const annotationMaxTileSpan = 100
type sliceNumpy struct {
- filter filter
- threads int
- chi2CaseControlColumn string
- chi2CaseControlFile string
- chi2Cases []bool
- chi2PValue float64
- trainingSet []int // see loadTrainingSet
- trainingSetSize int
- minCoverage int
- cgnames []string
- includeVariant1 bool
- debugTag tagID
+ filter filter
+ threads int
+ chi2Cases []bool
+ chi2PValue float64
+ minCoverage int
+ includeVariant1 bool
+ debugTag tagID
+
+ cgnames []string
+ samples []sampleInfo
+ trainingSet []int // samples index => training set index, or -1 if not in training set
+ trainingSetSize int
}
func (cmd *sliceNumpy) RunCommand(prog string, args []string, stdin io.Reader, stdout, stderr io.Writer) int {
hgvsChunked := flags.Bool("chunked-hgvs-matrix", false, "also generate hgvs-based matrix per chromosome")
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")
- trainingSetFilename := flags.String("training-set", "", "`tsv` file with sample IDs to be used for PCA fitting and Χ² test (if not provided, use all samples)")
+ samplesFilename := flags.String("samples", "", "`samples.csv` file with training/validation and case/control groups (see 'lightning choose-samples')")
onlyPCA := flags.Bool("pca", false, "generate pca matrix")
pcaComponents := flags.Int("pca-components", 4, "number of PCA components")
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.IntVar(&cmd.threads, "threads", 16, "number of memory-hungry assembly threads, and number of VCPUs to request for arvados container")
- flags.StringVar(&cmd.chi2CaseControlFile, "chi2-case-control-file", "", "tsv file or directory indicating cases and controls for Χ² test (if directory, all .tsv files will be read)")
- flags.StringVar(&cmd.chi2CaseControlColumn, "chi2-case-control-column", "", "name of case/control column in case-control files for Χ² test (value must be 0 for control, 1 for case)")
flags.Float64Var(&cmd.chi2PValue, "chi2-p-value", 1, "do Χ² test and omit columns with p-value above this threshold")
flags.BoolVar(&cmd.includeVariant1, "include-variant-1", false, "include most common variant when building one-hot matrix")
cmd.filter.Flags(flags)
}()
}
- if cmd.chi2PValue != 1 && (cmd.chi2CaseControlFile == "" || cmd.chi2CaseControlColumn == "") {
- return fmt.Errorf("cannot use provided -chi2-p-value=%f because -chi2-case-control-file= or -chi2-case-control-column= value is empty", cmd.chi2PValue)
+ 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)
KeepCache: 2,
APIAccess: true,
}
- err = runner.TranslatePaths(inputDir, regionsFilename, trainingSetFilename, &cmd.chi2CaseControlFile)
+ err = runner.TranslatePaths(inputDir, regionsFilename, samplesFilename)
if err != nil {
return err
}
"-chunked-hgvs-matrix=" + fmt.Sprintf("%v", *hgvsChunked),
"-single-onehot=" + fmt.Sprintf("%v", *onehotSingle),
"-chunked-onehot=" + fmt.Sprintf("%v", *onehotChunked),
- "-training-set=" + *trainingSetFilename,
+ "-samples=" + *samplesFilename,
"-pca=" + fmt.Sprintf("%v", *onlyPCA),
"-pca-components=" + fmt.Sprintf("%d", *pcaComponents),
"-max-pca-tiles=" + fmt.Sprintf("%d", *maxPCATiles),
- "-chi2-case-control-file=" + cmd.chi2CaseControlFile,
- "-chi2-case-control-column=" + cmd.chi2CaseControlColumn,
"-chi2-p-value=" + fmt.Sprintf("%f", cmd.chi2PValue),
"-include-variant-1=" + fmt.Sprintf("%v", cmd.includeVariant1),
"-debug-tag=" + fmt.Sprintf("%d", cmd.debugTag),
return err
}
+ if *samplesFilename != "" {
+ cmd.samples, err = cmd.loadSampleInfo(*samplesFilename)
+ if err != nil {
+ return err
+ }
+ }
+
cmd.cgnames = nil
var tagset [][]byte
err = DecodeLibrary(in0, strings.HasSuffix(infiles[0], ".gz"), func(ent *LibraryEntry) error {
return err
}
taglen := taglib.TagLen()
-
- if len(cmd.cgnames) == 0 {
- err = fmt.Errorf("no genomes found matching regexp %q", cmd.filter.MatchGenome)
- return err
- }
sort.Strings(cmd.cgnames)
- err = cmd.useCaseControlFiles()
- if err != nil {
- return err
- }
+
if len(cmd.cgnames) == 0 {
- err = fmt.Errorf("fatal: 0 cases, 0 controls, nothing to do")
- return err
+ return fmt.Errorf("fatal: 0 matching samples in library, nothing to do")
}
- err = cmd.loadTrainingSet(*trainingSetFilename)
- if err != nil {
- return err
+ 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
+ }
+ } 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 {
+ cmd.trainingSetSize = 0
+ 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)
+ }
+ if cmd.samples[i].isTraining {
+ cmd.trainingSet[i] = cmd.trainingSetSize
+ cmd.trainingSetSize++
+ } else {
+ cmd.trainingSet[i] = -1
+ }
+ }
}
if cmd.filter.MinCoverage == 1 {
// In the generic formula below, floating point
cmd.minCoverage = int(math.Ceil(cmd.filter.MinCoverage * float64(len(cmd.cgnames))))
}
- {
- labelsFilename := *outputDir + "/samples.csv"
- log.Infof("writing labels to %s", labelsFilename)
- var f *os.File
- f, err = os.Create(labelsFilename)
- if err != nil {
- return err
- }
- defer f.Close()
- for i, name := range cmd.cgnames {
- cc := 0
- if cmd.chi2Cases != nil && cmd.chi2Cases[i] {
- cc = 1
- }
- _, err = fmt.Fprintf(f, "%d,%q,%d\n", i, trimFilenameForLabel(name), cc)
- if err != nil {
- err = fmt.Errorf("write %s: %w", labelsFilename, err)
- return err
- }
- }
- err = f.Close()
- if err != nil {
- err = fmt.Errorf("close %s: %w", labelsFilename, err)
- return err
- }
- }
-
log.Info("indexing reference tiles")
type reftileinfo struct {
variant tileVariantID
return err
}
log.Print("done")
+
+ samplesOutFilename := *outputDir + "/samples.csv"
+ log.Infof("writing sample metadata to %s", samplesOutFilename)
+ var f *os.File
+ f, err = os.Create(samplesOutFilename)
+ if err != nil {
+ return err
+ }
+ defer f.Close()
+ for i, si := range cmd.samples {
+ var cc, tv string
+ if si.isCase {
+ cc = "1"
+ } else if si.isControl {
+ cc = "0"
+ }
+ if si.isTraining {
+ tv = "1"
+ } else {
+ tv = "0"
+ }
+ var pcavals string
+ for c := 0; c < outcols; c++ {
+ pcavals += fmt.Sprintf(",%f", pca.At(i, c))
+ }
+ _, err = fmt.Fprintf(f, "%d,%s,%s,%s%s\n", i, si.id, cc, tv, pcavals)
+ if err != nil {
+ err = fmt.Errorf("write %s: %w", samplesOutFilename, err)
+ return err
+ }
+ }
+ err = f.Close()
+ if err != nil {
+ err = fmt.Errorf("close %s: %w", samplesOutFilename, err)
+ return err
+ }
+ log.Print("done")
}
}
if !*mergeOutput && !*onehotChunked && !*onehotSingle && !*onlyPCA {
return err
}
}
+
return nil
}
-// Read training set file(s) from path (may be dir or file) and set up
-// cmd.trainingSet.
-//
-// cmd.trainingSet[i] == n >= 0 if cmd.cgnames[i] is the nth training
-// set sample.
-//
-// cmd.trainingSet[i] == -1 if cmd.cgnames[i] is not in the training
-// set.
-func (cmd *sliceNumpy) loadTrainingSet(path string) error {
- cmd.trainingSet = make([]int, len(cmd.cgnames))
- if path == "" {
- cmd.trainingSetSize = len(cmd.cgnames)
- for i := range cmd.trainingSet {
- cmd.trainingSet[i] = i
- }
- return nil
- }
- for i := range cmd.trainingSet {
- cmd.trainingSet[i] = -1
- }
- infiles, err := allFiles(path, nil)
- if err != nil {
- return err
- }
- for _, infile := range infiles {
- f, err := open(infile)
- if err != nil {
- return err
- }
- buf, err := io.ReadAll(f)
- f.Close()
- if err != nil {
- return err
- }
- for _, tsv := range bytes.Split(buf, []byte{'\n'}) {
- if len(tsv) == 0 {
- continue
- }
- split := strings.Split(string(tsv), "\t")
- pattern := split[0]
- found := -1
- for i, name := range cmd.cgnames {
- if strings.Contains(name, pattern) {
- if found >= 0 {
- log.Warnf("pattern %q in %s already matched sample ID %q -- not using %q", pattern, infile, cmd.cgnames[found], name)
- } else {
- found = i
- cmd.trainingSet[found] = 1
- }
- }
- }
- if found < 0 {
- log.Warnf("pattern %q in %s does not match any genome IDs", pattern, infile)
- continue
- }
- }
- }
- tsi := 0
- for i, x := range cmd.trainingSet {
- if x == 1 {
- cmd.trainingSet[i] = tsi
- tsi++
- }
- }
- cmd.trainingSetSize = tsi + 1
- return nil
+type sampleInfo struct {
+ id string
+ isCase bool
+ isControl bool
+ isTraining bool
+ isValidation bool
+ pcaComponents []float64
}
-// Read case/control files, remove non-case/control entries from
-// cmd.cgnames, and build cmd.chi2Cases.
-func (cmd *sliceNumpy) useCaseControlFiles() error {
- if cmd.chi2CaseControlFile == "" {
- return nil
- }
- infiles, err := allFiles(cmd.chi2CaseControlFile, nil)
+// Read samples.csv file with case/control and training/validation
+// flags.
+func (cmd *sliceNumpy) loadSampleInfo(samplesFilename string) ([]sampleInfo, error) {
+ var si []sampleInfo
+ f, err := open(samplesFilename)
if err != nil {
- return err
+ return nil, err
}
- // index in cmd.cgnames => case(true) / control(false)
- cc := map[int]bool{}
- for _, infile := range infiles {
- f, err := open(infile)
- if err != nil {
- return 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++
+ 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)
}
- buf, err := io.ReadAll(f)
- f.Close()
- if err != nil {
- return err
+ if split[0] == "Index" && split[1] == "SampleID" && split[2] == "CaseControl" && split[3] == "TrainingValidation" {
+ continue
}
- ccCol := -1
- for _, tsv := range bytes.Split(buf, []byte{'\n'}) {
- if len(tsv) == 0 {
- continue
- }
- split := strings.Split(string(tsv), "\t")
- if ccCol < 0 {
- // header row
- for col, name := range split {
- if name == cmd.chi2CaseControlColumn {
- ccCol = col
- break
- }
- }
- if ccCol < 0 {
- return fmt.Errorf("%s: no column named %q in header row %q", infile, cmd.chi2CaseControlColumn, tsv)
- }
- continue
- }
- if len(split) <= ccCol {
- continue
- }
- pattern := split[0]
- found := -1
- for i, name := range cmd.cgnames {
- if strings.Contains(name, pattern) {
- if found >= 0 {
- log.Warnf("pattern %q in %s matches multiple genome IDs (%q, %q)", pattern, infile, cmd.cgnames[found], name)
- }
- found = i
- if split[ccCol] == "0" {
- cc[found] = false
- }
- if split[ccCol] == "1" {
- cc[found] = true
- }
- }
- }
- if found < 0 {
- log.Warnf("pattern %q in %s does not match any genome IDs", pattern, infile)
- 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)
}
- }
- allnames := cmd.cgnames
- cmd.cgnames = nil
- cmd.chi2Cases = nil
- ncases := 0
- for i, name := range allnames {
- if cc, ok := cc[i]; ok {
- cmd.cgnames = append(cmd.cgnames, name)
- cmd.chi2Cases = append(cmd.chi2Cases, cc)
- if cc {
- ncases++
- }
+ if idx != len(si) {
+ return nil, fmt.Errorf("%s line %d: index %d out of order", samplesFilename, lineNum, idx)
}
+ si = append(si, sampleInfo{
+ id: split[1],
+ isCase: split[2] == "1",
+ isControl: split[2] == "0",
+ isTraining: split[3] == "1",
+ isValidation: split[3] == "0",
+ })
}
- log.Printf("%d cases, %d controls, %d neither (dropped)", ncases, len(cmd.cgnames)-ncases, len(allnames)-len(cmd.cgnames))
- return nil
+ return si, nil
}
func (cmd *sliceNumpy) filterHGVScolpair(colpair [2][]int8) bool {