Fix wrong array index in PCA mode.

[lightning.git] / slicenumpy.go

diff --git a/slicenumpy.go b/slicenumpy.go
index 94bbb978496cf634011b0529cad0cf5f04adb913..b557b9475cd4a540b2e01ba14aeeee9047c1fb80 100644 (file)
--- a/slicenumpy.go
+++ b/slicenumpy.go
@@ -45,6 +45,7 @@ type sliceNumpy struct {
        chi2Cases          []bool
        chi2PValue         float64
        pvalueMinFrequency float64
+       maxFrequency       float64
        pcaComponents      int
        minCoverage        int
        includeVariant1    bool
@@ -96,6 +97,7 @@ func (cmd *sliceNumpy) run(prog string, args []string, stdin io.Reader, stdout,
        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)
@@ -154,6 +156,7 @@ func (cmd *sliceNumpy) run(prog string, args []string, stdin io.Reader, stdout,
                        "-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),
                }
@@ -1265,7 +1268,7 @@ func (cmd *sliceNumpy) run(prog string, args []string, stdin io.Reader, stdout,
                        for i := range cmd.samples {
                                cmd.samples[i].pcaComponents = make([]float64, outcols)
                                for c := 0; c < outcols; c++ {
-                                       cmd.samples[i].pcaComponents[i] = pca.At(i, c)
+                                       cmd.samples[i].pcaComponents[c] = pca.At(i, c)
                                }
                        }
                        log.Print("done")
@@ -1564,6 +1567,7 @@ type onehotXref struct {
        variant tileVariantID
        hom     bool
        pvalue  float64
+       maf     float64
 }
 
 const onehotXrefSize = unsafe.Sizeof(onehotXref{})
@@ -1635,6 +1639,7 @@ func (cmd *sliceNumpy) tv2homhet(cgs map[string]CompactGenome, maxv tileVariantI
        }
        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
@@ -1642,11 +1647,20 @@ func (cmd *sliceNumpy) tv2homhet(cgs map[string]CompactGenome, maxv tileVariantI
                if col < 4 && !cmd.includeVariant1 {
                        continue
                }
-               if col&1 == 0 && cmd.pvalueMinFrequency < 1 && homhet2maf(obs[col:col+2]) < cmd.pvalueMinFrequency {
-                       // Skip both columns (hom and het) if allele
-                       // frequency is below threshold
-                       col++
-                       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])
@@ -1659,6 +1673,7 @@ func (cmd *sliceNumpy) tv2homhet(cgs map[string]CompactGenome, maxv tileVariantI
                        variant: tileVariantID(col >> 1),
                        hom:     col&1 == 0,
                        pvalue:  p,
+                       maf:     maf,
                })
        }
        return onehot, xref
@@ -1689,7 +1704,7 @@ func homhet2maf(onehot [][]bool) float64 {
 // P-value row contains 1000000x actual p-value.
 func onehotXref2int32(xrefs []onehotXref) []int32 {
        xcols := len(xrefs)
-       xdata := make([]int32, 5*xcols)
+       xdata := make([]int32, 6*xcols)
        for i, xref := range xrefs {
                xdata[i] = int32(xref.tag)
                xdata[xcols+i] = int32(xref.variant)
@@ -1698,6 +1713,7 @@ func onehotXref2int32(xrefs []onehotXref) []int32 {
                }
                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
 }