bac95a147f49cd331052e597006e04b3deee40fc
max
  Wed Apr 22 10:43:20 2026 -0700
lrSv/srSv: human-readable SV type filter labels, script cleanups

Add human-readable labels to the supertrack-level svType filter on
both the lrSv and srSv supertracks using the "CODE|CODE (Long name)"
filterValues syntax: DEL -> "DEL (Deletion)", INS -> "INS (Insertion)",
etc. Labels keep the short code up front so users can match what
hgTracks shows next to each feature.

Also sweep in the in-progress converter/as-file cleanups under
scripts/lrSv/ and scripts/srSv/ (introduction of lrSvCommon.py
helpers, consistent insLen / svLen / AC column naming, tightened
field-description text) that had been piling up as an unstaged
working tree.

refs #36258

diff --git src/hg/makeDb/scripts/lrSv/lrSvAou1kCsvToBed.py src/hg/makeDb/scripts/lrSv/lrSvAou1kCsvToBed.py
index 85dbd766430..550f491c33e 100644
--- src/hg/makeDb/scripts/lrSv/lrSvAou1kCsvToBed.py
+++ src/hg/makeDb/scripts/lrSv/lrSvAou1kCsvToBed.py
@@ -3,72 +3,89 @@
 
 Input is a gzipped CSV (media-2.gz) with columns:
   SV_coordinate, SV_ID, SV type, SV length, Mean GenotypePosterior nonref,
   AF(AFR,AMR,EAS,EUR,SAS), Fst(AFR vs Non-AFR), OMIM genes, Disease genes,
   Cancer genes, ACMG genes, OMIM CDS, Disease CDS, Cancer CDS, ACMG CDS,
   Regulatory element, SegDUP, Tandem repeats, Other LR datasets,
   Detected in AoU SR, eQTLs, GWAS, SV-trait associations,
   SR validation, LR assembly-supported, Locityper validation
 
 Usage:
     lrSvAou1kCsvToBed.py input.csv.gz output.bed
 """
 
 import csv
 import gzip
+import os
 import sys
 
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+from lrSvCommon import svName, normalizeSvType
+
+# AoU Phase-I (2025) SV panel: 1,027 samples => 2,054 alleles (diploid)
+# No per-variant AC in the site-level release; approximate AC as
+# round(max_popAF * N_alleles) for naming purposes only.
+AOU_N_ALLELES = 2054
+
 SV_COLORS = {
     "DEL": "200,0,0",
     "INS": "0,0,200",
 }
 
 def na(val):
     """Return empty string for NA values."""
     if val == "NA" or val == "No" or val == "":
         return ""
     return val
 
 def main():
     if len(sys.argv) != 3:
         print(__doc__, file=sys.stderr)
         sys.exit(1)
 
     inFile, outFile = sys.argv[1], sys.argv[2]
 
     with gzip.open(inFile, "rt") as fIn, open(outFile, "w") as fOut:
         reader = csv.reader(fIn)
         header = next(reader)
 
         for row in reader:
             coord = row[0]       # chr1:10627
-            svType = row[2]
-            svLen = int(row[3])
+            svTypeRaw = row[2]
+            svType = normalizeSvType(svTypeRaw)
+            svLenSrc = int(row[3])
 
             # Parse coordinate (1-based position)
             chrom, posStr = coord.split(":")
             pos = int(posStr)
 
             # BED is 0-based half-open
             chromStart = pos - 1
             if svType == "DEL":
-                chromEnd = chromStart + svLen
+                chromEnd = chromStart + svLenSrc
             else:
                 # INS: place at insertion site, 1 bp wide
                 chromEnd = chromStart + 1
 
-            name = f"{svType} {svLen}bp"
+            svLen = chromEnd - chromStart
+            # insLen: the source "SV length" represents the INS payload for INS
+            # and 0 for DEL (where it equals reference span)
+            if svType in ("INS", "MEI"):
+                insLen = svLenSrc
+            else:
+                insLen = 0
+
             color = SV_COLORS.get(svType, "100,100,100")
 
             # Parse population AFs (column 5): "0.001,0.002,0.003,0.004,0.005"
             afStr = row[5]
             afParts = afStr.split(",")
             try:
                 afAfr = float(afParts[0])
                 afAmr = float(afParts[1])
                 afEas = float(afParts[2])
                 afEur = float(afParts[3])
                 afSas = float(afParts[4])
             except (ValueError, IndexError):
                 afAfr = afAmr = afEas = afEur = afSas = 0.0
 
             fst = na(row[6])
@@ -81,42 +98,51 @@
 
             regElement = na(row[15])
             segDup = na(row[16])
             tandemRepeat = na(row[17])
             otherLr = na(row[18])
             detectedSr = na(row[19])
 
             eqtls = na(row[20])
             gwas = na(row[21])
             traitAssoc = na(row[22])
 
             # Use max population AF as score (0-1000)
             maxAf = max(afAfr, afAmr, afEas, afEur, afSas)
             score = min(int(round(maxAf * 1000)), 1000)
 
+            # AC: AoU site-level data doesn't publish AC; approximate with
+            # round(maxAf * 2054) so the name has something informative.
+            ac = int(round(maxAf * AOU_N_ALLELES))
+
+            featLen = insLen if svType in ("INS", "MEI") else svLen
+            name = svName(svType, featLen, ac)
+
             bedRow = [
                 chrom,
                 str(chromStart),
                 str(chromEnd),
                 name,
                 str(score),
                 ".",
                 str(chromStart),
                 str(chromEnd),
                 color,
                 svType,
                 str(svLen),
+                str(insLen),
+                str(ac),
                 f"{afAfr:.6f}",
                 f"{afAmr:.6f}",
                 f"{afEas:.6f}",
                 f"{afEur:.6f}",
                 f"{afSas:.6f}",
                 fst,
                 omimGenes,
                 diseaseGenes,
                 cancerGenes,
                 acmgGenes,
                 regElement,
                 segDup,
                 tandemRepeat,
                 otherLr,
                 detectedSr,