diff --git a/ebv_lytic_expression/curate_cascade_annotations.py b/ebv_lytic_expression/curate_cascade_annotations.py
new file mode 100644
index 0000000..95f9f74
--- /dev/null
+++ b/ebv_lytic_expression/curate_cascade_annotations.py
@@ -0,0 +1,333 @@
+#!/usr/bin/env python3
+"""Curate Djavadian 2018 CAGE classes + Ersing 2017 EBV protein TMT for the viewer.
+
+Sources (do not redistribute the 7 MB Ersing workbook):
+ Djavadian, Hayes, Johannsen. PLOS Pathog. 2018;14:e1007114. Table 2.
+ Ersing et al. Cell Rep. 2017;19:1479–1493. Table S1 (gp350+ WCL TMT).
+"""
+from __future__ import annotations
+
+import csv
+import json
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parent
+ERSING_XLSX = Path("/tmp/ebv-supp/epmc/mmc2.xlsx")
+
+# Djavadian et al. 2018 Table 2 (CAGE-seq TSS).
+DJAV = [
+ (1709, 1729, "+", "late", 0.00, 0.01, 25, "BNRF1", "major tegument protein"),
+ (11330, 11349, "+", "latent", 1.02, 0.81, 184, "Cp", "latency promoter"),
+ (53782, 53794, "+", "early", 0.81, 1.25, 758, "BHRF1", "v-Bcl2"),
+ (58113, 58119, "+", "late", 0.00, 0.00, 22, "BFRF0.5", "terminase subunit"),
+ (58581, 58593, "+", "early", 0.98, 1.18, 151, "BFRF0.5?", "terminase subunit"),
+ (58860, 58867, "+", "late", 0.01, 0.00, 104, "BFRF1", "capsid nuclear egress"),
+ (61372, 61381, "+", "late", 0.02, 0.00, 346, "BFRF3", "capsid hexon tip"),
+ (62231, 62239, "+", "early", 1.18, 0.88, 78, "Fp", ""),
+ (75047, 75054, "+", "leaky", 0.19, 0.05, 72, "BORF1", "capsid 1x triplex"),
+ (76198, 76213, "+", "early", 1.05, 1.30, 161, "BORF2", "RNR large subunit"),
+ (78831, 78840, "+", "early", 0.93, 1.26, 279, "BaRF1", "RNR small subunit"),
+ (79869, 79874, "+", "early", 1.29, 1.31, 171, "BMRF1", "DNA polymerase processivity"),
+ (80811, 80863, "+", "early", 0.64, 0.84, 158, "BMRF2", "virion glycoprotein"),
+ (86914, 86917, "+", "early", 0.57, 0.24, 30, "BSRF1", "virion protein"),
+ (88540, 88546, "+", "leaky", 0.36, 0.27, 66, "BLRF1", "glycoprotein N"),
+ (88894, 88898, "+", "leaky", 0.10, 0.04, 366, "BLRF2", "tegument protein"),
+ (105040, 105049, "+", "early", 0.98, 1.07, 200, "BRRF1", "Na"),
+ (106271, 106278, "+", "leaky", 0.28, 0.34, 42, "BRRF2", "tegument protein"),
+ (109934, 109941, "+", "leaky", 0.35, 0.57, 22, "BKRF2", "glycoprotein L"),
+ (110175, 110180, "+", "early", 1.24, 1.04, 300, "BKRF3", "uracil DNA glycosylase"),
+ (110924, 110929, "+", "early", 0.95, 1.18, 167, "BKRF4", "tegument protein"),
+ (113906, 113915, "+", "leaky", 0.24, 0.14, 11, "BBRF1", "portal"),
+ (115794, 115797, "+", "leaky", 0.47, 0.40, 6, "BBRF2", ""),
+ (119129, 119134, "+", "leaky", 0.23, 0.29, 93, "BBRF3", "glycoprotein M"),
+ (137247, 137251, "+", "leaky", 0.23, 2.20, 12, "BcRF1", "vTBP; vPIC component"),
+ (144610, 144618, "+", "late", 0.01, 0.00, 5, "BXRF1", ""),
+ (145333, 145340, "+", "early", 0.98, 0.63, 9, "BVRF1", "portal cork"),
+ (147752, 147758, "+", "late", 0.02, 0.01, 16, "BVRF2", "scaffold protease"),
+ (148650, 148655, "+", "leaky", 0.27, 0.26, 52, "BdRF1", "capsid scaffold"),
+ (165497, 165499, "+", "early", 1.29, 1.06, 186, "BARF1", "CSF-1 decoy receptor"),
+ (167605, 167603, "-", "early", 0.64, 2.41, 6, "BNLF2a", "TAP inhibitor"),
+ (167499, 167485, "-", "early", 0.66, 0.21, 198, "BNLF2a/b", "TAP inhibitor/unknown"),
+ (165414, 165410, "-", "early", 1.94, 0.87, 127, "BALF1", "putative vBcl-2"),
+ (164786, 164778, "-", "early", 1.61, 0.86, 44, "BALF2", "ssDNA binding protein"),
+ (161637, 161632, "-", "leaky", 0.46, 0.98, 9, "BALF3", "terminase subunit"),
+ (159340, 159332, "-", "leaky", 0.34, 0.14, 50, "BALF4", "glycoprotein B"),
+ (150544, 150530, "-", "late", 0.00, 0.00, 197, "BILF2", "vGPCR"),
+ (148156, 148151, "-", "early", 1.08, 1.41, 16, "BVLF1", "vPIC component"),
+ (145119, 145100, "-", "early", 0.90, 1.36, 196, "BXLF1", "thymidine kinase"),
+ (143282, 143257, "-", "leaky", 0.13, 0.11, 20, "BXLF2", "glycoprotein H"),
+ (137683, 137669, "-", "late", 0.00, 0.02, 70, "BcLF1", "major capsid protein"),
+ (133323, 133316, "-", "late", 0.00, 0.00, 55, "BDLF1", "capsid 2x triplex"),
+ (132448, 132441, "-", "late", 0.01, 0.33, 80, "BDLF2", "virion glycoprotein"),
+ (131078, 131070, "-", "leaky", 0.15, 0.27, 89, "BDLF3", "gp150"),
+ (129350, 129343, "-", "early", 1.29, 1.02, 38, "BDLF3.5", "vPIC component"),
+ (128404, 128398, "-", "late", 0.04, 0.05, 3, "BGLF1", ""),
+ (126902, 126893, "-", "late", 0.03, 0.01, 59, "BGLF2", "virion protein"),
+ (125140, 125083, "-", "early", 0.72, 1.00, 19, "BGLF3", "vPIC component"),
+ (124087, 124083, "-", "early", 0.73, 0.66, 34, "BGLF3.5", "vPIC component"),
+ (123871, 123809, "-", "early", 1.21, 1.17, 94, "BGLF4", "protein kinase"),
+ (122429, 122417, "-", "early", 1.34, 1.10, 95, "BGLF5", "alkaline exonuclease"),
+ (121303, 121121, "-", "leaky", 0.50, 0.37, 111, "BBLF1", "myristoylated virion protein"),
+ (119044, 119040, "-", "early", 1.25, 1.08, 203, "BBLF2/3", "helicase-primase accessory"),
+ (114445, 114361, "-", "early", 1.05, 1.15, 74, "BBLF4", "helicase"),
+ (106186, 106182, "-", "early", 1.07, 1.96, 5, "BRLF1", "Rta"),
+ (102129, 102126, "-", "late", 0.02, 0.00, 210, "BZLF2", "gp42"),
+ (92163, 92158, "-", "late", 0.00, 0.01, 171, "BLLF1", "gp350"),
+ (90027, 90019, "-", "early", 1.11, 1.40, 133, "BLLF2", ""),
+ (88489, 88480, "-", "early", 1.07, 1.16, 229, "BLLF3", "dUTPase"),
+ (87030, 87023, "-", "early", 1.07, 1.16, 14, "BSLF1", "primase"),
+ (84330, 84323, "-", "early", 1.05, 1.08, 969, "SM", "lytic RNA export (BMLF1)"),
+ (75294, 75281, "-", "late", 0.01, 0.01, 6, "BOLF1", "tegument, binds BPLF1"),
+ (72163, 72156, "-", "late", 0.00, 0.01, 5, "BPLF1", "largest tegument protein"),
+ (58539, 58534, "-", "leaky", 0.19, 0.14, 6, "BFLF1", "packaging protein"),
+ (57130, 57048, "-", "early", 0.79, 0.41, 187, "BFLF2", "capsid nuclear egress"),
+ (52821, 52315, "-", "early", 0.51, 1.80, 65, "BHLF1", "OriLyt transcript"),
+]
+
+ORF_TO_YUAN = {
+ "SM": "BMLF1",
+ "BBLF2/3": "BBLF2",
+ "BNLF2a/b": "BNLF2b",
+}
+
+
+def linear_fold(signed: float) -> float:
+ return 1.0 / abs(signed) if signed < 0 else signed
+
+
+def mean_pos(vals):
+ xs = [float(v) for v in vals if v is not None and v != "" and float(v) > 0]
+ if not xs:
+ return None
+ return sum(xs) / len(xs)
+
+
+def load_yuan():
+ genes = []
+ seen = set()
+ rna48 = {}
+ with (ROOT / "data" / "yuan2006_table1_curated.csv").open() as f:
+ for row in csv.DictReader(f):
+ g = row["gene"]
+ hr = int(float(row["hours"]))
+ fold = linear_fold(float(row["signed_fold"]))
+ if hr == 48:
+ rna48[g] = fold
+ if g not in seen:
+ seen.add(g)
+ genes.append({"gene": g, "class": row["class"]})
+ return genes, rna48
+
+
+def cage_for_yuan(yuan_names: set[str]) -> dict:
+ best = {}
+ for start, end, strand, kin, b2, b4, tpm, orf, ann in DJAV:
+ gene = ORF_TO_YUAN.get(orf, orf)
+ if gene not in yuan_names:
+ continue
+ rec = {
+ "gene": gene,
+ "orf": orf,
+ "kinetics": kin,
+ "balf2_ratio": b2,
+ "bdlf4_ratio": b4,
+ "wt_tpm": tpm,
+ "annotation": ann,
+ "vpic_independent_late": bool(kin == "late" and b4 >= 0.2),
+ }
+ prev = best.get(gene)
+ if prev is None or tpm > prev["wt_tpm"]:
+ best[gene] = rec
+ return best
+
+
+def load_ersing(yuan_names: set[str]) -> dict:
+ import openpyxl
+
+ alias = {
+ "EBNA-LP": "EBNALP",
+ "BDRF1": "BdRF1",
+ "BdRF1": "BdRF1",
+ }
+ wb = openpyxl.load_workbook(ERSING_XLSX, read_only=True, data_only=True)
+ ws = wb["Data"]
+ proteins = {}
+ for i, row in enumerate(ws.iter_rows(values_only=True)):
+ if i == 0:
+ continue
+ vals = list(row)
+ sp = vals[2]
+ if not sp or str(sp).upper() == "HUMAN":
+ continue
+ gs = vals[12]
+ if not gs or str(gs).startswith("Frame"):
+ continue
+ gene = alias.get(gs, gs)
+ if gene not in yuan_names:
+ continue
+ pep = [vals[14], vals[15], vals[16], vals[19]]
+ pep_n = sum(1 for p in pep if p and p > 0)
+ rec = {
+ "gene": gene,
+ "source_id": gs,
+ "peptides_expts": pep_n,
+ "p3hr1_hours": [0, 24, 48, 72],
+ "p3hr1_signal": [
+ mean_pos([vals[22], vals[32], vals[33], vals[42]]),
+ mean_pos([vals[29], vals[39], vals[49]]),
+ mean_pos([vals[30], vals[40], vals[50]]),
+ mean_pos([vals[31], vals[41], vals[51]]),
+ ],
+ "akata_hours": [0, 48],
+ "akata_signal": [
+ mean_pos([vals[71], vals[72]]),
+ mean_pos([vals[75], vals[76]]),
+ ],
+ }
+ prev = proteins.get(gene)
+ if prev is None or pep_n > prev["peptides_expts"]:
+ proteins[gene] = rec
+ return proteins
+
+
+def fold(a, b):
+ if a is None or b is None or a <= 0 or b <= 0:
+ return None
+ return b / a
+
+
+def main():
+ yuan, rna48 = load_yuan()
+ names = {g["gene"] for g in yuan}
+ cage = cage_for_yuan(names)
+ prot = load_ersing(names)
+ # BGRF1/BDRF1 is one spliced terminase; Yuan lists both oligos.
+ if "BGRF1" in names and "BdRF1" in prot and "BGRF1" not in prot:
+ shared = dict(prot["BdRF1"])
+ shared["gene"] = "BGRF1"
+ shared["source_id"] = prot["BdRF1"]["source_id"] + " (same ORF as BdRF1)"
+ prot["BGRF1"] = shared
+
+ genes = []
+ for g in yuan:
+ name = g["gene"]
+ c = cage.get(name)
+ p = prot.get(name)
+ yuan_cls = g["class"]
+ cage_kin = c["kinetics"] if c else None
+ mismatch = False
+ if cage_kin:
+ # Compare Yuan array class vs CAGE DNA-replication class.
+ y = yuan_cls
+ if y in ("IE", "IE/E"):
+ y_bin = "early"
+ elif y == "E":
+ y_bin = "early"
+ elif y == "L":
+ y_bin = "late"
+ else:
+ y_bin = None
+ if y_bin and cage_kin in ("early", "leaky", "late"):
+ if y_bin == "early" and cage_kin == "late":
+ mismatch = True
+ if y_bin == "late" and cage_kin == "early":
+ mismatch = True
+ ak_fold = None
+ if p:
+ ak_fold = fold(p["akata_signal"][0], p["akata_signal"][1])
+ genes.append(
+ {
+ "gene": name,
+ "yuan_class": yuan_cls,
+ "cage": c,
+ "protein": p,
+ "array_vs_cage_mismatch": mismatch,
+ "rna_fold_48h": rna48.get(name),
+ "akata_protein_fold_48h": ak_fold,
+ }
+ )
+
+ out = {
+ "sources": [
+ {
+ "id": "yuan2006",
+ "cite": "Yuan et al. J Virol 2006;80:2548–2565",
+ "doi": "10.1128/JVI.80.5.2548-2565.2006",
+ "note": "Akata + anti-IgG cytoplasmic RNA fold vs 0 h (Table 1).",
+ },
+ {
+ "id": "djavadian2018",
+ "cite": "Djavadian, Hayes, Johannsen. PLOS Pathog 2018;14:e1007114",
+ "doi": "10.1371/journal.ppat.1007114",
+ "note": "HEK293 CAGE-seq TSS class by DNA replication (BALF2) and vPIC (BDLF4), 48 h after Rta+Zta. Not a time series.",
+ },
+ {
+ "id": "ersing2017",
+ "cite": "Ersing, Nobre, Gewurz, Weekes et al. Cell Rep 2017;19:1479–1493",
+ "doi": "10.1016/j.celrep.2017.04.062",
+ "note": "TMT of gp350+ cells. Akata: 0 vs 48 h anti-IgG (same trigger as Yuan). P3HR1-ZHT/RHT: 0/24/48/72 h. Not paired with Yuan RNA aliquots. Protein temporal classes complement IE/E/L RNA (Ersing; Weekes et al. Cell 2014 CMV).",
+ },
+ ],
+ "genes": genes,
+ }
+
+ js_path = ROOT / "web" / "cascade.data.js"
+ js_path.write_text(
+ "window.CASCADE = " + json.dumps(out, indent=2) + ";\n",
+ encoding="utf-8",
+ )
+
+ csv_path = ROOT / "data" / "cascade_annotations.csv"
+ with csv_path.open("w", newline="") as f:
+ w = csv.DictWriter(
+ f,
+ fieldnames=[
+ "gene",
+ "yuan_class",
+ "cage_kinetics",
+ "balf2_ratio",
+ "bdlf4_ratio",
+ "wt_tpm",
+ "array_vs_cage_mismatch",
+ "rna_fold_48h",
+ "akata_protein_fold_48h",
+ "p3hr1_0",
+ "p3hr1_24",
+ "p3hr1_48",
+ "p3hr1_72",
+ ],
+ )
+ w.writeheader()
+ for g in genes:
+ c = g["cage"] or {}
+ p = g["protein"] or {}
+ sig = p.get("p3hr1_signal") or [None, None, None, None]
+ w.writerow(
+ {
+ "gene": g["gene"],
+ "yuan_class": g["yuan_class"],
+ "cage_kinetics": c.get("kinetics"),
+ "balf2_ratio": c.get("balf2_ratio"),
+ "bdlf4_ratio": c.get("bdlf4_ratio"),
+ "wt_tpm": c.get("wt_tpm"),
+ "array_vs_cage_mismatch": g["array_vs_cage_mismatch"],
+ "rna_fold_48h": g["rna_fold_48h"],
+ "akata_protein_fold_48h": g["akata_protein_fold_48h"],
+ "p3hr1_0": sig[0],
+ "p3hr1_24": sig[1],
+ "p3hr1_48": sig[2],
+ "p3hr1_72": sig[3],
+ }
+ )
+
+ n_cage = sum(1 for g in genes if g["cage"])
+ n_prot = sum(1 for g in genes if g["protein"])
+ n_ak = sum(1 for g in genes if g["akata_protein_fold_48h"])
+ n_mm = sum(1 for g in genes if g["array_vs_cage_mismatch"])
+ print(f"wrote {js_path} and {csv_path}")
+ print(f"genes={len(genes)} cage={n_cage} protein={n_prot} akata_48h_fold={n_ak} mismatches={n_mm}")
+ print("mismatches:", [g["gene"] for g in genes if g["array_vs_cage_mismatch"]])
+
+
+if __name__ == "__main__":
+ main()
diff --git a/ebv_lytic_expression/data/cascade_annotations.csv b/ebv_lytic_expression/data/cascade_annotations.csv
new file mode 100644
index 0000000..efd627b
--- /dev/null
+++ b/ebv_lytic_expression/data/cascade_annotations.csv
@@ -0,0 +1,60 @@
+gene,yuan_class,cage_kinetics,balf2_ratio,bdlf4_ratio,wt_tpm,array_vs_cage_mismatch,rna_fold_48h,akata_protein_fold_48h,p3hr1_0,p3hr1_24,p3hr1_48,p3hr1_72
+BZLF1,IE,,,,,False,2.9,53.77618335003269,1721.4980103744163,8614.317606351688,7959.466777134119,7253.485789061975
+BRLF1,IE,early,1.07,1.96,5,False,2.7,6.313177953708339,3892.9515323079204,18710.429463627093,19458.343778807168,13275.583522788613
+BMLF1,IE/E,early,1.05,1.08,969,False,3.9,39.98047752498598,1118.043411533191,20711.139079680386,18466.417979360485,17548.891729126233
+BCRF2,U,,,,,False,4.0,,,,,
+EBNALP,LT,,,,,False,6.1,,197.39527534434723,125.1459175048711,128.26840782962338,131.4748143896989
+EBNA2,LT,,,,,False,5.4,,,,,
+BHLF1,E,early,0.51,1.8,65,False,8.4,,,,,
+BHRF1,E,early,0.81,1.25,758,False,5.2,17.421076581690865,187.40820431979338,971.9500718486142,1122.673898869493,880.8664880031293
+BFLF2,E,early,0.79,0.41,187,False,7.1,223.5330181289925,582.6229785251097,13068.728066602474,15110.961140950376,8238.065800037342
+BFLF1,E,leaky,0.19,0.14,6,False,2.9,25.277323947486487,682.9660528514127,16219.48509345272,13458.210173855177,10784.936179236305
+BFRF1,E,late,0.01,0.0,104,True,6.9,70.11586263717221,944.6491404856235,27821.2763042337,37656.18890638144,27294.063061921497
+BFRF2,E,,,,,False,5.5,19.295897604986095,89.74464346378407,1216.4376272078232,943.0104247847609,746.0802965438169
+BFRF3,L,late,0.02,0.0,346,False,5.1,33.79041765729878,267.0362089470794,6528.142529109496,7524.251546413748,3837.6467332476586
+BPLF1,L,late,0.0,0.01,5,False,5.0,29.474299188945345,900.2261601671016,26767.601751902752,25298.120278528804,14904.448466266074
+BNRF1,L,late,0.0,0.01,25,False,5.8,21.78896761610392,2118.173945119397,50543.07710223947,55012.832782847494,38059.186334098
+BOLF1,L,late,0.01,0.01,6,False,2.3,73.38444605896731,653.6831261468536,8771.241532542383,9193.860201766931,5755.137625336311
+BORF1,L,leaky,0.19,0.05,72,False,5.7,23.2184642750116,196.7258753186157,9137.580973773622,9055.619594918187,6090.562625906503
+BORF2,E,early,1.05,1.3,161,False,6.6,36.57366020103709,3409.086866823235,64706.79887901229,80510.51578554424,55444.094771368305
+BaRF1,E,early,0.93,1.26,279,False,5.5,37.61304557069818,1182.0168176776606,25905.108551986123,28473.996988222698,18598.288950549937
+BMRF1,E,early,1.29,1.31,171,False,6.3,39.243359262293744,3351.8745954638543,93934.42023041705,101166.29829710566,70999.77291070136
+BMRF2,L,early,0.64,0.84,158,True,5.2,17.60140757161568,60.80424435979389,3332.2007575659827,3135.385774862305,2096.290061564052
+BLLF3,E,early,1.07,1.16,229,False,6.8,29.4420983618548,1507.2840354413597,23611.975257225957,20415.51876290559,16366.506525300196
+BLRF1,L,leaky,0.36,0.27,66,False,5.0,,,,,
+BLRF2,L,leaky,0.1,0.04,366,False,4.0,53.27852826661343,823.4833849567792,21327.15585027052,25040.793807449372,13787.665191577524
+BLLF1,L,late,0.0,0.01,171,False,5.0,131.84156292405692,117.98232893787674,4655.958111286784,3517.2959713633086,1461.0196518834755
+BZLF2,L,late,0.02,0.0,210,False,4.1,123.99956356624558,125.88176642044414,8311.340377783066,6542.447313393052,4399.4503775069925
+BRRF1,E,early,0.98,1.07,200,False,4.2,47.61118259157017,454.05242734650886,10925.946459097082,10864.07478260522,8898.74689775177
+BRRF2,L,leaky,0.28,0.34,42,False,4.7,27.54467362297796,524.5180602266361,6970.15542282054,5975.352597770237,3249.1383536006288
+BKRF2,L,leaky,0.35,0.57,22,False,6.4,,,,,
+BKRF3,E,early,1.24,1.04,300,False,7.0,73.4986740682135,667.7150036591482,13987.342736216577,12275.623414045096,10838.878578501366
+BKRF4,L,early,0.95,1.18,167,True,4.5,85.22577243611214,595.3532192635923,10072.547800361312,4938.332966473789,3030.6506740081063
+BBLF4,E,early,1.05,1.15,74,False,3.8,13.639873905670125,469.5038404531729,9058.059942703729,7520.561492362565,5015.868806643393
+BBRF1,L,leaky,0.24,0.14,11,False,5.8,76.90521843830444,429.13448978495325,15970.267575423997,11325.524454051354,6882.567562874928
+BBRF2,L,leaky,0.47,0.4,6,False,4.4,57.98549093620431,399.03284191895983,13612.302464607079,11687.85652517985,8199.791607044548
+BBLF2,E,early,1.25,1.08,203,False,5.0,15.142177360430995,800.7080075823174,12442.079456506193,8373.948939705808,6821.052847250008
+BBRF3,L,leaky,0.23,0.29,93,False,6.0,,47.85762720099955,517.4173297939403,824.068376627544,437.1601982593972
+BGLF5,E,early,1.34,1.1,95,False,6.0,36.97235997274975,759.2330745268569,14638.814278089556,15108.998829302318,12835.925869413235
+BGLF3,U,early,0.72,1.0,19,False,4.7,,49.70861582999995,1626.1255743990907,628.5205345423451,636.1578077480598
+BGRF1,L,,,,,False,4.2,17.024583825765674,207.71137786029803,3159.3389411952194,2162.7374530031793,1630.5414112201327
+BGLF2,L,late,0.03,0.01,59,False,4.2,47.67006131766582,238.1181253213751,10801.134285954902,11074.278100373906,7080.017671715101
+BGLF1,L,late,0.04,0.05,3,False,3.8,24.17698666294981,52.84229557095584,4301.473548925015,2022.1355356983238,1939.5291788515572
+BDLF4,E,,,,,False,5.5,,16.321331943115784,715.338398389017,226.78510110250681,260.9470724115835
+BDLF3,L,leaky,0.15,0.27,89,False,5.8,89.89566317683527,47.719333969964595,1966.7808846964817,1818.7422386735027,1757.461136676734
+BDLF1,L,late,0.0,0.0,55,False,7.5,171.0000506817526,87.78379978662831,4334.384274453511,3676.6681177737814,3105.5652217825386
+BcLF1,L,late,0.0,0.02,70,False,4.0,29.081390755268142,2026.7260124753097,80634.9995375006,82155.32866078157,41668.28890225705
+BXLF2,L,leaky,0.13,0.11,20,False,5.3,83.9188341266691,358.53842306985894,14721.86001175418,10788.018601726244,7692.606578019396
+BXLF1,E,early,0.9,1.36,196,False,5.1,34.967660053732864,1807.9242369301737,40094.90695766085,44120.549777003886,32365.356543791717
+BVRF1,L,early,0.98,0.63,9,True,3.9,10.276919376629838,127.3291265241181,3796.1434433722693,3033.5885381830144,2289.696605503456
+BdRF1,L,leaky,0.27,0.26,52,False,5.8,17.024583825765674,207.71137786029803,3159.3389411952194,2162.7374530031793,1630.5414112201327
+BILF2,L,late,0.0,0.0,197,False,6.4,,,,,
+LF3,E,,,,,False,7.6,48.67936146090523,87.09784370343142,3759.093805409188,5685.734563638027,3236.9842632309033
+LF2,U,,,,,False,5.0,14.479787297055198,548.5048503096889,8218.232396820327,8850.700936072275,6644.194330454132
+BALF5,E,,,,,False,4.3,58.63121288045128,1900.630432058125,53786.612955552504,47468.7565461183,39820.1948397717
+BALF4,L,leaky,0.34,0.14,50,False,6.8,60.95159207763085,1206.6516800565844,31953.16326047129,33829.62016869923,19939.59503355081
+BALF2,E,early,1.61,0.86,44,False,4.9,38.85602351263216,5002.303911305815,133262.63508577223,141567.88820678883,84569.68154389622
+BALF1,E,early,1.94,0.87,127,False,4.4,7.721101812694095,51.39207835234844,717.7399015555088,372.79196640977,260.130519518773
+BARF1,E,early,1.29,1.06,186,False,3.8,,15.155135472177104,900.4465132908363,957.0717603505724,647.0451533741186
+BNLF2b,E,early,0.66,0.21,198,False,6.1,23.73116531699743,101.06518159887612,3926.070351062606,2030.1855468233043,1905.1361720609193
+BNLF2a,E,early,0.64,2.41,6,False,4.9,,,,,
diff --git a/ebv_lytic_expression/web/app.js b/ebv_lytic_expression/web/app.js
index 196758a..a3cc5a4 100644
--- a/ebv_lytic_expression/web/app.js
+++ b/ebv_lytic_expression/web/app.js
@@ -3,6 +3,7 @@
const HOURS = DATA.hours;
const GENES = DATA.genes;
const BY_NAME = Object.fromEntries(GENES.map((g) => [g.gene, g]));
+ const CASCADE = Object.fromEntries((window.CASCADE?.genes || []).map((g) => [g.gene, g]));
const CALIBRATORS = ["BZLF1", "BRLF1", "BMRF1", "BALF5", "BXLF1", "BLLF1", "BFRF3"];
const PALETTE = [
@@ -18,9 +19,94 @@
showGhosts: true,
showBand: true,
classFilter: "all",
+ cageFilter: "all",
search: "",
};
+ function cascadeOf(name) {
+ return CASCADE[name] || null;
+ }
+
+ function cageKin(name) {
+ return cascadeOf(name)?.cage?.kinetics || null;
+ }
+
+ function cageLabel(kin) {
+ if (kin === "early") return "CAGE E";
+ if (kin === "leaky") return "CAGE LL";
+ if (kin === "late") return "CAGE L";
+ if (kin === "latent") return "CAGE lat";
+ return "";
+ }
+
+ function cageColor(kin) {
+ if (kin === "early") return "#5eb0ff";
+ if (kin === "leaky") return "#f2d06b";
+ if (kin === "late") return "#7dce9a";
+ if (kin === "latent") return "#c9a0e8";
+ return "#6b7c8d";
+ }
+
+ function pearson(xs, ys) {
+ const n = xs.length;
+ if (n < 3) return null;
+ const mx = xs.reduce((a, b) => a + b, 0) / n;
+ const my = ys.reduce((a, b) => a + b, 0) / n;
+ let num = 0;
+ let dx = 0;
+ let dy = 0;
+ for (let i = 0; i < n; i++) {
+ const a = xs[i] - mx;
+ const b = ys[i] - my;
+ num += a * b;
+ dx += a * a;
+ dy += b * b;
+ }
+ const den = Math.sqrt(dx * dy);
+ return den ? num / den : null;
+ }
+
+ function heatFill(log2fold) {
+ const t = Math.max(0, Math.min(1, log2fold / 5));
+ const stops = [
+ [16, 22, 32],
+ [36, 74, 110],
+ [94, 176, 255],
+ [242, 208, 107],
+ ];
+ const x = t * (stops.length - 1);
+ const i = Math.min(stops.length - 2, Math.floor(x));
+ const f = x - i;
+ const a = stops[i];
+ const b = stops[i + 1];
+ const r = Math.round(a[0] + (b[0] - a[0]) * f);
+ const g = Math.round(a[1] + (b[1] - a[1]) * f);
+ const bl = Math.round(a[2] + (b[2] - a[2]) * f);
+ return `rgb(${r},${g},${bl})`;
+ }
+
+ function highlightOnChart(name) {
+ if (state.hovered === name) return;
+ state.hovered = name;
+ renderChartOnly();
+ document.querySelectorAll(".gene-row").forEach((row) => {
+ const n = row.querySelector(".name")?.textContent;
+ row.classList.toggle("hovered", state.hovered === n);
+ });
+ }
+
+ function proteinFolds(p, key) {
+ if (!p) return [];
+ const hours = p[key + "_hours"];
+ const sig = p[key + "_signal"];
+ if (!hours || !sig || !sig[0] || sig[0] <= 0) return [];
+ return hours.map((hr, i) => {
+ const v = sig[i];
+ if (v == null || v <= 0) return null;
+ return { hour: hr, fold: v / sig[0] };
+ }).filter(Boolean);
+ }
+
const $ = (sel) => document.querySelector(sel);
function linear(g) {
@@ -68,6 +154,7 @@
const q = state.search.trim().toLowerCase();
return GENES.filter((g) => {
if (state.classFilter !== "all" && g.class !== state.classFilter) return false;
+ if (state.cageFilter !== "all" && cageKin(g.gene) !== state.cageFilter) return false;
if (q && !g.gene.toLowerCase().includes(q)) return false;
return true;
});
@@ -84,6 +171,11 @@
render();
}
+ function pinCage(kin) {
+ GENES.filter((g) => cageKin(g.gene) === kin).forEach((g) => state.pinned.add(g.gene));
+ render();
+ }
+
function pinOnly(list) {
state.pinned = new Set(list.filter((g) => BY_NAME[g]));
render();
@@ -294,7 +386,8 @@
tip.style.display = "block";
tip.style.left = ev.clientX - rect.left + 14 + "px";
tip.style.top = ev.clientY - rect.top + 14 + "px";
- tip.innerHTML = `${g.gene} · ${g.class}
${hr} h → ${fold.toFixed(1)}× vs 0 h`;
+ const ckin = cageKin(hit.gene);
+ tip.innerHTML = `${g.gene} · ${g.class}${ckin ? " · CAGE " + ckin : ""}
${hr} h → ${fold.toFixed(1)}× RNA vs 0 h`;
} else {
tip.style.display = "none";
}
@@ -326,10 +419,12 @@
row.className = "gene-row";
if (state.pinned.has(g.gene)) row.classList.add("pinned");
if (state.hovered === g.gene) row.classList.add("hovered");
- row.innerHTML = `
+ const ckin = cageKin(g.gene);
+ const mm = cascadeOf(g.gene)?.array_vs_cage_mismatch;
+ row.innerHTML = `
${g.gene}
- `;
+ `;
row.onmouseenter = () => {
state.hovered = g.gene;
renderChartOnly();
@@ -356,6 +451,310 @@
else if (state.pinned.size === 1) showDetail([...state.pinned][0]);
}
+ function svgEl(name, attrs) {
+ const el = document.createElementNS("http://www.w3.org/2000/svg", name);
+ Object.entries(attrs).forEach(([k, v]) => el.setAttribute(k, v));
+ return el;
+ }
+
+ function drawTrack(svg, pts, x, yOf, color, dash, r) {
+ if (pts.length >= 2) {
+ const p = svgEl("path", {
+ d: pts.map((d, i) => `${i ? "L" : "M"}${x(d.hour).toFixed(1)},${yOf(d.fold).toFixed(1)}`).join(" "),
+ fill: "none",
+ stroke: color,
+ "stroke-width": "1.8",
+ "stroke-dasharray": dash || "",
+ });
+ svg.appendChild(p);
+ }
+ pts.forEach((d) => {
+ svg.appendChild(svgEl("circle", { cx: x(d.hour), cy: yOf(d.fold), r: r || 2.2, fill: color }));
+ });
+ }
+
+ function trackYScale(folds, y0, y1) {
+ const useLog = state.yMode === "log2";
+ const yv = (f) => (useLog ? Math.log2(Math.max(f, 1e-6)) : f);
+ let yMin = Math.min(...folds.map(yv));
+ let yMax = Math.max(...folds.map(yv));
+ const pad = (yMax - yMin) * 0.16 || 0.2;
+ yMin -= pad;
+ yMax += pad;
+ return (f) => y0 + ((yMax - yv(f)) / (yMax - yMin)) * (y1 - y0);
+ }
+
+ function drawAlignedSparklines(host, g) {
+ const cas = cascadeOf(g.gene);
+ const prot = cas?.protein;
+ const w = 268;
+ const h = 132;
+ const m = { t: 6, r: 8, b: 16, l: 28 };
+ const svg = svgEl("svg", { class: "mini tracks", viewBox: `0 0 ${w} ${h}` });
+ const x = (hr) => m.l + (hr / 72) * (w - m.l - m.r);
+ const rnaFolds = g.hours.map((hr, i) => ({ hour: hr, fold: g.linear_fold[i] }));
+ const ak = proteinFolds(prot, "akata");
+ const p3 = proteinFolds(prot, "p3hr1");
+ const split = 58;
+ const yRna = trackYScale(rnaFolds.map((d) => d.fold), m.t + 10, split - 4);
+ const protF = [...ak.map((d) => d.fold), ...p3.map((d) => d.fold)];
+ [0, 24, 48, 72].forEach((hr) => {
+ const t = svgEl("text", { x: x(hr), y: h - 3, "text-anchor": "middle", fill: "#8b9aab", "font-size": "9" });
+ t.textContent = hr + "h";
+ svg.appendChild(t);
+ });
+ const labR = svgEl("text", { x: 4, y: m.t + 8, fill: "#8b9aab", "font-size": "9" });
+ labR.textContent = "RNA";
+ svg.appendChild(labR);
+ const labP = svgEl("text", { x: 4, y: split + 12, fill: "#8b9aab", "font-size": "9" });
+ labP.textContent = "prot.";
+ svg.appendChild(labP);
+ const divider = svgEl("line", { x1: m.l, x2: w - m.r, y1: split, y2: split, stroke: "#2a3544" });
+ svg.appendChild(divider);
+ drawTrack(svg, rnaFolds, x, yRna, "#5eb0ff", "", 2.2);
+ if (protF.length) {
+ const yProt = trackYScale(protF, split + 10, h - m.b - 2);
+ if (p3.length) drawTrack(svg, p3, x, yProt, "#7dce9a", "3 2", 2.2);
+ if (ak.length) {
+ ak.forEach((d) => {
+ svg.appendChild(svgEl("circle", { cx: x(d.hour), cy: yProt(d.fold), r: 3.2, fill: "#f0a04b" }));
+ });
+ }
+ } else {
+ const miss = svgEl("text", { x: m.l + 8, y: split + 28, fill: "#6b7c8d", "font-size": "10" });
+ miss.textContent = "not quantified in Ersing WCL";
+ svg.appendChild(miss);
+ }
+ host.replaceChildren(svg);
+ }
+
+ function scatterPoints() {
+ return (window.CASCADE?.genes || []).filter((c) => c.rna_fold_48h && c.akata_protein_fold_48h);
+ }
+
+ function bindPlotHover(svg, status) {
+ svg.onmousemove = (ev) => {
+ const gene = ev.target && ev.target.dataset ? ev.target.dataset.gene : null;
+ if (status) status.textContent = gene ? gene : status.dataset.idle;
+ highlightOnChart(gene);
+ };
+ svg.onmouseleave = () => {
+ if (status) status.textContent = status.dataset.idle;
+ highlightOnChart(null);
+ };
+ svg.onclick = (ev) => {
+ const gene = ev.target && ev.target.dataset ? ev.target.dataset.gene : null;
+ if (gene) togglePin(gene);
+ };
+ }
+
+ function drawScatter(host, highlight) {
+ const pts = scatterPoints();
+ const wrap = document.createElement("div");
+ const w = 268;
+ const h = 210;
+ const m = { t: 14, r: 12, b: 30, l: 40 };
+ const svg = svgEl("svg", { class: "scatter", viewBox: `0 0 ${w} ${h}` });
+ const lx = (f) => Math.log2(Math.max(f, 1e-6));
+ const xs = pts.map((p) => lx(p.rna_fold_48h));
+ const ys = pts.map((p) => lx(p.akata_protein_fold_48h));
+ const r = pearson(xs, ys);
+ const xMin = Math.min(0, ...xs) - 0.4;
+ const xMax = Math.max(1, ...xs) + 0.4;
+ const yMin = Math.min(0, ...ys) - 0.4;
+ const yMax = Math.max(1, ...ys) + 0.4;
+ const X = (f) => m.l + ((lx(f) - xMin) / (xMax - xMin)) * (w - m.l - m.r);
+ const Y = (f) => m.t + ((yMax - lx(f)) / (yMax - yMin)) * (h - m.t - m.b);
+ const xlab = svgEl("text", { x: m.l + (w - m.l - m.r) / 2, y: h - 6, "text-anchor": "middle", fill: "#8b9aab", "font-size": "10" });
+ xlab.textContent = "RNA 48 h (log2 fold, Yuan)";
+ svg.appendChild(xlab);
+ const ylab = svgEl("text", {
+ x: 12,
+ y: m.t + (h - m.t - m.b) / 2,
+ "text-anchor": "middle",
+ fill: "#8b9aab",
+ "font-size": "10",
+ transform: `rotate(-90 12 ${m.t + (h - m.t - m.b) / 2})`,
+ });
+ ylab.textContent = "protein 48 h (log2 fold, Akata TMT)";
+ svg.appendChild(ylab);
+ svg.appendChild(svgEl("line", {
+ x1: X(2 ** xMin), y1: Y(2 ** xMin), x2: X(2 ** xMax), y2: Y(2 ** xMax),
+ stroke: "#334155", "stroke-dasharray": "3 3",
+ }));
+ const eq = svgEl("text", { x: X(2 ** (xMax - 0.15)), y: Y(2 ** (xMax - 0.15)) - 4, fill: "#6b7c8d", "font-size": "9" });
+ eq.textContent = "equal fold";
+ svg.appendChild(eq);
+ pts.forEach((p) => {
+ const kin = p.cage?.kinetics;
+ const on = p.gene === highlight || state.pinned.has(p.gene);
+ const c = svgEl("circle", {
+ cx: X(p.rna_fold_48h),
+ cy: Y(p.akata_protein_fold_48h),
+ r: p.gene === highlight ? 5.5 : on ? 4.2 : 3.3,
+ fill: cageColor(kin),
+ opacity: p.gene === highlight ? 1 : on ? 0.95 : 0.55,
+ stroke: state.pinned.has(p.gene) ? colorFor(p.gene) : "none",
+ "stroke-width": state.pinned.has(p.gene) ? 1.6 : 0,
+ "data-gene": p.gene,
+ });
+ const title = document.createElementNS("http://www.w3.org/2000/svg", "title");
+ title.textContent = `${p.gene}: RNA ${p.rna_fold_48h.toFixed(1)}× · protein ${p.akata_protein_fold_48h.toFixed(1)}×`;
+ c.appendChild(title);
+ svg.appendChild(c);
+ });
+ const status = document.createElement("div");
+ status.className = "plot-status";
+ status.dataset.idle = r == null ? `${pts.length} genes with both measures` : `n=${pts.length} · Pearson r=${r.toFixed(2)} on log2 (plotted axes)`;
+ status.textContent = status.dataset.idle;
+ bindPlotHover(svg, status);
+ wrap.appendChild(svg);
+ wrap.appendChild(status);
+ host.replaceChildren(wrap);
+ }
+
+ function drawCageMap(host, highlight) {
+ const pts = (window.CASCADE?.genes || []).filter((c) => c.cage && c.cage.kinetics && c.cage.kinetics !== "latent");
+ const wrap = document.createElement("div");
+ const w = 268;
+ const h = 196;
+ const m = { t: 12, r: 12, b: 28, l: 36 };
+ const svg = svgEl("svg", { class: "scatter cage-map", viewBox: `0 0 ${w} ${h}` });
+ const xs = pts.map((p) => p.cage.balf2_ratio);
+ const ys = pts.map((p) => p.cage.bdlf4_ratio);
+ const xMin = -0.05;
+ const xMax = Math.max(1.6, ...xs) + 0.15;
+ const yMin = -0.05;
+ const yMax = Math.max(1.6, ...ys) + 0.15;
+ const X = (v) => m.l + ((v - xMin) / (xMax - xMin)) * (w - m.l - m.r);
+ const Y = (v) => m.t + ((yMax - v) / (yMax - yMin)) * (h - m.t - m.b);
+ [0.1, 0.5].forEach((cut) => {
+ svg.appendChild(svgEl("line", {
+ x1: X(cut), x2: X(cut), y1: m.t, y2: m.t + (h - m.t - m.b),
+ stroke: "#334155", "stroke-dasharray": "3 3",
+ }));
+ });
+ const lateL = svgEl("text", { x: X(0.05), y: m.t + 10, fill: "#7dce9a", "font-size": "9" });
+ lateL.textContent = "true late";
+ svg.appendChild(lateL);
+ const leakL = svgEl("text", { x: X(0.3), y: m.t + 10, fill: "#f2d06b", "font-size": "9" });
+ leakL.textContent = "leaky";
+ svg.appendChild(leakL);
+ const earlyL = svgEl("text", { x: X(1.05), y: m.t + 10, fill: "#5eb0ff", "font-size": "9" });
+ earlyL.textContent = "early";
+ svg.appendChild(earlyL);
+ const xlab = svgEl("text", { x: m.l + (w - m.l - m.r) / 2, y: h - 6, "text-anchor": "middle", fill: "#8b9aab", "font-size": "10" });
+ xlab.textContent = "BALF2 ratio (DNA replication)";
+ svg.appendChild(xlab);
+ const ylab = svgEl("text", {
+ x: 11,
+ y: m.t + (h - m.t - m.b) / 2,
+ "text-anchor": "middle",
+ fill: "#8b9aab",
+ "font-size": "10",
+ transform: `rotate(-90 11 ${m.t + (h - m.t - m.b) / 2})`,
+ });
+ ylab.textContent = "BDLF4 ratio (vPIC)";
+ svg.appendChild(ylab);
+ pts.forEach((p) => {
+ const on = p.gene === highlight || state.pinned.has(p.gene);
+ const c = svgEl("circle", {
+ cx: X(p.cage.balf2_ratio),
+ cy: Y(p.cage.bdlf4_ratio),
+ r: p.gene === highlight ? 5.5 : on ? 4.2 : 3.3,
+ fill: cageColor(p.cage.kinetics),
+ opacity: p.gene === highlight ? 1 : on ? 0.95 : 0.6,
+ stroke: state.pinned.has(p.gene) ? colorFor(p.gene) : "none",
+ "stroke-width": state.pinned.has(p.gene) ? 1.6 : 0,
+ "data-gene": p.gene,
+ });
+ const title = document.createElementNS("http://www.w3.org/2000/svg", "title");
+ title.textContent = `${p.gene} · BALF2 ${p.cage.balf2_ratio.toFixed(2)} · BDLF4 ${p.cage.bdlf4_ratio.toFixed(2)}`;
+ c.appendChild(title);
+ svg.appendChild(c);
+ });
+ const status = document.createElement("div");
+ status.className = "plot-status";
+ status.dataset.idle = "Djavadian Fig. 4 · dashed at 0.1 / 0.5";
+ status.textContent = status.dataset.idle;
+ bindPlotHover(svg, status);
+ wrap.appendChild(svg);
+ wrap.appendChild(status);
+ host.replaceChildren(wrap);
+ }
+
+ function drawPinHeatmap(host, highlight) {
+ const names = [...state.pinned].filter((n) => BY_NAME[n]);
+ names.sort((a, b) => {
+ const da = BY_NAME[a].peak_hour - BY_NAME[b].peak_hour;
+ return da || a.localeCompare(b);
+ });
+ if (!names.length) {
+ host.replaceChildren();
+ const p = document.createElement("p");
+ p.className = "empty";
+ p.style.margin = "0";
+ p.textContent = "Pin genes to see their RNA cascade as a heatmap (sorted by peak hour).";
+ host.appendChild(p);
+ return;
+ }
+ const rowH = 14;
+ const m = { t: 16, r: 8, b: 6, l: 52 };
+ const w = 268;
+ const h = m.t + m.b + names.length * rowH;
+ const svg = svgEl("svg", { class: "heat", viewBox: `0 0 ${w} ${h}`, preserveAspectRatio: "xMidYMin meet" });
+ svg.style.height = `${h}px`;
+ HOURS.forEach((hr, i) => {
+ const x = m.l + (i + 0.5) * ((w - m.l - m.r) / HOURS.length);
+ const t = svgEl("text", { x, y: 11, "text-anchor": "middle", fill: "#8b9aab", "font-size": "9" });
+ t.textContent = hr;
+ svg.appendChild(t);
+ });
+ names.forEach((name, ri) => {
+ const g = BY_NAME[name];
+ const y = m.t + ri * rowH;
+ const lab = svgEl("text", {
+ x: m.l - 4,
+ y: y + rowH * 0.72,
+ "text-anchor": "end",
+ fill: name === highlight ? "#e7ecf1" : "#8b9aab",
+ "font-size": "9",
+ "font-family": "ui-monospace, monospace",
+ "data-gene": name,
+ });
+ lab.textContent = name;
+ svg.appendChild(lab);
+ g.hours.forEach((hr, i) => {
+ const cw = (w - m.l - m.r) / HOURS.length;
+ const rect = svgEl("rect", {
+ x: m.l + i * cw + 0.6,
+ y: y + 1,
+ width: cw - 1.2,
+ height: rowH - 2,
+ rx: 1.5,
+ fill: heatFill(Math.log2(Math.max(g.linear_fold[i], 1e-6))),
+ stroke: name === highlight ? "#e7ecf1" : "none",
+ "stroke-width": name === highlight ? 0.8 : 0,
+ "data-gene": name,
+ });
+ const title = document.createElementNS("http://www.w3.org/2000/svg", "title");
+ title.textContent = `${name} · ${hr} h · ${g.linear_fold[i].toFixed(1)}×`;
+ rect.appendChild(title);
+ svg.appendChild(rect);
+ });
+ });
+ svg.onmousemove = (ev) => {
+ const gene = ev.target && ev.target.dataset ? ev.target.dataset.gene : null;
+ highlightOnChart(gene);
+ };
+ svg.onmouseleave = () => highlightOnChart(null);
+ svg.onclick = (ev) => {
+ const gene = ev.target && ev.target.dataset ? ev.target.dataset.gene : null;
+ if (gene) showDetail(gene);
+ };
+ host.replaceChildren(svg);
+ }
+
function showDetail(name) {
const g = BY_NAME[name];
const el = $("#detail-body");
@@ -363,6 +762,9 @@
el.innerHTML = `
Hover a line or pin a gene. Faint traces are the other 59 RNAs (10–90% band = typical range).
`; return; } + const cas = cascadeOf(name); + const cage = cas?.cage; + const prot = cas?.protein; const peakMark = g.peak_hour; const rows = g.hours .map( @@ -370,19 +772,58 @@ `Separate tracks, independent y (Weekes QTV / Ersing): shape, not magnitude. Same hour axis as the main chart.
+| Hour | Fold | log2 |
|---|---|---|
| Hour | RNA fold | log2 |
Yuan et al. J Virol 2006 Table 1 (doi:10.1128/JVI.80.5.2548-2565.2006). Signed-fold converted to linear (negatives inverted). Missing table cells are not shown.
`; +Yuan RNA is Akata cytoplasmic fold vs 0 h. Ersing protein is TMT in gp350+ cells (Akata anti-IgG 0 vs 48 h; P3HR1-ZHT/RHT 0/24/48/72 h) — not paired aliquots. Djavadian CAGE class is HEK293 at 48 h by DNA-replication dependence. ${rna48 && akF ? `At 48 h this gene is ${rna48.toFixed(1)}× RNA vs ${akF.toFixed(1)}× protein.` : ""} Nested lytic RNAs can look “early” on arrays while CAGE and protein are late (Djavadian Fig. 1).
`; + drawAlignedSparklines($("#spark-host"), g); + drawCageMap($("#cage-host"), name); + drawScatter($("#scatter-host"), name); + const back = $("#back-overview"); + if (back) { + back.onclick = () => { + state.hovered = null; + render(); + }; + } } function render() { @@ -392,7 +833,26 @@ else if (state.pinned.size === 1) showDetail([...state.pinned][0]); else { $("#detail-body").innerHTML = `Hover a faint line to identify it. Click to pin (color). Context: all 59 genes as ghosts + 10–90 percentile band and dashed median. Default pins are MultiCAST calibrators.
+Log2 fold vs 0 h, genes ordered by peak hour (Yuan-style cascade; Weekes/Ersing heatmap of temporal profiles). Main line chart is unchanged.
+ +BALF2 vs BDLF4 ratios (Djavadian Fig. 4). True late < 0.1, early > 0.5, leaky in between. Not a time series.
+ +Same cell/trigger, not paired aliquots (Ersing; Weekes 2014 CMV). Color = CAGE class. Diagonal = equal fold. IE RNA often peaks before 24 h, so 48 h RNA can look modest while protein is still high.
+Pinned now: ${[...state.pinned].join(", ") || "none"}
`; + drawPinHeatmap($("#heat-host"), null); + drawCageMap($("#cage-host"), null); + drawScatter($("#scatter-host"), null); } $("#y-linear").classList.toggle("active", state.yMode === "linear"); $("#y-log2").classList.toggle("active", state.yMode === "log2"); @@ -429,6 +889,27 @@ const top = [...GENES].sort((a, b) => b.peak_fold - a.peak_fold).slice(0, 8).map((g) => g.gene); pinOnly(top); }; + $("#preset-protein").onclick = () => { + pinOnly(["BZLF1", "BRLF1", "BMRF1", "BFRF1", "BLLF1", "BFRF3"]); + }; + $("#preset-mismatch").onclick = () => { + pinOnly(GENES.filter((g) => cascadeOf(g.gene)?.array_vs_cage_mismatch).map((g) => g.gene)); + }; + document.querySelectorAll("[data-cage]").forEach((btn) => { + btn.onclick = () => { + const kin = btn.dataset.cage; + if (btn.dataset.action === "pin-cage") { + pinCage(kin); + return; + } + if (kin === "all") state.cageFilter = "all"; + else state.cageFilter = state.cageFilter === kin ? "all" : kin; + document.querySelectorAll("#cage-filter [data-cage]").forEach((b) => { + b.classList.toggle("active", b.dataset.cage === state.cageFilter); + }); + renderList(); + }; + }); $("#y-linear").onclick = () => { state.yMode = "linear"; render(); diff --git a/ebv_lytic_expression/web/cascade.data.js b/ebv_lytic_expression/web/cascade.data.js new file mode 100644 index 0000000..4e02dff --- /dev/null +++ b/ebv_lytic_expression/web/cascade.data.js @@ -0,0 +1,2244 @@ +window.CASCADE = { + "sources": [ + { + "id": "yuan2006", + "cite": "Yuan et al. J Virol 2006;80:2548\u20132565", + "doi": "10.1128/JVI.80.5.2548-2565.2006", + "note": "Akata + anti-IgG cytoplasmic RNA fold vs 0 h (Table 1)." + }, + { + "id": "djavadian2018", + "cite": "Djavadian, Hayes, Johannsen. PLOS Pathog 2018;14:e1007114", + "doi": "10.1371/journal.ppat.1007114", + "note": "HEK293 CAGE-seq TSS class by DNA replication (BALF2) and vPIC (BDLF4), 48 h after Rta+Zta. Not a time series." + }, + { + "id": "ersing2017", + "cite": "Ersing, Nobre, Gewurz, Weekes et al. Cell Rep 2017;19:1479\u20131493", + "doi": "10.1016/j.celrep.2017.04.062", + "note": "TMT of gp350+ cells. Akata: 0 vs 48 h anti-IgG (same trigger as Yuan). P3HR1-ZHT/RHT: 0/24/48/72 h. Not paired with Yuan RNA aliquots. Protein temporal classes complement IE/E/L RNA (Ersing; Weekes et al. Cell 2014 CMV)." + } + ], + "genes": [ + { + "gene": "BZLF1", + "yuan_class": "IE", + "cage": null, + "protein": { + "gene": "BZLF1", + "source_id": "BZLF1", + "peptides_expts": 4, + "p3hr1_hours": [ + 0, + 24, + 48, + 72 + ], + "p3hr1_signal": [ + 1721.4980103744163, + 8614.317606351688, + 7959.466777134119, + 7253.485789061975 + ], + "akata_hours": [ + 0, + 48 + ], + "akata_signal": [ + 175.82785196361098, + 9455.35080523755 + ] + }, + "array_vs_cage_mismatch": false, + "rna_fold_48h": 2.9, + "akata_protein_fold_48h": 53.77618335003269 + }, + { + "gene": "BRLF1", + "yuan_class": "IE", + "cage": { + "gene": "BRLF1", + "orf": "BRLF1", + "kinetics": "early", + "balf2_ratio": 1.07, + "bdlf4_ratio": 1.96, + "wt_tpm": 5, + "annotation": "Rta", + "vpic_independent_late": false + }, + "protein": { + "gene": "BRLF1", + "source_id": "BRLF1", + "peptides_expts": 4, + "p3hr1_hours": [ + 0, + 24, + 48, + 72 + ], + "p3hr1_signal": [ + 3892.9515323079204, + 18710.429463627093, + 19458.343778807168, + 13275.583522788613 + ], + "akata_hours": [ + 0, + 48 + ], + "akata_signal": [ + 150.77874716031127, + 951.8930624602408 + ] + }, + "array_vs_cage_mismatch": false, + "rna_fold_48h": 2.7, + "akata_protein_fold_48h": 6.313177953708339 + }, + { + "gene": "BMLF1", + "yuan_class": "IE/E", + "cage": { + "gene": "BMLF1", + "orf": "SM", + "kinetics": "early", + "balf2_ratio": 1.05, + "bdlf4_ratio": 1.08, + "wt_tpm": 969, + "annotation": "lytic RNA export (BMLF1)", + "vpic_independent_late": false + }, + "protein": { + "gene": "BMLF1", + "source_id": "BMLF1", + "peptides_expts": 4, + "p3hr1_hours": [ + 0, + 24, + 48, + 72 + ], + "p3hr1_signal": [ + 1118.043411533191, + 20711.139079680386, + 18466.417979360485, + 17548.891729126233 + ], + "akata_hours": [ + 0, + 48 + ], + "akata_signal": [ + 605.915771968321, + 24224.801903213985 + ] + }, + "array_vs_cage_mismatch": false, + "rna_fold_48h": 3.9, + "akata_protein_fold_48h": 39.98047752498598 + }, + { + "gene": "BCRF2", + "yuan_class": "U", + "cage": null, + "protein": null, + "array_vs_cage_mismatch": false, + "rna_fold_48h": 4.0, + "akata_protein_fold_48h": null + }, + { + "gene": "EBNALP", + "yuan_class": "LT", + "cage": null, + "protein": { + "gene": "EBNALP", + "source_id": "EBNA-LP", + "peptides_expts": 3, + "p3hr1_hours": [ + 0, + 24, + 48, + 72 + ], + "p3hr1_signal": [ + 197.39527534434723, + 125.1459175048711, + 128.26840782962338, + 131.4748143896989 + ], + "akata_hours": [ + 0, + 48 + ], + "akata_signal": [ + null, + null + ] + }, + "array_vs_cage_mismatch": false, + "rna_fold_48h": 6.1, + "akata_protein_fold_48h": null + }, + { + "gene": "EBNA2", + "yuan_class": "LT", + "cage": null, + "protein": null, + "array_vs_cage_mismatch": false, + "rna_fold_48h": 5.4, + "akata_protein_fold_48h": null + }, + { + "gene": "BHLF1", + "yuan_class": "E", + "cage": { + "gene": "BHLF1", + "orf": "BHLF1", + "kinetics": "early", + "balf2_ratio": 0.51, + "bdlf4_ratio": 1.8, + "wt_tpm": 65, + "annotation": "OriLyt transcript", + "vpic_independent_late": false + }, + "protein": null, + "array_vs_cage_mismatch": false, + "rna_fold_48h": 8.4, + "akata_protein_fold_48h": null + }, + { + "gene": "BHRF1", + "yuan_class": "E", + "cage": { + "gene": "BHRF1", + "orf": "BHRF1", + "kinetics": "early", + "balf2_ratio": 0.81, + "bdlf4_ratio": 1.25, + "wt_tpm": 758, + "annotation": "v-Bcl2", + "vpic_independent_late": false + }, + "protein": { + "gene": "BHRF1", + "source_id": "BHRF1", + "peptides_expts": 4, + "p3hr1_hours": [ + 0, + 24, + 48, + 72 + ], + "p3hr1_signal": [ + 187.40820431979338, + 971.9500718486142, + 1122.673898869493, + 880.8664880031293 + ], + "akata_hours": [ + 0, + 48 + ], + "akata_signal": [ + 80.0818049257515, + 1395.1112564115456 + ] + }, + "array_vs_cage_mismatch": false, + "rna_fold_48h": 5.2, + "akata_protein_fold_48h": 17.421076581690865 + }, + { + "gene": "BFLF2", + "yuan_class": "E", + "cage": { + "gene": "BFLF2", + "orf": "BFLF2", + "kinetics": "early", + "balf2_ratio": 0.79, + "bdlf4_ratio": 0.41, + "wt_tpm": 187, + "annotation": "capsid nuclear egress", + "vpic_independent_late": false + }, + "protein": { + "gene": "BFLF2", + "source_id": "BFLF2", + "peptides_expts": 4, + "p3hr1_hours": [ + 0, + 24, + 48, + 72 + ], + "p3hr1_signal": [ + 582.6229785251097, + 13068.728066602474, + 15110.961140950376, + 8238.065800037342 + ], + "akata_hours": [ + 0, + 48 + ], + "akata_signal": [ + 8.759662674357276, + 1958.073835390964 + ] + }, + "array_vs_cage_mismatch": false, + "rna_fold_48h": 7.1, + "akata_protein_fold_48h": 223.5330181289925 + }, + { + "gene": "BFLF1", + "yuan_class": "E", + "cage": { + "gene": "BFLF1", + "orf": "BFLF1", + "kinetics": "leaky", + "balf2_ratio": 0.19, + "bdlf4_ratio": 0.14, + "wt_tpm": 6, + "annotation": "packaging protein", + "vpic_independent_late": false + }, + "protein": { + "gene": "BFLF1", + "source_id": "BFLF1", + "peptides_expts": 4, + "p3hr1_hours": [ + 0, + 24, + 48, + 72 + ], + "p3hr1_signal": [ + 682.9660528514127, + 16219.48509345272, + 13458.210173855177, + 10784.936179236305 + ], + "akata_hours": [ + 0, + 48 + ], + "akata_signal": [ + 126.86963634460379, + 3206.924896982355 + ] + }, + "array_vs_cage_mismatch": false, + "rna_fold_48h": 2.9, + "akata_protein_fold_48h": 25.277323947486487 + }, + { + "gene": "BFRF1", + "yuan_class": "E", + "cage": { + "gene": "BFRF1", + "orf": "BFRF1", + "kinetics": "late", + "balf2_ratio": 0.01, + "bdlf4_ratio": 0.0, + "wt_tpm": 104, + "annotation": "capsid nuclear egress", + "vpic_independent_late": false + }, + "protein": { + "gene": "BFRF1", + "source_id": "BFRF1", + "peptides_expts": 4, + "p3hr1_hours": [ + 0, + 24, + 48, + 72 + ], + "p3hr1_signal": [ + 944.6491404856235, + 27821.2763042337, + 37656.18890638144, + 27294.063061921497 + ], + "akata_hours": [ + 0, + 48 + ], + "akata_signal": [ + 283.68561059544254, + 19890.861304652375 + ] + }, + "array_vs_cage_mismatch": true, + "rna_fold_48h": 6.9, + "akata_protein_fold_48h": 70.11586263717221 + }, + { + "gene": "BFRF2", + "yuan_class": "E", + "cage": null, + "protein": { + "gene": "BFRF2", + "source_id": "BFRF2", + "peptides_expts": 4, + "p3hr1_hours": [ + 0, + 24, + 48, + 72 + ], + "p3hr1_signal": [ + 89.74464346378407, + 1216.4376272078232, + 943.0104247847609, + 746.0802965438169 + ], + "akata_hours": [ + 0, + 48 + ], + "akata_signal": [ + 18.075400127208205, + 348.78107002376214 + ] + }, + "array_vs_cage_mismatch": false, + "rna_fold_48h": 5.5, + "akata_protein_fold_48h": 19.295897604986095 + }, + { + "gene": "BFRF3", + "yuan_class": "L", + "cage": { + "gene": "BFRF3", + "orf": "BFRF3", + "kinetics": "late", + "balf2_ratio": 0.02, + "bdlf4_ratio": 0.0, + "wt_tpm": 346, + "annotation": "capsid hexon tip", + "vpic_independent_late": false + }, + "protein": { + "gene": "BFRF3", + "source_id": "BFRF3", + "peptides_expts": 4, + "p3hr1_hours": [ + 0, + 24, + 48, + 72 + ], + "p3hr1_signal": [ + 267.0362089470794, + 6528.142529109496, + 7524.251546413748, + 3837.6467332476586 + ], + "akata_hours": [ + 0, + 48 + ], + "akata_signal": [ + 233.5817930861307, + 7892.826345521102 + ] + }, + "array_vs_cage_mismatch": false, + "rna_fold_48h": 5.1, + "akata_protein_fold_48h": 33.79041765729878 + }, + { + "gene": "BPLF1", + "yuan_class": "L", + "cage": { + "gene": "BPLF1", + "orf": "BPLF1", + "kinetics": "late", + "balf2_ratio": 0.0, + "bdlf4_ratio": 0.01, + "wt_tpm": 5, + "annotation": "largest tegument protein", + "vpic_independent_late": false + }, + "protein": { + "gene": "BPLF1", + "source_id": "BPLF1", + "peptides_expts": 4, + "p3hr1_hours": [ + 0, + 24, + 48, + 72 + ], + "p3hr1_signal": [ + 900.2261601671016, + 26767.601751902752, + 25298.120278528804, + 14904.448466266074 + ], + "akata_hours": [ + 0, + 48 + ], + "akata_signal": [ + 907.2192628656851, + 26739.651983677657 + ] + }, + "array_vs_cage_mismatch": false, + "rna_fold_48h": 5.0, + "akata_protein_fold_48h": 29.474299188945345 + }, + { + "gene": "BNRF1", + "yuan_class": "L", + "cage": { + "gene": "BNRF1", + "orf": "BNRF1", + "kinetics": "late", + "balf2_ratio": 0.0, + "bdlf4_ratio": 0.01, + "wt_tpm": 25, + "annotation": "major tegument protein", + "vpic_independent_late": false + }, + "protein": { + "gene": "BNRF1", + "source_id": "BNRF1", + "peptides_expts": 4, + "p3hr1_hours": [ + 0, + 24, + 48, + 72 + ], + "p3hr1_signal": [ + 2118.173945119397, + 50543.07710223947, + 55012.832782847494, + 38059.186334098 + ], + "akata_hours": [ + 0, + 48 + ], + "akata_signal": [ + 1787.8261693028517, + 38954.88650616296 + ] + }, + "array_vs_cage_mismatch": false, + "rna_fold_48h": 5.8, + "akata_protein_fold_48h": 21.78896761610392 + }, + { + "gene": "BOLF1", + "yuan_class": "L", + "cage": { + "gene": "BOLF1", + "orf": "BOLF1", + "kinetics": "late", + "balf2_ratio": 0.01, + "bdlf4_ratio": 0.01, + "wt_tpm": 6, + "annotation": "tegument, binds BPLF1", + "vpic_independent_late": false + }, + "protein": { + "gene": "BOLF1", + "source_id": "BOLF1", + "peptides_expts": 4, + "p3hr1_hours": [ + 0, + 24, + 48, + 72 + ], + "p3hr1_signal": [ + 653.6831261468536, + 8771.241532542383, + 9193.860201766931, + 5755.137625336311 + ], + "akata_hours": [ + 0, + 48 + ], + "akata_signal": [ + 15.571442439868743, + 1142.701677788862 + ] + }, + "array_vs_cage_mismatch": false, + "rna_fold_48h": 2.3, + "akata_protein_fold_48h": 73.38444605896731 + }, + { + "gene": "BORF1", + "yuan_class": "L", + "cage": { + "gene": "BORF1", + "orf": "BORF1", + "kinetics": "leaky", + "balf2_ratio": 0.19, + "bdlf4_ratio": 0.05, + "wt_tpm": 72, + "annotation": "capsid 1x triplex", + "vpic_independent_late": false + }, + "protein": { + "gene": "BORF1", + "source_id": "BORF1", + "peptides_expts": 4, + "p3hr1_hours": [ + 0, + 24, + 48, + 72 + ], + "p3hr1_signal": [ + 196.7258753186157, + 9137.580973773622, + 9055.619594918187, + 6090.562625906503 + ], + "akata_hours": [ + 0, + 48 + ], + "akata_signal": [ + 571.9393802943798, + 13279.55406883733 + ] + }, + "array_vs_cage_mismatch": false, + "rna_fold_48h": 5.7, + "akata_protein_fold_48h": 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