def adiponectin_levels(genome):
"""Adiponectin levels."""
if genome.ethnicity == "asian":
r = unphased_match(
genome.rs1851665, {
"AA": "Slightly lower, which may be bad (rs1851665)\n",
"AG": "Typical (rs1851665)\n",
"GG": "Slightly higher, which is good (rs1851665)\n",
None: "Unable to determine for rs1851665\n"
})
r += unphased_match(
genome.rs7193788, {
"AA": "Slightly higher, which is good (rs7193788)",
"AG": "Typical (rs7193788)",
"GG": "Slightly lower, which may be bad (rs7193788)",
None: "Unable to determine for rs7193788"
})
return r
elif genome.ethnicity in [None, "european"]:
return unphased_match(
genome.rs6444175, {
"AA": "Lower, which may be bad",
"AG": "Slightly lower, which may be bad",
"GG": "Typical levels",
None: "Unable to determine"
})
def adiponectin_levels(genome):
"""Adiponectin levels."""
if genome.ethnicity == "asian":
r = unphased_match(
genome.rs1851665,
{
"AA": "Slightly lower, which may be bad (rs1851665)\n",
"AG": "Typical (rs1851665)\n",
"GG": "Slightly higher, which is good (rs1851665)\n",
None: "Unable to determine for rs1851665\n",
},
)
r += unphased_match(
genome.rs7193788,
{
"AA": "Slightly higher, which is good (rs7193788)",
"AG": "Typical (rs7193788)",
"GG": "Slightly lower, which may be bad (rs7193788)",
None: "Unable to determine for rs7193788",
},
)
return r
elif genome.ethnicity in [None, "european"]:
return unphased_match(
genome.rs6444175,
{
"AA": "Lower, which may be bad",
"AG": "Slightly lower, which may be bad",
"GG": "Typical levels",
None: "Unable to determine",
},
)
def exfoliation_glaucoma(genome):
"""Exfoliation glaucoma."""
assert_european(genome)
OR = unphased_match(genome.rs2165241, {
"CT": 0.79,
})
raise NotImplementedError()
def stroke(genome):
"""Stroke."""
return unphased_match(genome.rs12425791, {
"AA": "Moderately increased risk of having a stroke",
"AG": "Slightly increased risk of having a stroke",
"GG": "Typical risk of having a stroke",
None: "Unable to determine"})
def caffeine_metabolism(genome):
"""Caffeine metabolism."""
assert_european(genome)
return unphased_match(
genome.rs762551,
{"AA": "Fast metabolizer", "AC": "Slow metabolizer", "CC": "Slow metabolizer", None: "Unable to determine"},
)
def biological_age(genome):
"""Biological aging (telomere lengths)."""
assert_european(genome)
ages = {
"rs10936599": {"TT": 7.82, "CT": 3.91, "CC": 0, None: 0},
"rs2736100": {"AA": 3.14, "AC": 0, "CC": -3.14, None: 0},
"rs9420907": {"AA": 0, "AC": -2.76, "CC": -5.52, None: 0},
"rs755017": {"AA": 0, "AG": -2.47, "GG": -4.94, None: 0},
"rs11100479": {"CC": 5.98, "CT": -2.99, "TT": 0, None: 0},
"rs10165485": {"TT": 0, "CT": -2.23, "CC": -4.46, None: 0},
}
age = [unphased_match(genome[rsid], t) for (rsid, t) in ages.items()]
def qual(age):
if age <= 0:
return "younger"
elif age > 0:
return "older"
msg = "From %.1f years %s to %.1f years %s than actual age\n" % (
abs(min(age)),
qual(min(age)),
abs(max(age)),
qual(max(age)),
)
msg += "The sum is %.1f years %s, compared to actual age" % (abs(sum(age)), qual(sum(age)))
return msg
def hiv_aids_resistance(genome):
"""Resistance to HIV/AIDS."""
return unphased_match(
genome.i3003626, {
"DD": "Some resistance to most common strain of HIV",
"DI": "Not resistant, but may have slower disease progression",
"II": "Not resistant"
})
def hair_curl(genome):
assert_european(genome)
return unphased_match(
genome.rs17646946, {
"AA": "Straighter hair on average",
"AG": "Straighter hair on average",
"GG": "Slightly curlier hair on average"
})
def pain_sensitivity(genome):
"""Pain sensitivity."""
return unphased_match(
genome.rs6269, {
"AA": "Increased sensitivity to pain",
"AG": "Typical sensitivity to pain",
"GG": "Less sensitive to pain",
None: "Unable to determine"
})
def blond_vs_brown_hair(genome):
"""Hair color; blond versus brown."""
return unphased_match(
genome.rs1667394, {
"CC": "Greatly decreased odds of having blond hair vs. brown",
"CT": "Decreased odds of having blond hair vs. brown",
"TT": "Typical odds of having blond hair vs. brown hair",
None: "Unable to determine"
})
def red_hair(genome):
"""Hair color; odds for red hair."""
return unphased_match(
genome.rs1805007, {
"CC": "Typical odds for red hair",
"CT": "Substantially increased odds for red hair",
"TT": "Greatly increased odds for red hair",
None: "Unable to determine"
})
def bitter_taste(genome):
"Bitter taste perception."
return unphased_match(
genome.rs713598, {
"CC": "Probably can't taste certain bitter flavours",
"CG": "Can taste bitter flavours that others can't",
"GG": "Can taste bitter flavours that others can't",
None: "Unable to determine"
})
def earwax_type(genome):
"Earwax type."
return unphased_match(
genome.rs17822931, {
"CC": "Wet earwax (sticky, honey-colored)",
"CT": "Wet earwax (sticky, honey-colored)",
"TT": "Dry earwax (flaky, pale)",
None: "Unable to determine"
})
def malaria_resistance(genome):
"Malaria resistance (Duffy antigen)."
return unphased_match(
genome.rs2814778, {
"CC": "Likely resistant to P. vivax",
"CT": "Likely to have some resistance to P. vivax",
"TT": "Likely not resistant to P. vivax",
None: "Unable to determine"
})
def alcohol_flush_reaction(genome):
"Alcohol flush reaction."
return unphased_match(
genome.rs671, {
"AA": "Extreme reaction (no copies of the ALDH2 gene)",
"AG": "Moderate reaction (one copy of the ALDH2 gene)",
"GG": "Little to no reaction (two copies of the ALDH2 gene)",
None: "Unable to determine"
})
def lactose_intolerance(genome):
"Lactose intolerance."
return unphased_match(
genome.rs4988235, {
"AA": "Likely lactose tolerant",
"AG": "Likely lactose tolerant",
"GG": "Likely lactose intolerant",
None: "Unable to determine"
})
def birth_weight(genome):
"""Birth weight."""
assert_european(genome)
weights = {
"rs7903146": {"TT": 0, "CT": -30, "CC": -60, None: 0},
"rs1799884": {"TT": +54, "CT": +27, "CC": 0, None: 0},
}
weight = [unphased_match(genome[rsid], w) for (rsid, w) in weights.items()]
return "From %.1fg to %.1fg (sum: %.1fg) compared to typical weight" % (min(weight), max(weight), sum(weight))
def norovirus_resistance(genome):
"""Norovirus resistance (most common strain)."""
return unphased_match(
genome.rs601338, {
"AA": "Resistant to most common strain",
"AG": "Likely not resistant to most common strain",
"GG": "Likely not resistant to most common strain",
None: "Unable to determine"
})
def biological_age(genome):
"""Biological aging (telomere lengths)."""
assert_european(genome)
ages = {
"rs10936599": {
"TT": 7.82,
"CT": 3.91,
"CC": 0,
None: 0
},
"rs2736100": {
"AA": 3.14,
"AC": 0,
"CC": -3.14,
None: 0
},
"rs9420907": {
"AA": 0,
"AC": -2.76,
"CC": -5.52,
None: 0
},
"rs755017": {
"AA": 0,
"AG": -2.47,
"GG": -4.94,
None: 0
},
"rs11100479": {
"CC": 5.98,
"CT": -2.99,
"TT": 0,
None: 0
},
"rs10165485": {
"TT": 0,
"CT": -2.23,
"CC": -4.46,
None: 0
},
}
age = [unphased_match(genome[rsid], t) for (rsid, t) in ages.items()]
def qual(age):
if age <= 0:
return "younger"
elif age > 0:
return "older"
msg = "From %.1f years %s to %.1f years %s than actual age\n" % (abs(
min(age)), qual(min(age)), abs(max(age)), qual(max(age)))
msg += "The sum is %.1f years %s, compared to actual age" % (abs(
sum(age)), qual(sum(age)))
return msg
def smoking_behaviour(genome):
"""Smoking behaviour."""
assert_european(genome)
return unphased_match(
genome.rs1051730, {
"AA": "Likely to smoke more than average",
"AG": "Likely to smoke a little bit more than average",
"GG": "Likely to smoke typical amount of cigarettes per day",
None: "Unable to determine"
})
def muscle_performance(genome):
"""Muscle performance."""
return unphased_match(
genome.rs1815739, {
"CC": "Likely sprinter, perhaps endurance athlete (two copies)",
"CT": "Likely sprinter, perhaps endurance athlete (one copy)",
"TT":
"Unlikely sprinter, but likely endurance athlete (no copies)",
None: "Unable to determine"
})
def hair_curl(genome):
assert_european(genome)
return unphased_match(
genome.rs17646946,
{
"AA": "Straighter hair on average",
"AG": "Straighter hair on average",
"GG": "Slightly curlier hair on average",
},
)
def hiv_aids_resistance(genome):
"""Resistance to HIV/AIDS."""
return unphased_match(
genome.i3003626,
{
"DD": "Some resistance to most common strain of HIV",
"DI": "Not resistant, but may have slower disease progression",
"II": "Not resistant",
},
)
def caffeine_metabolism(genome):
"""Caffeine metabolism."""
assert_european(genome)
return unphased_match(
genome.rs762551, {
"AA": "Fast metabolizer",
"AC": "Slow metabolizer",
"CC": "Slow metabolizer",
None: "Unable to determine"
})
def blood_glucose(genome):
"""Blood glucose."""
assert_european(genome)
return unphased_match(
genome.rs560887, {
"CC": "Average fasting plasma glucose levels of 5.18mmol/L",
"CT": "Average fasting plasma glucose levels of 5.12mmol/L",
"TT": "Average fasting plasma glucose levels of 5.06mmol/L",
None: "Unable to determine"
})
def aspargus_detection(genome):
"""Aspargus metabolite detection."""
assert_european(genome)
return unphased_match(
genome.rs4481887, {
"AA": "Higher odds of smelling aspargus in urine",
"AG": "Medium odds of smelling aspargus in urine",
"GG": "Typical odds of smelling aspargus in urine",
None: "Unable to determine"
})
def heroin_addiction(genome):
"""Heroin addiction."""
assert_european(genome)
return unphased_match(
genome.rs1799971, {
"AA": "Typical odds of addiction",
"AG": "Higher odds of addiction",
"GG": "Higher odds of addiction",
None: "Unable to determine"
})
def eye_color(genome):
"Eye color."
assert_european(genome)
return unphased_match(
genome.rs12913832, {
"AA": "Brown eyes, although 14% have green and 1% have blue",
"AG": "Most likely brown or green, but 7% have blue",
"GG": "Most likely blue, but 30% have green and 1% brown",
None: "Unable to determine"
})
def pain_sensitivity(genome):
"""Pain sensitivity."""
return unphased_match(
genome.rs6269,
{
"AA": "Increased sensitivity to pain",
"AG": "Typical sensitivity to pain",
"GG": "Less sensitive to pain",
None: "Unable to determine",
},
)
def blond_vs_brown_hair(genome):
"""Hair color; blond versus brown."""
return unphased_match(
genome.rs1667394,
{
"CC": "Greatly decreased odds of having blond hair vs. brown",
"CT": "Decreased odds of having blond hair vs. brown",
"TT": "Typical odds of having blond hair vs. brown hair",
None: "Unable to determine",
},
)
def bitter_taste(genome):
"Bitter taste perception."
return unphased_match(
genome.rs713598,
{
"CC": "Probably can't taste certain bitter flavours",
"CG": "Can taste bitter flavours that others can't",
"GG": "Can taste bitter flavours that others can't",
None: "Unable to determine",
},
)
def red_hair(genome):
"""Hair color; odds for red hair."""
return unphased_match(
genome.rs1805007,
{
"CC": "Typical odds for red hair",
"CT": "Substantially increased odds for red hair",
"TT": "Greatly increased odds for red hair",
None: "Unable to determine",
},
)
def muscle_performance(genome):
"""Muscle performance."""
return unphased_match(
genome.rs1815739,
{
"CC": "Likely sprinter, perhaps endurance athlete (two copies)",
"CT": "Likely sprinter, perhaps endurance athlete (one copy)",
"TT": "Unlikely sprinter, but likely endurance athlete (no copies)",
None: "Unable to determine",
},
)
def alcohol_flush_reaction(genome):
"Alcohol flush reaction."
return unphased_match(
genome.rs671,
{
"AA": "Extreme reaction (no copies of the ALDH2 gene)",
"AG": "Moderate reaction (one copy of the ALDH2 gene)",
"GG": "Little to no reaction (two copies of the ALDH2 gene)",
None: "Unable to determine",
},
)
def malaria_resistance(genome):
"Malaria resistance (Duffy antigen)."
return unphased_match(
genome.rs2814778,
{
"CC": "Likely resistant to P. vivax",
"CT": "Likely to have some resistance to P. vivax",
"TT": "Likely not resistant to P. vivax",
None: "Unable to determine",
},
)
def lactose_intolerance(genome):
"Lactose intolerance."
return unphased_match(
genome.rs4988235,
{
"AA": "Likely lactose tolerant",
"AG": "Likely lactose tolerant",
"GG": "Likely lactose intolerant",
None: "Unable to determine",
},
)
def norovirus_resistance(genome):
"""Norovirus resistance (most common strain)."""
return unphased_match(
genome.rs601338,
{
"AA": "Resistant to most common strain",
"AG": "Likely not resistant to most common strain",
"GG": "Likely not resistant to most common strain",
None: "Unable to determine",
},
)
def earwax_type(genome):
"Earwax type."
return unphased_match(
genome.rs17822931,
{
"CC": "Wet earwax (sticky, honey-colored)",
"CT": "Wet earwax (sticky, honey-colored)",
"TT": "Dry earwax (flaky, pale)",
None: "Unable to determine",
},
)
def eye_color(genome):
"Eye color."
assert_european(genome)
return unphased_match(
genome.rs12913832,
{
"AA": "Brown eyes, although 14% have green and 1% have blue",
"AG": "Most likely brown or green, but 7% have blue",
"GG": "Most likely blue, but 30% have green and 1% brown",
None: "Unable to determine",
},
)
def blood_glucose(genome):
"""Blood glucose."""
assert_european(genome)
return unphased_match(
genome.rs560887,
{
"CC": "Average fasting plasma glucose levels of 5.18mmol/L",
"CT": "Average fasting plasma glucose levels of 5.12mmol/L",
"TT": "Average fasting plasma glucose levels of 5.06mmol/L",
None: "Unable to determine",
},
)
def heroin_addiction(genome):
"""Heroin addiction."""
assert_european(genome)
return unphased_match(
genome.rs1799971,
{
"AA": "Typical odds of addiction",
"AG": "Higher odds of addiction",
"GG": "Higher odds of addiction",
None: "Unable to determine",
},
)
def aspargus_detection(genome):
"""Aspargus metabolite detection."""
assert_european(genome)
return unphased_match(
genome.rs4481887,
{
"AA": "Higher odds of smelling aspargus in urine",
"AG": "Medium odds of smelling aspargus in urine",
"GG": "Typical odds of smelling aspargus in urine",
None: "Unable to determine",
},
)
def breast_cancer(genome):
"""Breast cancer."""
if not genome.female:
raise ValueError("Only applicable for females")
s = []
s.append(unphased_match(genome.rs1219648, {
"AA": "Typical odds",
"AG": "Slightly higher odds",
"GG": "Moderately higher odds",
None: "Unable to determine (see rs2420946 instead)"}))
s.append(unphased_match(genome.rs3803662, {
"AA": "Moderately increased odds",
"AG": "?",
"GG": "Typical odds",
None: "Unable to determine"}))
s.append("Note: There are MANY more SNPs to test here...")
# TODO: Add remaining SNPs
return "\n".join(s)
def smoking_behaviour(genome):
"""Smoking behaviour."""
assert_european(genome)
return unphased_match(
genome.rs1051730,
{
"AA": "Likely to smoke more than average",
"AG": "Likely to smoke a little bit more than average",
"GG": "Likely to smoke typical amount of cigarettes per day",
None: "Unable to determine",
},
)
def migraines(genome):
"""Migranes."""
assert_european(genome)
s = []
s.append(unphased_match(genome.rs2651899, {
"CC": "Slightly higher odds of migraines",
"CT": "Typical odds of migraines",
"TT": "Slightly lower odds of migraines",
None: "Unable to determine"}))
s.append(unphased_match(genome.rs10166942, {
"TT": "Typical odds of migraines",
"CT": "Slightly lower odds of migraines",
"CC": "Slightly lower odds of migraines",
None: "Unable to determine"}))
s.append(unphased_match(genome.rs11172113, {
"TT": "Slightly higher odds of migraines",
"CT": "Typical odds of migraines",
"CC": "Slightly lower odds of migraines",
None: "Unable to determine"}))
return "\n".join(s)
def birth_weight(genome):
"""Birth weight."""
assert_european(genome)
weights = {
"rs7903146": {
"TT": 0,
"CT": -30,
"CC": -60,
None: 0
},
"rs1799884": {
"TT": +54,
"CT": +27,
"CC": 0,
None: 0
},
}
weight = [unphased_match(genome[rsid], w) for (rsid, w) in weights.items()]
return "From %.1fg to %.1fg (sum: %.1fg) compared to typical weight" % (
min(weight), max(weight), sum(weight))
def hypothyroidism(genome):
"""Hypothyroidism.
Studies:
http://dx.doi.org/10.1371/journal.pone.0034442
"""
if genome.ethnicity is not None and genome.ethnicity != "european":
raise ValueError("Only applicable to Europeans")
# TODO: Use a better score metric and use weighting and ORs.
# TODO: Try to use interval arithmetic as well, for fun.
scores = {
"rs7850258": {"GG": 0.5, "AG": 0, "AA": -0.5, None: 0},
"rs2476601": {"GG": 1, "AG": 0.5, "AA": 0, None: 0},
"rs3184504": {"TT": 0.5, "CT": 0, "CC": -0.5, None: 0},
"rs4915077": {"CC": 1, "CT": 0.5, "TT": 0, None: 0},
"rs2517532": {"GG": 0.5, "AG": 0, "AA": -0.5, None: 0},
}
hi = sum(map(lambda l: max(l.values()), scores.values()))
lo = sum(map(lambda l: min(l.values()), scores.values()))
score = 0.0
for rsid, genotypes in scores.items():
score += unphased_match(genome[rsid], genotypes)
if score > 0:
s = "About %.1f%% higher risk than baseline\n" % (100.0*score/hi)
s += "(%.1f vs %.1f of %.1f points)\n" % (score, lo, hi)
s += "Test is unweighted, see 23andMe for more info"
return s
elif score < 0:
s = "About %.1f%% lower risk than baseline\n" % 100.0*score/lo
s += "(%.1f vs %.1f of %.1f points)\n" % (score, lo, hi)
s += "Test is unweighted, see 23andMe for more info"
return s
else:
return "Typical risk"
