Live · free to use
A free allele-frequency reference built on 9,743 Malaysian people and 762,042 markers, with frequencies broken down by ancestry group. Type a marker, a gene or a condition. Aggregate counts only, and no personal data of any kind. Looking up a marker by its rsID needs no account. This browser is a free preview of the data behind JRP 2.0, the next phase of the Prima Nexus Joint Research Program (Prima Nexus JRP).
Why this exists
differ by 20 percentage points or more in allele frequency between Chinese, Malay and Indian Malaysians, and 19,304 of those differ by 30 points or more. For any of them a single pooled national figure is meaningless, and the US or European reference value a researcher would otherwise reach for is simply the wrong number for most patients in front of them.
That is roughly one marker in eleven of the 738,148 markers we can compare in the ancestry build of 19 September 2026, and it is the reason to use a local denominator rather than a global one. The 8,622 markers in the MHC region of chromosome 6 are left out of that comparison, because those probes are the hardest on any array. Here is the difference on one well-understood marker:
If you work on a Malaysian cohort you have almost certainly reached for a global or largely European allele frequency because there was no local number to cite. For most markers that is a rough approximation. For pharmacogenomics it can be badly wrong, because several of the variants that matter most in clinical dosing sit at very different frequencies across Malay, Chinese and Indian ancestries than they do in European reference sets.
Look it up
An rsID goes straight to the marker, and always will, with no account. A gene name returns every published marker in or near it, and anything else searches the 1,091 markers we have curated a clinical meaning for. Those broader searches show the first two matches here; fuller research access to the data is planned for JRP 2.0.
Try rs671, rs4149056, CYP2C19, MTHFR, drug response
Prima Nexus Joint Research Program
The Prima Nexus Joint Research Program (Prima Nexus JRP) is being opened phase by phase: from generating new genomic data, to discovering new questions in our Malaysian data, to advancing selected research. What you can look up here is a preview of JRP 2.0.
Now open · JRP 1.0
Your research question, for an ongoing or future project, is turned into genomic data and insight, supported by in-kind funding for genomic services, sample logistics and bioinformatics, scientific guidance, and analysis and interpretation.
Coming soon · JRP 2.0
Research opportunities are opened around our Malaysian genomic data, the cohort behind this browser, so new questions can be explored with it.
You are looking at a preview of it: one marker at a time, the first two matches of a wider search.
Future phase · JRP 3.0
Selected discoveries are taken further, through deeper research collaboration and scientific publication opportunities.
Researchers in JRP 1.0 who work on human samples may be given priority access to our Malaysian genomic data when it opens in JRP 2.0, subject to Prima Nexus approval. Each phase has its own eligibility, selection and governance requirements.
The cohort
Every figure on this page is read from the published dataset itself, so it moves with each release rather than being typed in. The pooled counts are from the release of 18 September 2026. The ancestry breakdown further down is its own build and is currently from 19 September 2026, covering 9,656 of those people; it is refreshed separately.
Ancestry groups, grouped 19 September 2026
Ancestry groups are inferred from genetic data by principal component analysis over roughly 17,000 markers, followed by clustering, without using any labels. Self-reported ethnicity is deliberately not collected. The grouping is measured; the group names are provisional, pending confirmation against reference populations.
Why the numbers differ
Three denominators appear on this page and they mean different things. The cohort overall is 12,000 or more participants and growing. This release reports frequencies from the 9,743 genotyped on a genome-wide array. And every individual marker carries its own number of people, because the arrays changed over the collection period, so a marker on a newer array was never measured in people run on an older one.
A further 1,574 participants were run on a targeted PCR panel instead. They are deliberately excluded from every frequency here: that panel measures a few hundred pre-selected markers rather than the genome, and pooling it would distort those markers' denominators.
Sex composition of this release
Self-reported at kit activation and matched to the array cohort by barcode, so no name or date of birth is involved. Sex is on record for 9,125 of the 9,743 participants in this release, or 93.7%. Mismatches against genetic sex are almost always a data-entry error at activation rather than a biological finding.
Age at sample collection
This is how old each participant was when their sample was collected, not how old they are now. Computed for the 9,122 participants, 93.6% of this release, who have both a usable date of birth and a collection date. That denominator is not interchangeable with the count behind the frequencies. Age is derived from a restricted record that never enters the research archive and was never written to disk in producing these counts.
Headline participant figures are rounded down. Roughly 3,000 further community samples are in the processing queue and join the published counts as they clear quality control.
Provenance. This cohort comes entirely from Prima Nexus's own testing activity and from community participation, collected continuously since April 2019. It is not derived from, and carries no connection to, any client research project or any government or public-sector programme. Nothing generated under a client or public-sector engagement is used here, and nothing here is offered on any third party's behalf.
About the data
A dataset you cannot interrogate is a dataset you should not cite. These are the figures a reviewer would ask for, stated before being asked.
All genotyping is performed on Illumina bead arrays by our sequencing partners in Singapore, Hong Kong, Japan and South Korea: GSA v3 with Malaysian custom content, GSA v2/v3, and the Asian Screening Array.
The array for each batch is established from the number of markers in the delivered genotype file, not from the text of the accompanying report, because a marker count cannot be mislabelled and the reports are inconsistent.
98.48% median call rate. The individuals below a 95% call rate are flagged for review before use rather than quietly included, and the count is republished with every release.
Where the laboratory's own figure was not retained, the call rate was recomputed directly from that person's genotype file, and the record says which.
One folder per laboratory delivery, 302 of them, each carrying its order number, date, platform, the evidence for that platform, per-individual quality, and a SHA-256 for every file in it.
Raw scanner output is retained wherever it was supplied, so genotypes can be re-called from the original instrument measurement if a manifest is ever revised.
All 28,171 archive files were fingerprinted with SHA-256. Re-running the verification re-reads every file and reports anything that differs, is missing, or is new.
That is the difference between saying the data is unaltered and demonstrating it.
The grouping is measured; the names are provisional. Groups come from principal component analysis over roughly 17,000 markers followed by clustering, with no labels used. The names attached to them are inferred from two anchor markers.
Confirming them means projecting reference populations into the same space, and no Malay or Austronesian population exists in 1000 Genomes, so a separate reference is needed. Sound for deciding which markers merit attention. Not sufficient on its own for publication.
An earlier build of this page showed two Chinese clusters. They were never two populations, and they are gone. Outside the MHC region of chromosome 6 they agreed to within five percentage points at more than 99.9% of markers and carried the East Asian anchor markers equally; inside it they diverged wildly. At rs9262570, the HLA-B*58:01 tag, each cluster alone was far from Hardy-Weinberg proportions (chi-square 434 in the smaller one) while the two combined were in balance (0.2).
The cause was our own method. The clustering was reading the MHC, where hundreds of markers travel together as one haplotype, and in effect sorted Chinese participants by whether they carry it. Standard practice is to leave that region out, along with the other regions of long-range linkage disequilibrium listed by Price and colleagues (2008). Since 26 September 2026 the grouping does exactly that, and also thins markers that are close together and strongly correlated. One Chinese group results, and no component of the analysis follows the MHC any more.
The markers in the MHC region are still left out of the counts that compare groups: those probes are the hardest on any array, and that exclusion is stated wherever the counts appear.
The published data holds no personal identifiers. Records that do identify people are kept in a separate restricted area and excluded from every research output.
Nothing derived from fewer than 20 individuals is published anywhere, following the practice of the NIH All of Us programme. No individual-level data exists in the files behind this page.
Our Data Protection Officer, , answers any question about how this data is held: . See Data protection.
Positions are given in GRCh38 by default and labelled as such, with the GRCh37 coordinate shown alongside.
The same marker has different coordinates in the two builds, and mixing them is a common and silent source of wrong results.
What you get
?marker=rs671 to this page's URL and it opens on that record, so a methods section or supplementary table can point straight at it.Privacy and governance
The browser contains no personal information of any kind. No names, no dates of birth, no individual results, nothing that can be traced to a participant. It reports how many people carry a variant, the way a census reports how many people live in a state without naming them.
Nothing based on fewer than 20 people is ever displayed. Markers below that threshold are withheld from the published data entirely rather than shown with a suppressed count, and the page never computes a smaller subset of its own. That is the same small cell rule used by major national genomic programmes, so the standard is an accepted one rather than something we invented.
Collaboration
A good local cohort is usually held by a university, a hospital or a national research institution, under their own governance and their own ethics approval. We do not hold those datasets and we do not speak for the people who do. What we can do is convene the right group around a question and support the science once a collaboration is agreed.
Send us the research question and the population you need, not a data request. We keep a running picture of who in the local ecosystem works on what.
Where several groups are circling the same question, we bring them together, because a consortium is far more likely to clear a data access committee than a lone request.
Where we know the institution holding a relevant cohort, we introduce you directly and step back. The conversation, and the decision, belong to them.
Once a collaboration is agreed, we do what we are actually for: genotyping and assays, bioinformatics, sample logistics, ethics and grant documentation, and project support.
What we are not offering. We do not hold, broker, resell or grant access to any dataset we do not own, and nothing on this page should be read as an offer of access to a third party's data. Where we have processed samples for another organisation, we acted as a laboratory only and claim no rights over the resulting data. Access to any institutional cohort is decided by the institution that holds it and by its ethics committee, never by us.
Prima Nexus Joint Research Program
The browser shows what our Malaysian data says about one marker. JRP 1.0 helps you generate your own genomic data now, with in-kind funding for genomic services and scientific guidance, for ongoing or future projects. JRP 2.0 will open research around this cohort, and JRP 3.0 takes selected work further, towards publication.
JRP 1.0 is open now. JRP 2.0 is coming soon. Researchers in JRP 1.0 who work on human samples may be given priority access to JRP 2.0, subject to Prima Nexus approval.