Module reference¶
Yeliztli runs many analysis modules over your data. Each one loads a curated panel of variants, extracts the ones you carry, and stores findings with an evidence rating. For how to read each kind of output — evidence stars, categorical levels, diplotypes, polygenic percentiles, and the recurring caveats — see the interpretation reference.
Modules come in three kinds:
- Modules with their own page in the app — you can open them from the dashboard and see a tailored view.
- Findings-only modules — they don't have a dedicated page, but their results appear in the unified Findings Explorer (these are documented together under Specialized findings).
- Disclosure-gated modules — sensitive results that stay hidden until you opt in.
How to read any module
Every module analyses consumer genotyping-array data and is research/educational only — not diagnostic. Many report categorical levels or polygenic percentiles rather than yes/no answers, and some withhold a number when the data can't support it. See Intended use & disclaimers.
Health & hereditary risk¶
| Module | What it analyses |
|---|---|
| Hereditary cancer | 28-gene hereditary-cancer panel + cancer polygenic scores |
| Cardiovascular | 16-gene panel: familial hypercholesterolemia, cardiomyopathy, channelopathy |
| Carrier status | Reproductive carrier screening across 7 recessive-disease genes |
| Gene health | Categorical risk across ~17 conditions in 4 body systems |
| Familial hypercholesterolemia | FH-focused view: LDLR/APOB/PCSK9 + LDL-C polygenic score |
| Metabolic | Polygenic scores for type-2 diabetes and BMI/obesity |
| Bone density (eBMD) | Heel bone-density polygenic score (fracture-risk context) |
| Rare variants | Customisable finder for rare and ultra-rare carried variants |
Pharmacogenomics¶
| Module | What it analyses |
|---|---|
| Pharmacogenomics | Star-allele calling + CPIC prescribing context for 11 drug-metabolism genes |
| HLA (imputed) | Operator-provisioned imputed classical-HLA calls for drug hypersensitivity, disease rule-outs, susceptibility context, and raw HLA export |
Wellness & traits¶
| Module | What it analyses |
|---|---|
| Nutrigenomics | Nutrient-metabolism pathways (folate, vitamin D, B12, omega-3, iron, lactose) |
| Methylation | MTHFR and five methylation-cycle pathways |
| Fitness | Endurance, power, recovery, and training-response pathways |
| Sleep | Caffeine metabolism, chronotype, sleep quality and disorders |
| Skin | Pigmentation/UV, barrier, oxidative-aging, and micronutrient pathways |
| Allergy & immune | Atopic, drug-hypersensitivity, food (celiac), and histamine pathways |
| Traits & personality | Cognitive, Big-Five, and behavioural trait scores (research-use) |
Ancestry¶
| Module | What it analyses |
|---|---|
| Ancestry | Global ancestry (PCA + admixture) and mtDNA / Y haplogroups |
Disclosure-gated (opt-in)¶
These stay hidden until you explicitly choose to view them.
| Module | What it analyses |
|---|---|
| APOE | APOE ε2/ε3/ε4 diplotype — cardiovascular, Alzheimer's, and lipid context |
| Parkinson's (LRRK2) | LRRK2 G2019S risk variant, with reduced-penetrance framing |
| Sex-chromosome aneuploidy | Screen for an XXY signature (confirmation-only) |
Specialized findings¶
Ten more condition-specific modules run automatically and surface in the Findings Explorer — haemochromatosis, thrombophilia, alpha-1 antitrypsin, AMD, APOL1 kidney risk, gout, LHON, MT-RNR1, G6PD, and BChE. See Specialized findings.
Quality control¶
A quality-control pass (call rate, heterozygosity, per-chromosome counts, sex inference) runs on every sample and feeds the QC summary on the dashboard. It is not a finding-producing module you pick — it's always-on background quality reporting.