rt.excluded) {
+ continue
+ }
+ if v == 0 {
+ out[outidx] = 0 // tag not found / spanning tile
+ } else if variants, ok := seq[tag]; ok && int(v) < len(variants) && len(variants[v].Sequence) > 0 {
+ out[outidx] = int16(variantRemap[tag-tagstart][v])
+ } else {
+ out[outidx] = -1 // low quality tile variant
+ }
+ if tag == cmd.debugTag {
+ log.Printf("tag %d row %d col %d outidx %d v %d out %d", tag, row, col, outidx, v, out[outidx])
+ }
+ outidx++
+ }
+ }
+ seq = nil
+ cgs = nil
+ debug.FreeOSMemory()
+ throttleNumpyMem.Release()
+ if *mergeOutput || *hgvsSingle {
+ log.Infof("%04d: matrix fragment %d rows x %d cols", infileIdx, rows, cols)
+ toMerge[infileIdx] = out
+ }
+ if !*mergeOutput && !*onehotChunked && !*onehotSingle {
+ fnm := fmt.Sprintf("%s/matrix.%04d.npy", *outputDir, infileIdx)
+ err = writeNumpyInt16(fnm, out, rows, cols)
+ if err != nil {
+ return err
+ }
+ }
+ }
+ debug.FreeOSMemory()
log.Infof("%s: done (%d/%d)", infile, int(atomic.AddInt64(&done, 1)), len(infiles))
return nil
})
}
if err = throttleMem.Wait(); err != nil {
- return 1
+ return err
}
if *hgvsChunked {
log.Info("flushing hgvsCols temp files")
for seqname := range refseq {
- err = bufHGVSCols[seqname].Flush()
- if err != nil {
- return 1
- }
- bufHGVSCols[seqname] = nil // free buffer memory
+ close(encodeHGVSTodo[seqname])
+ }
+ err = encodeHGVS.Wait()
+ if err != nil {
+ return err
}
for seqname := range refseq {
log.Infof("%s: reading hgvsCols from temp file", seqname)
f := tmpHGVSCols[seqname]
_, err = f.Seek(0, io.SeekStart)
if err != nil {
- return 1
+ return err
}
- var hgvsCols map[hgvs.Variant][2][]int8
+ var hgvsCols hgvsColSet
dec := gob.NewDecoder(bufio.NewReaderSize(f, 1<<24))
for err == nil {
err = dec.Decode(&hgvsCols)
}
if err != io.EOF {
- return 1
+ return err
}
log.Infof("%s: sorting %d hgvs variants", seqname, len(hgvsCols))
variants := make([]hgvs.Variant, 0, len(hgvsCols))
return vi.New < vj.New
}
})
- rows := len(cgnames)
+ rows := len(cmd.cgnames)
cols := len(variants) * 2
log.Infof("%s: building hgvs matrix (rows=%d, cols=%d, mem=%d)", seqname, rows, cols, rows*cols)
out := make([]int8, rows*cols)
for varIdx, variant := range variants {
hgvsCols := hgvsCols[variant]
- for row := range cgnames {
+ for row := range cmd.cgnames {
for ph := 0; ph < 2; ph++ {
out[row*cols+varIdx+ph] = hgvsCols[ph][row]
}
}
err = writeNumpyInt8(fmt.Sprintf("%s/hgvs.%s.npy", *outputDir, seqname), out, rows, cols)
if err != nil {
- return 1
+ return err
}
out = nil
}
err = ioutil.WriteFile(fnm, hgvsLabels.Bytes(), 0666)
if err != nil {
- return 1
+ return err
}
}
}
annoFilename := fmt.Sprintf("%s/matrix.annotations.csv", *outputDir)
annof, err = os.Create(annoFilename)
if err != nil {
- return 1
+ return err
}
annow = bufio.NewWriterSize(annof, 1<<20)
}
- rows := len(cgnames)
+ rows := len(cmd.cgnames)
cols := 0
for _, chunk := range toMerge {
cols += len(chunk) / rows
log.Infof("reading %s", annotationsFilename)
buf, err := os.ReadFile(annotationsFilename)
if err != nil {
- return 1
+ return err
}
if *mergeOutput {
err = os.Remove(annotationsFilename)
if err != nil {
- return 1
+ return err
}
}
for _, line := range bytes.Split(buf, []byte{'\n'}) {
// change to 1 ("hgvs variant
// present") below, either on
// this line or a future line.
- hgvsColPair = [2][]int16{make([]int16, len(cgnames)), make([]int16, len(cgnames))}
+ hgvsColPair = [2][]int16{make([]int16, len(cmd.cgnames)), make([]int16, len(cmd.cgnames))}
rt, ok := reftile[tagID(tag)]
if !ok {
err = fmt.Errorf("bug: seeing annotations for tag %d, but it has no reftile entry", tag)
- return 1
+ return err
}
for ph := 0; ph < 2; ph++ {
for row := 0; row < rows; row++ {
if *mergeOutput {
err = annow.Flush()
if err != nil {
- return 1
+ return err
}
err = annof.Close()
if err != nil {
- return 1
+ return err
}
err = writeNumpyInt16(fmt.Sprintf("%s/matrix.npy", *outputDir), out, rows, cols)
if err != nil {
- return 1
+ return err
}
}
out = nil
}
err = writeNumpyInt16(fmt.Sprintf("%s/hgvs.npy", *outputDir), out, rows, cols)
if err != nil {
- return 1
+ return err
}
fnm := fmt.Sprintf("%s/hgvs.annotations.csv", *outputDir)
log.Printf("writing hgvs labels: %s", fnm)
err = ioutil.WriteFile(fnm, hgvsLabels.Bytes(), 0777)
if err != nil {
- return 1
+ return err
}
}
}
- return 0
+ if *onehotSingle || *onlyPCA {
+ nzCount := 0
+ for _, part := range onehotIndirect {
+ nzCount += len(part[0])
+ }
+ onehot := make([]uint32, nzCount*2) // [r,r,r,...,c,c,c,...]
+ var xrefs []onehotXref
+ chunkOffset := uint32(0)
+ outcol := 0
+ for i, part := range onehotIndirect {
+ for i := range part[1] {
+ part[1][i] += chunkOffset
+ }
+ copy(onehot[outcol:], part[0])
+ copy(onehot[outcol+nzCount:], part[1])
+ xrefs = append(xrefs, onehotXrefs[i]...)
+
+ outcol += len(part[0])
+ chunkOffset += onehotChunkSize[i]
+
+ part[0] = nil
+ part[1] = nil
+ onehotXrefs[i] = nil
+ debug.FreeOSMemory()
+ }
+ if *onehotSingle {
+ fnm := fmt.Sprintf("%s/onehot.npy", *outputDir)
+ err = writeNumpyUint32(fnm, onehot, 2, nzCount)
+ if err != nil {
+ return err
+ }
+ fnm = fmt.Sprintf("%s/onehot-columns.npy", *outputDir)
+ err = writeNumpyInt32(fnm, onehotXref2int32(xrefs), 5, len(xrefs))
+ if err != nil {
+ return err
+ }
+ fnm = fmt.Sprintf("%s/stats.json", *outputDir)
+ j, err := json.Marshal(map[string]interface{}{
+ "pvalueCallCount": cmd.pvalueCallCount,
+ })
+ if err != nil {
+ return err
+ }
+ err = os.WriteFile(fnm, j, 0777)
+ if err != nil {
+ return err
+ }
+ }
+ if *onlyPCA {
+ cols := 0
+ for _, c := range onehot[nzCount:] {
+ if int(c) >= cols {
+ cols = int(c) + 1
+ }
+ }
+ if cols == 0 {
+ return fmt.Errorf("cannot do PCA: one-hot matrix is empty")
+ }
+ log.Printf("have %d one-hot cols", cols)
+ stride := 1
+ for *maxPCATiles > 0 && cols > *maxPCATiles*2 {
+ cols = (cols + 1) / 2
+ stride = stride * 2
+ }
+ if cols%2 == 1 {
+ // we work with pairs of columns
+ cols++
+ }
+ log.Printf("creating full matrix (%d rows) and training matrix (%d rows) with %d cols, stride %d", len(cmd.cgnames), cmd.trainingSetSize, cols, stride)
+ mtxFull := mat.NewDense(len(cmd.cgnames), cols, nil)
+ mtxTrain := mat.NewDense(cmd.trainingSetSize, cols, nil)
+ for i, c := range onehot[nzCount:] {
+ if int(c/2)%stride == 0 {
+ outcol := int(c/2)/stride*2 + int(c)%2
+ mtxFull.Set(int(onehot[i]), outcol, 1)
+ if trainRow := cmd.trainingSet[int(onehot[i])]; trainRow >= 0 {
+ mtxTrain.Set(trainRow, outcol, 1)
+ }
+ }
+ }
+ log.Print("fitting")
+ transformer := nlp.NewPCA(cmd.pcaComponents)
+ transformer.Fit(mtxTrain.T())
+ log.Printf("transforming")
+ pca, err := transformer.Transform(mtxFull.T())
+ if err != nil {
+ return err
+ }
+ pca = pca.T()
+ outrows, outcols := pca.Dims()
+ log.Printf("copying result to numpy output array: %d rows, %d cols", outrows, outcols)
+ out := make([]float64, outrows*outcols)
+ for i := 0; i < outrows; i++ {
+ for j := 0; j < outcols; j++ {
+ out[i*outcols+j] = pca.At(i, j)
+ }
+ }
+ fnm := fmt.Sprintf("%s/pca.npy", *outputDir)
+ log.Printf("writing numpy: %s", fnm)
+ output, err := os.OpenFile(fnm, os.O_CREATE|os.O_TRUNC|os.O_WRONLY, 0777)
+ if err != nil {
+ return err
+ }
+ npw, err := gonpy.NewWriter(nopCloser{output})
+ if err != nil {
+ return fmt.Errorf("gonpy.NewWriter: %w", err)
+ }
+ npw.Shape = []int{outrows, outcols}
+ err = npw.WriteFloat64(out)
+ if err != nil {
+ return fmt.Errorf("WriteFloat64: %w", err)
+ }
+ err = output.Close()
+ if err != nil {
+ return err
+ }
+ log.Print("done")
+
+ log.Print("copying pca components to sampleInfo")
+ for i := range cmd.samples {
+ cmd.samples[i].pcaComponents = make([]float64, outcols)
+ for c := 0; c < outcols; c++ {
+ cmd.samples[i].pcaComponents[c] = pca.At(i, c)
+ }
+ }
+ log.Print("done")
+
+ err = writeSampleInfo(cmd.samples, *outputDir)
+ if err != nil {
+ return err
+ }
+ }
+ }
+ if !*mergeOutput && !*onehotChunked && !*onehotSingle && !*onlyPCA {
+ tagoffsetFilename := *outputDir + "/chunk-tag-offset.csv"
+ log.Infof("writing tag offsets to %s", tagoffsetFilename)
+ var f *os.File
+ f, err = os.Create(tagoffsetFilename)
+ if err != nil {
+ return err
+ }
+ defer f.Close()
+ for idx, offset := range chunkStartTag {
+ _, err = fmt.Fprintf(f, "%q,%d\n", fmt.Sprintf("matrix.%04d.npy", idx), offset)
+ if err != nil {
+ err = fmt.Errorf("write %s: %w", tagoffsetFilename, err)
+ return err
+ }
+ }
+ err = f.Close()
+ if err != nil {
+ err = fmt.Errorf("close %s: %w", tagoffsetFilename, err)
+ return err
+ }
+ }
+
+ return nil
+}
+
+type sampleInfo struct {
+ id string
+ isCase bool
+ isControl bool
+ isTraining bool
+ isValidation bool
+ pcaComponents []float64
+}
+
+// Read samples.csv file with case/control and training/validation
+// flags.
+func loadSampleInfo(samplesFilename string) ([]sampleInfo, error) {
+ var si []sampleInfo
+ f, err := open(samplesFilename)
+ if err != nil {
+ return nil, err
+ }
+ buf, err := io.ReadAll(f)
+ f.Close()
+ if err != nil {
+ return nil, err
+ }
+ lineNum := 0
+ for _, csv := range bytes.Split(buf, []byte{'\n'}) {
+ lineNum++
+ if len(csv) == 0 {
+ continue
+ }
+ split := strings.Split(string(csv), ",")
+ if len(split) < 4 {
+ return nil, fmt.Errorf("%d fields < 4 in %s line %d: %q", len(split), samplesFilename, lineNum, csv)
+ }
+ if split[0] == "Index" && split[1] == "SampleID" && split[2] == "CaseControl" && split[3] == "TrainingValidation" {
+ continue
+ }
+ idx, err := strconv.Atoi(split[0])
+ if err != nil {
+ if lineNum == 1 {
+ return nil, fmt.Errorf("header does not look right: %q", csv)
+ }
+ return nil, fmt.Errorf("%s line %d: index: %s", samplesFilename, lineNum, err)
+ }
+ if idx != len(si) {
+ return nil, fmt.Errorf("%s line %d: index %d out of order", samplesFilename, lineNum, idx)
+ }
+ var pcaComponents []float64
+ if len(split) > 4 {
+ for _, s := range split[4:] {
+ f, err := strconv.ParseFloat(s, 64)
+ if err != nil {
+ return nil, fmt.Errorf("%s line %d: cannot parse float %q: %s", samplesFilename, lineNum, s, err)
+ }
+ pcaComponents = append(pcaComponents, f)
+ }
+ }
+ si = append(si, sampleInfo{
+ id: split[1],
+ isCase: split[2] == "1",
+ isControl: split[2] == "0",
+ isTraining: split[3] == "1",
+ isValidation: split[3] == "0" && len(split[2]) > 0, // fix errant 0s in input
+ pcaComponents: pcaComponents,
+ })
+ }
+ return si, nil
+}
+
+func writeSampleInfo(samples []sampleInfo, outputDir string) error {
+ fnm := outputDir + "/samples.csv"
+ log.Infof("writing sample metadata to %s", fnm)
+ f, err := os.Create(fnm)
+ if err != nil {
+ return err
+ }
+ defer f.Close()
+ pcaLabels := ""
+ if len(samples) > 0 {
+ for i := range samples[0].pcaComponents {
+ pcaLabels += fmt.Sprintf(",PCA%d", i)
+ }
+ }
+ _, err = fmt.Fprintf(f, "Index,SampleID,CaseControl,TrainingValidation%s\n", pcaLabels)
+ if err != nil {
+ return err
+ }
+ for i, si := range samples {
+ var cc, tv string
+ if si.isCase {
+ cc = "1"
+ } else if si.isControl {
+ cc = "0"
+ }
+ if si.isTraining {
+ tv = "1"
+ } else if si.isValidation {
+ tv = "0"
+ }
+ var pcavals string
+ for _, pcaval := range si.pcaComponents {
+ pcavals += fmt.Sprintf(",%f", pcaval)
+ }
+ _, err = fmt.Fprintf(f, "%d,%s,%s,%s%s\n", i, si.id, cc, tv, pcavals)
+ if err != nil {
+ return fmt.Errorf("write %s: %w", fnm, err)
+ }
+ }
+ err = f.Close()
+ if err != nil {
+ return fmt.Errorf("close %s: %w", fnm, err)
+ }
+ log.Print("done")
+ return nil
+}
+
+func (cmd *sliceNumpy) filterHGVScolpair(colpair [2][]int8) bool {
+ if cmd.chi2PValue >= 1 {
+ return true
+ }
+ col0 := make([]bool, 0, len(cmd.chi2Cases))
+ col1 := make([]bool, 0, len(cmd.chi2Cases))
+ cases := make([]bool, 0, len(cmd.chi2Cases))
+ for i, c := range cmd.chi2Cases {
+ if colpair[0][i] < 0 {
+ continue
+ }
+ col0 = append(col0, colpair[0][i] != 0)
+ col1 = append(col1, colpair[1][i] != 0)
+ cases = append(cases, c)
+ }
+ return len(cases) >= cmd.minCoverage &&
+ (pvalue(col0, cases) <= cmd.chi2PValue || pvalue(col1, cases) <= cmd.chi2PValue)
+}
+
+func writeNumpyUint32(fnm string, out []uint32, rows, cols int) error {
+ output, err := os.Create(fnm)
+ if err != nil {
+ return err
+ }
+ defer output.Close()
+ bufw := bufio.NewWriterSize(output, 1<<26)
+ npw, err := gonpy.NewWriter(nopCloser{bufw})
+ if err != nil {
+ return err
+ }
+ log.WithFields(log.Fields{
+ "filename": fnm,
+ "rows": rows,
+ "cols": cols,
+ "bytes": rows * cols * 4,
+ }).Infof("writing numpy: %s", fnm)
+ npw.Shape = []int{rows, cols}
+ npw.WriteUint32(out)
+ err = bufw.Flush()
+ if err != nil {
+ return err
+ }
+ return output.Close()
+}
+
+func writeNumpyInt32(fnm string, out []int32, rows, cols int) error {
+ output, err := os.Create(fnm)
+ if err != nil {
+ return err
+ }
+ defer output.Close()
+ bufw := bufio.NewWriterSize(output, 1<<26)
+ npw, err := gonpy.NewWriter(nopCloser{bufw})
+ if err != nil {
+ return err
+ }
+ log.WithFields(log.Fields{
+ "filename": fnm,
+ "rows": rows,
+ "cols": cols,
+ "bytes": rows * cols * 4,
+ }).Infof("writing numpy: %s", fnm)
+ npw.Shape = []int{rows, cols}
+ npw.WriteInt32(out)
+ err = bufw.Flush()
+ if err != nil {
+ return err
+ }
+ return output.Close()
}
func writeNumpyInt16(fnm string, out []int16, rows, cols int) error {
"filename": fnm,
"rows": rows,
"cols": cols,
+ "bytes": rows * cols * 2,
}).Infof("writing numpy: %s", fnm)
npw.Shape = []int{rows, cols}
npw.WriteInt16(out)
"filename": fnm,
"rows": rows,
"cols": cols,
+ "bytes": rows * cols,
}).Infof("writing numpy: %s", fnm)
npw.Shape = []int{rows, cols}
npw.WriteInt8(out)
}
return output.Close()
}
+
+func allele2homhet(colpair [2][]int8) {
+ a, b := colpair[0], colpair[1]
+ for i, av := range a {
+ bv := b[i]
+ if av < 0 || bv < 0 {
+ // no-call
+ a[i], b[i] = -1, -1
+ } else if av > 0 && bv > 0 {
+ // hom
+ a[i], b[i] = 1, 0
+ } else if av > 0 || bv > 0 {
+ // het
+ a[i], b[i] = 0, 1
+ } else {
+ // ref (or a different variant in same position)
+ // (this is a no-op) a[i], b[i] = 0, 0
+ }
+ }
+}
+
+type onehotXref struct {
+ tag tagID
+ variant tileVariantID
+ hom bool
+ pvalue float64
+ maf float64
+}
+
+const onehotXrefSize = unsafe.Sizeof(onehotXref{})
+
+// Build onehot matrix (m[tileVariantIndex][genome] == 0 or 1) for all
+// variants of a single tile/tag#.
+//
+// Return nil if no tile variant passes Χ² filter.
+func (cmd *sliceNumpy) tv2homhet(cgs map[string]CompactGenome, maxv tileVariantID, remap []tileVariantID, tag, chunkstarttag tagID, seq map[tagID][]TileVariant) ([][]int8, []onehotXref) {
+ if tag == cmd.debugTag {
+ tv := make([]tileVariantID, len(cmd.cgnames)*2)
+ for i, name := range cmd.cgnames {
+ copy(tv[i*2:(i+1)*2], cgs[name].Variants[(tag-chunkstarttag)*2:])
+ }
+ log.WithFields(logrus.Fields{
+ "cgs[i].Variants[tag*2+j]": tv,
+ "maxv": maxv,
+ "remap": remap,
+ "tag": tag,
+ "chunkstarttag": chunkstarttag,
+ }).Info("tv2homhet()")
+ }
+ if maxv < 1 || (maxv < 2 && !cmd.includeVariant1) {
+ // everyone has the most common variant (of the variants we don't drop)
+ return nil, nil
+ }
+ tagoffset := tag - chunkstarttag
+ coverage := 0
+ for cgidx, cgname := range cmd.cgnames {
+ if !cmd.minCoverageAll && !cmd.samples[cgidx].isTraining {
+ continue
+ }
+ cg := cgs[cgname]
+ alleles := 0
+ for _, v := range cg.Variants[tagoffset*2 : tagoffset*2+2] {
+ if v > 0 && int(v) < len(seq[tag]) && len(seq[tag][v].Sequence) > 0 {
+ alleles++
+ }
+ }
+ if alleles == 2 {
+ coverage++
+ }
+ }
+ if coverage < cmd.minCoverage {
+ return nil, nil
+ }
+ // "observed" array for p-value calculation (training set
+ // only)
+ obs := make([][]bool, (maxv+1)*2) // 2 slices (hom + het) for each variant#
+ // one-hot output (all samples)
+ outcols := make([][]int8, (maxv+1)*2)
+ for i := range obs {
+ obs[i] = make([]bool, cmd.trainingSetSize)
+ outcols[i] = make([]int8, len(cmd.cgnames))
+ }
+ for cgid, name := range cmd.cgnames {
+ tsid := cmd.trainingSet[cgid]
+ cgvars := cgs[name].Variants[tagoffset*2:]
+ tv0, tv1 := remap[cgvars[0]], remap[cgvars[1]]
+ for v := tileVariantID(1); v <= maxv; v++ {
+ if tv0 == v && tv1 == v {
+ if tsid >= 0 {
+ obs[v*2][tsid] = true
+ }
+ outcols[v*2][cgid] = 1
+ } else if tv0 == v || tv1 == v {
+ if tsid >= 0 {
+ obs[v*2+1][tsid] = true
+ }
+ outcols[v*2+1][cgid] = 1
+ }
+ }
+ }
+ var onehot [][]int8
+ var xref []onehotXref
+ var maf float64
+ for col := 2; col < len(obs); col++ {
+ // col 0,1 correspond to tile variant 0, i.e.,
+ // no-call; col 2,3 correspond to the most common
+ // variant; so we (normally) start at col 4.
+ if col < 4 && !cmd.includeVariant1 {
+ continue
+ }
+ if col&1 == 0 {
+ maf = homhet2maf(obs[col : col+2])
+ if maf < cmd.pvalueMinFrequency {
+ // Skip both columns (hom and het) if
+ // allele frequency is below threshold
+ col++
+ continue
+ }
+ if maf > cmd.maxFrequency {
+ // Skip both columns if allele
+ // frequency is above threshold
+ col++
+ continue
+ }
+ }
+ atomic.AddInt64(&cmd.pvalueCallCount, 1)
+ p := cmd.pvalue(obs[col])
+ if cmd.chi2PValue < 1 && !(p < cmd.chi2PValue) {
+ continue
+ }
+ onehot = append(onehot, outcols[col])
+ xref = append(xref, onehotXref{
+ tag: tag,
+ variant: tileVariantID(col >> 1),
+ hom: col&1 == 0,
+ pvalue: p,
+ maf: maf,
+ })
+ }
+ return onehot, xref
+}
+
+func homhet2maf(onehot [][]bool) float64 {
+ if len(onehot[0]) == 0 {
+ return 0
+ }
+ n := 0
+ for i := range onehot[0] {
+ if onehot[0][i] {
+ // hom
+ n += 2
+ } else if onehot[1][i] {
+ // het
+ n += 1
+ }
+ }
+ return float64(n) / float64(len(onehot[0])*2)
+}
+
+// convert a []onehotXref with length N to a numpy-style []int32
+// matrix with N columns, one row per field of onehotXref struct.
+//
+// Hom/het row contains hom=0, het=1.
+//
+// P-value row contains 1000000x actual p-value.
+func onehotXref2int32(xrefs []onehotXref) []int32 {
+ xcols := len(xrefs)
+ xdata := make([]int32, 6*xcols)
+ for i, xref := range xrefs {
+ xdata[i] = int32(xref.tag)
+ xdata[xcols+i] = int32(xref.variant)
+ if xref.hom {
+ xdata[xcols*2+i] = 1
+ }
+ xdata[xcols*3+i] = int32(xref.pvalue * 1000000)
+ xdata[xcols*4+i] = int32(-math.Log10(xref.pvalue) * 1000000)
+ xdata[xcols*5+i] = int32(xref.maf * 1000000)
+ }
+ return xdata
+}
+
+// transpose onehot data from in[col][row] to numpy-style
+// out[row*cols+col].
+func onehotcols2int8(in [][]int8) []int8 {
+ if len(in) == 0 {
+ return nil
+ }
+ cols := len(in)
+ rows := len(in[0])
+ out := make([]int8, rows*cols)
+ for row := 0; row < rows; row++ {
+ outrow := out[row*cols:]
+ for col, incol := range in {
+ outrow[col] = incol[row]
+ }
+ }
+ return out
+}
+
+// Return [2][]uint32{rowIndices, colIndices} indicating which
+// elements of matrixT[c][r] have non-zero values.
+func onehotChunk2Indirect(matrixT [][]int8) [2][]uint32 {
+ var nz [2][]uint32
+ for c, col := range matrixT {
+ for r, val := range col {
+ if val != 0 {
+ nz[0] = append(nz[0], uint32(r))
+ nz[1] = append(nz[1], uint32(c))
+ }
+ }
+ }
+ return nz
+}
projects / lightning.git / blobdiff