888e7470c14eeecdca310ed36bb45c3c00ae8052
lrnassar
  Tue Apr 21 15:14:04 2026 -0700
QA fixes for MPRA superTrack. refs #37359

Fix broken mpraVarDb bigDataUrl — pointed at /gbdb/hg38/mpra/mpravardb.bb
but the file is at /gbdb/hg38/mpra/mpravardb/mpravardb.bb, causing
hgTrackDb -strict to silently drop the subtrack.

Rebuild mpravardb.bb after two fixes in mpravardbToBed.py: sanitize UTF-8
in user-visible string fields (curly quotes, primes, NBSP mojibake) that
the browser does not transcode, eliminating ~246k non-ASCII occurrences
across 42% of rows; and change safe_float / pval_to_score to write NaN
and return score 0 for NA / out-of-range p-values instead of 0.0 and
score 1000 (previously inflated untested variants to the top of
score-sorted views).

trackDb stanza cleanup: shorten mpraVarDb longLabel, drop superfluous
type bed 4 from superTrack, make bigBed 9+13 explicit, remove redundant
mouseOverField, align parent mpra on, add filterValues for
cell_line/assay/cellLine and filterByRange sliders for percentile_rank /
fdr / log2FC, add labelFields and maxWindowToDraw.

Description pages: add cross-species disclosure (mouse reporter cells
used to assay human sequences), update mpraVarDb header to post-liftOver
count 239,028 with Studies-table footnote, fix mpraVarDb.html
download-server paths, soften imprecise "51 MPRA experiments" claim in
mpra.html and mprabase.html.

relatedTracks.ra: reciprocal mpra <-> wgEncodeReg4 and mpra <-> cCREs.

Expand mpra.txt makedoc with upstream provenance and QA-rebuild log.

diff --git src/hg/makeDb/scripts/mpravardb/mpravardbToBed.py src/hg/makeDb/scripts/mpravardb/mpravardbToBed.py
index a7b13d1317b..c97884640b5 100644
--- src/hg/makeDb/scripts/mpravardb/mpravardbToBed.py
+++ src/hg/makeDb/scripts/mpravardb/mpravardbToBed.py
@@ -1,173 +1,218 @@
 #!/usr/bin/env python3
 """
 Convert mpravardb.csv to BED9+ format, liftOver hg19 to hg38,
 merge, and create bigBed.
 
 Usage:
     cd /hive/data/genomes/hg38/bed/mpra/mpravardb
     python3 ~/kent/src/hg/makeDb/scripts/mpravardb/mpravardbToBed.py
 """
 
 import csv
+import re
 import subprocess
 import sys
 import os
 import math
 
 SCRIPT_DIR = os.path.join(os.environ["HOME"], "kent/src/hg/makeDb/scripts/mpravardb")
 AS_FILE = os.path.join(SCRIPT_DIR, "mpravardb.as")
 LIFTOVER_CHAIN = "/gbdb/hg19/liftOver/hg19ToHg38.over.chain.gz"
 CHROM_SIZES = "/hive/data/genomes/hg38/chrom.sizes"
 INPUT_CSV = "mpravardb.csv"
 
+# Upstream CSV contains UTF-8 curly quotes, primes, and NBSP mojibake.
+# Browser does not transcode UTF-8 in bigBed fields, so everything user-visible
+# must be plain ASCII. Transliterate or strip.
+_SANITIZE_MAP = {
+    "’": "'",  # RIGHT SINGLE QUOTATION MARK (used as apostrophe)
+    "‘": "'",  # LEFT SINGLE QUOTATION MARK
+    "“": '"',  # LEFT DOUBLE QUOTATION MARK
+    "”": '"',  # RIGHT DOUBLE QUOTATION MARK
+    "′": "'",  # PRIME (used after numerals: 3'UTR)
+    "″": '"',  # DOUBLE PRIME
+    "–": "-",  # EN DASH
+    "—": "-",  # EM DASH
+    "…": "...", # HORIZONTAL ELLIPSIS
+    " ": " ",  # NO-BREAK SPACE
+    "¬": "",   # NOT SIGN  (NBSP mojibake pair)
+    "†": "",   # DAGGER    (NBSP mojibake pair)
+}
+_SANITIZE_RE = re.compile("|".join(re.escape(k) for k in _SANITIZE_MAP))
+
+def sanitize_text(s):
+    """Return ASCII-only version of s for bigBed string fields."""
+    if s is None:
+        return ""
+    out = _SANITIZE_RE.sub(lambda m: _SANITIZE_MAP[m.group()], s)
+    # Drop any remaining non-ASCII (rare), then collapse runs of whitespace
+    out = out.encode("ascii", "ignore").decode("ascii")
+    out = re.sub(r"\s+", " ", out).strip()
+    return out
+
 def pval_to_score(pval):
-    """Convert p-value to a 0-1000 score using -log10."""
-    if pval is None or pval == "":
+    """Convert p-value to a 0-1000 score using -log10.
+    Missing / out-of-range / non-numeric → 0 (not 1000).
+    Many rows upstream encode NA as literal 0.0, which is indistinguishable from
+    a true p=0; treat all non-positive inputs as unscored."""
+    if pval is None or pval in ("", "NA"):
         return 0
     try:
         p = float(pval)
     except ValueError:
         return 0
-    if p <= 0:
-        return 1000
+    if p <= 0 or p > 1:
+        return 0
     score = int(-math.log10(p) * 100)
     return max(0, min(1000, score))
 
 def pval_to_color(pval, fdr):
-    """Color by significance: red if FDR<0.05, orange if p<0.05, black otherwise."""
+    """Color by significance: red if FDR<0.05, orange if p<0.05, grey otherwise."""
     try:
         fdr_val = float(fdr) if fdr not in (None, "", "NA") else 1.0
     except ValueError:
         fdr_val = 1.0
     try:
         p_val = float(pval) if pval not in (None, "", "NA") else 1.0
     except ValueError:
         p_val = 1.0
 
     if fdr_val < 0.05:
         return "200,0,0"     # dark red - FDR significant
     elif p_val < 0.05:
         return "255,165,0"   # orange - nominally significant
     else:
         return "190,190,190" # grey - not significant
 
 def safe_float(val):
-    """Convert to float, return 0.0 for NA or empty."""
+    """Convert to float, return NaN for NA / empty / non-numeric.
+    Using NaN (rather than 0.0) keeps untested variants out of filterByRange
+    sliders by default and avoids masquerading as p=0 / fdr=0 in the details
+    page.  bedToBigBed accepts the literal string "nan" in float fields."""
     if val in (None, "", "NA"):
-        return 0.0
+        return math.nan
     try:
         return float(val)
     except ValueError:
-        return 0.0
+        return math.nan
 
 def csv_to_bed(input_csv, hg19_bed, hg38_bed):
     """Parse CSV and write two BED files, one per assembly."""
     hg19_count = 0
     hg38_count = 0
     with open(input_csv, newline="") as fin, \
          open(hg19_bed, "w") as f19, \
          open(hg38_bed, "w") as f38:
         reader = csv.reader(fin)
         header = next(reader)
         for row in reader:
             chrom_num, pos, ref, alt, genome = row[0], row[1], row[2], row[3], row[4]
             rsid, disease, cellline = row[5], row[6], row[7]
             desc, log2fc, pvalue, fdr, study = row[8], row[9], row[10], row[11], row[12]
 
+            # Sanitize user-visible string fields (ASCII only, drop NBSP mojibake)
+            rsid = sanitize_text(rsid)
+            disease = sanitize_text(disease)
+            cellline = sanitize_text(cellline)
+            desc = sanitize_text(desc)
+            study = sanitize_text(study)
+            ref = sanitize_text(ref)
+            alt = sanitize_text(alt)
+
             chrom = "chr" + chrom_num
             try:
                 start = int(pos) - 1  # CSV uses 1-based coordinates
             except ValueError:
                 continue
             end = start + max(1, len(ref))  # span the reference allele
 
             # Build name
             if rsid and rsid != "NA":
                 name = rsid
             else:
                 name = f"{chrom}:{pos}:{ref}>{alt}"
 
             score = pval_to_score(pvalue)
             color = pval_to_color(pvalue, fdr)
 
             # Truncate long string fields to stay within bigBed limits
             if len(desc) > 250:
                 desc = desc[:247] + "..."
             if len(study) > 250:
                 study = study[:247] + "..."
 
             # Short values for mouseOver (3 significant digits)
             log2fc_val = safe_float(log2fc)
             pvalue_val = safe_float(pvalue)
             fdr_val = safe_float(fdr)
             mo_log2fc = f"{log2fc_val:.3g}"
             mo_pvalue = f"{pvalue_val:.3g}"
             mo_fdr = f"{fdr_val:.3g}"
 
             fields = [
                 chrom, str(start), str(end), name, str(score), ".",
                 str(start), str(end), color,
                 ref, alt,
                 rsid if rsid and rsid != "NA" else ".",
                 disease, cellline, desc,
                 str(log2fc_val),
                 str(pvalue_val),
                 str(fdr_val),
                 study,
                 mo_log2fc, mo_pvalue, mo_fdr,
             ]
             line = "\t".join(fields) + "\n"
 
             if genome == "hg19":
                 f19.write(line)
                 hg19_count += 1
             elif genome == "hg38":
                 f38.write(line)
                 hg38_count += 1
 
     print(f"Wrote {hg19_count} hg19 rows to {hg19_bed}")
     print(f"Wrote {hg38_count} hg38 rows to {hg38_bed}")
 
 def run(cmd):
     """Run a shell command, exit on failure."""
     print(f"  Running: {cmd}")
     result = subprocess.run(cmd, shell=True)
     if result.returncode != 0:
         print(f"ERROR: command failed with exit code {result.returncode}", file=sys.stderr)
         sys.exit(1)
 
 def main():
     hg19_bed = "mpravardb.hg19.bed"
     hg38_bed = "mpravardb.hg38.bed"
     lifted_bed = "mpravardb.hg19lifted.bed"
     unmapped_bed = "mpravardb.unmapped.bed"
     merged_bed = "mpravardb.bed"
     output_bb = "mpravardb.bb"
 
     print("Step 1: Converting CSV to BED format...")
     csv_to_bed(INPUT_CSV, hg19_bed, hg38_bed)
 
     print("\nStep 2: Lifting hg19 coordinates to hg38...")
     run(f"liftOver -bedPlus=9 -tab {hg19_bed} {LIFTOVER_CHAIN} {lifted_bed} {unmapped_bed}")
 
     # Count unmapped
     unmapped = sum(1 for line in open(unmapped_bed) if not line.startswith("#"))
     lifted = sum(1 for _ in open(lifted_bed))
     print(f"  Lifted: {lifted}, Unmapped: {unmapped}")
 
     print("\nStep 3: Merging hg38 native + lifted hg19...")
     run(f"cat {hg38_bed} {lifted_bed} > {merged_bed}.tmp")
     run(f"bedSort {merged_bed}.tmp {merged_bed}")
     os.remove(f"{merged_bed}.tmp")
 
     total = sum(1 for _ in open(merged_bed))
     print(f"  Total merged rows: {total}")
 
     print("\nStep 4: Converting to bigBed...")
     run(f"bedToBigBed -type=bed9+ -tab -as={AS_FILE} {merged_bed} {CHROM_SIZES} {output_bb}")
 
     print(f"\nDone. Output: {output_bb}")
     print(f"File size: {os.path.getsize(output_bb) / 1024 / 1024:.1f} MB")
 
 if __name__ == "__main__":
     main()