Axiom GeneTitan & Illumina Infinium · Custom Array Design

Dense, reproducible genotyping at population scale.

Genome-wide association studies, marker-assisted selection, genetic diversity panels, and quality-control genotyping all need dense, reproducible, cost-effective SNP data. Arrays deliver exactly that: fixed marker sets, >99% call rates, and per-sample economics that sequencing cannot match at scale.

Plan Your Project → Learn the Basics
Axiom GeneTitan + Illumina
platforms
Custom arrays
from 1,500 to 2.6M markers
Human, plant & animal
catalog arrays
Full GWAS
analysis pipeline
About the Service

SNP Genotyping at Nucleome Informatics

Nucleome Informatics offers SNP genotyping on the two dominant array platforms:

Design your own array from your own data:

  • Genotype calls (call rate, per-SNP and per-sample QC metrics) in standard formats (PLINK, VCF, Axiom/Illumina reports)
  • Full QC pipeline: sample call rate, SNP call rate, heterozygosity, sex concordance, relatedness/duplicates, Hardy–Weinberg screening
  • Population structure analysis (PCA, ADMIXTURE-style clustering)
  • Complete GWAS analysis: association testing, Manhattan/QQ plots, multiple-testing correction, annotation of significant loci
  • Imputation to reference panels (TOPMed, HRC/1000 Genomes for human; species-appropriate panels elsewhere)

Custom array development

  • Axiom myDesign: submit your SNPs (from sequencing, WGS, or databases); Thermo Fisher's design pipeline selects and places markers from 1,500 (384HT format, minimum order 1,920 samples) up to 2.6 million markers (GW plate formats, minimum 480 samples). Design turnaround is typically as few as 6 weeks after SNP lockdown.
  • Population-optimised GWAS modules: imputation-based SNP selection enriches the array with markers informative for your population — critical for Indian and South Asian cohorts under-represented in global arrays.
  • Multi-species support: custom arrays for any organism with sequence data — crops, livestock, fish, pathogens, and wildlife.
Learning Path

From first principles to expert-level analysis

New here? Start with Foundations. Planning a study or reviewing results? Jump to Practitioner or Expert. Each level builds on the one before it, so you can read this page as a short course or dip in where you need to.

Start here if you are new to this service — six ideas that explain what it is and why it matters.

LEVEL 1

What is SNP genotyping?

Reading the identity of single-letter variants (SNPs) at thousands to millions of positions across the genome — a fixed, reproducible snapshot of genetic variation.

LEVEL 1

Why use arrays instead of sequencing?

Arrays are cheaper per sample at fixed marker sets, produce highly reproducible calls, and are simpler to analyse. Sequencing discovers new variants; arrays type known ones at scale. Large GWAS and breeding programmes overwhelmingly use arrays.

LEVEL 1

What is a GWAS?

A genome-wide association study: testing each SNP for statistical association with a trait (disease, yield, milk production, growth) across hundreds or thousands of individuals.

LEVEL 1

What is a custom array?

An array designed for your project: you provide SNPs (from your own sequencing data or databases), and the manufacturer places them on a purpose-built array. Axiom myDesign supports 1,500–2.6M markers.

LEVEL 1

Which species are supported?

Human, plus a wide range of plants and animals through catalog arrays, and essentially any organism with sequence data through custom design.

LEVEL 1

What do I get?

Genotype calls, QC reports, population structure analysis, and — for GWAS projects — association results with publication-ready figures.

For scientists planning a project or reading a report: how each step works and how it can mislead.

LEVEL 2

Platform selection

Axiom excels at agrigenomics throughput and flexible custom design; Illumina's GSA dominates human cohort genotyping with strong imputation support. We recommend based on species, sample number, and marker requirements.

LEVEL 2

Array design (custom projects)

You supply SNPs; the design pipeline scores each marker for convertibility and places the best set. Axiom design typically completes in as few as 6 weeks after SNP lockdown. We manage the design submission and review convertibility reports with you.

LEVEL 2

Laboratory workflow

DNA is whole-genome amplified, fragmented, hybridised to the array, and stained/imaged (GeneTitan for Axiom; iScan/NextSeq for Infinium). Automated calling produces genotype calls with per-marker quality scores.

LEVEL 2

Quality control

Standard GWAS QC filters: sample call rate (typically ≥98%), SNP call rate, heterozygosity outliers, sex discordance, duplicate/relatedness checks, and Hardy–Weinberg equilibrium screening in controls.

LEVEL 2

Imputation

Genotypes are phased and imputed to dense reference panels (TOPMed/HRC/1000 Genomes for human), expanding effective marker density to millions and enabling cross-cohort meta-analysis.

LEVEL 2

Association testing

Linear/logistic regression with covariates for human traits; mixed linear models (GEMMA, GCTA, BOLT-LMM, SAIGE) correct for relatedness and structure; plant breeding uses GAPIT/TASSEL/FarmCPU with population structure (Q) and kinship (K) models.

For study design: the decisions that determine whether the data answers your question.

LEVEL 3

Power and sample size

GWAS power depends on allele frequency, effect size, and sample number. We run power calculations before you commit samples — underpowered GWAS produce false negatives and irreproducible hits.

LEVEL 3

The genome-wide significance threshold

The conventional 5×10⁻⁸ threshold for human GWAS reflects ~1 million independent tests; species-specific thresholds depend on LD structure. QQ-plot inflation (genomic control λ) is monitored and reported.

LEVEL 3

Population structure in Indian cohorts

India's population structure is complex and under-represented in reference panels. Our imputation-based Axiom module design enriches arrays for South Asian variation — a concrete advantage for Indian GWAS.

LEVEL 3

Post-GWAS analysis

Significant loci are annotated (VEP), fine-mapped, and integrated with eQTL/functional data; candidate gene prioritisation and pathway enrichment complete the analysis.

LEVEL 3

Breeding programme integration

For marker-assisted selection, we convert GWAS hits into low-density diagnostic marker sets — often via a second, small custom array — closing the loop from discovery to application.

LEVEL 3

Data submission

GWAS summary statistics are formatted for GWAS Catalog/dbGaP/SRA submission where applicable.

SNP
single nucleotide polymorphism; a single-letter genetic variant.
GWAS
genome-wide association study.
Imputation
inferring untyped variants from typed neighbours using reference panels.
LD (linkage disequilibrium)
non-random association of variants; determines GWAS resolution.
Kinship matrix
the genetic relatedness matrix used in mixed-model association.
PRS
polygenic risk score; a weighted sum of risk alleles predicting trait liability.
The Science

How it works, in two figures

The Axiom myDesign system (1,500–2.6M markers, >10M genotype-tested database markers, ~6-week design) is documented in Thermo Fisher technical materials; GWAS best practices (mixed models, QC thresholds, imputation) are established in the statistical genetics literature. See references below.

Figure 1 Array vs sequencing economics. schematic
Sequencing (discovery) Arrays (scale) Finds novel variants Higher cost per sample Complex analysis Fixed marker sets, >99% call rates Economical per sample at scale Custom design from your data
Figure 1 | Array vs sequencing economics. (Illustrative schematic, not sample data.)
Figure 2 GWAS workflow. schematic
DNA Array hybridisation GeneTitan / iScan calling QC (call rate, HWE, sex) Imputation (TOPMed / HRC) Mixed-model GWAS & annotation
Figure 2 | GWAS workflow. (Illustrative schematic, not sample data.)
Technology Highlights

Built for the questions you are asking

The platforms, pipelines and standards behind this service.

Axiom GeneTitan instrument

Fully automated imaging and calling for 96- or 384-sample plate formats — the throughput engine for large cohorts and breeding programmes.

Axiom myDesign custom arrays

From 1,500 markers (384HT, min. 1,920 samples) to 2.6 million markers (GW plates, min. 480 samples), designed from your SNP list with the Axiom Genomic Database's >10 million genotype-tested markers.

Illumina Infinium and GSA

The Global Screening Array family (~650K variants with pharmacogenomic and clinical content) plus Infinium custom and semi-custom options (iSelect-style designs) for human and non-human species.

Agrigenomics catalog arrays

Established catalog arrays for major crops and livestock (e.g. bovine, porcine, ovine, chicken, maize, wheat, rice families) — marker counts and content vary by species; we match the array to your breeding or diversity question.

Full GWAS pipeline

QC → imputation (Beagle/Minimac; TOPMed/HRC/1000G for human) → population structure (PCA/ADMIXTURE) → association (mixed models: GEMMA, GCTA, BOLT-LMM, SAIGE for human; GAPIT, TASSEL, FarmCPU for plants) → annotation (VEP) → Manhattan/QQ visualisation.

Polygenic risk scores

PRS construction and validation from GWAS summary statistics where sample size supports it — with honest power caveats. ---

Scope Note

What this service does and does not cover

Scope note. Arrays type pre-selected markers only; variants absent from the array (and not recoverable by imputation) are not measured. Catalog array content varies by species and version — we confirm exact marker content for your project before ordering. Custom array design lead times and minimum sample orders are set by the manufacturer (Axiom: as few as 6 weeks after SNP lockdown; 384HT minimum 1,920 samples; GW plates minimum 480 samples). GWAS results are associations, not causal proof; functional validation is a separate step. ---
Why Nucleome

Service highlights

What you can expect from our team in Hyderabad.

Both major platforms

Axiom GeneTitan and Illumina Infinium under one roof — platform chosen for your project, not our inventory.

Custom array development

From 1,500 to 2.6M markers, designed from your data, with South Asian-optimised GWAS modules.

Agrigenomics depth

Catalog arrays and custom design for crops, livestock, and aquaculture species.

Full GWAS analysis

From raw calls to Manhattan plots and candidate genes — analysis included.

Indian population expertise

Imputation-based marker selection for South Asian cohorts.

Breeding-to-discovery pipeline

From diversity panels to diagnostic marker sets for selection programmes. ---

Questions

Frequently asked, in plain language

From the basics to the finer points of design and interpretation.

basicHow many SNPs do I need for a GWAS?
For human GWAS, arrays with ~300K–700K well-distributed markers, imputed to millions, are standard. For species with different LD structure, marker density requirements vary — we advise per species.
basicWhat sample do you need?
Typically 50–200 ng DNA per sample at standard purity. We provide submission guidelines and QC every batch.
basicCan you design an array for my crop/livestock species?
Yes — Axiom myDesign supports custom arrays for any organism with sequence data, from 1,500 to 2.6M markers.
intermediateAxiom or Illumina — which platform?
Axiom offers flexible custom design and high-throughput agrigenomics workflows; Illumina's GSA is the standard for human cohorts with strong imputation support. We recommend based on species, scale, and marker needs.
intermediateHow long does custom array design take?
Axiom design typically completes in as few as 6 weeks after SNP lockdown. Minimum sample orders apply (1,920 samples for 384HT format; 480 for GW plates).
intermediateWhat QC do you apply?
Sample and SNP call rates, heterozygosity, sex concordance, duplicates/relatedness, and HWE screening — with all thresholds documented and reported.
advancedCan you optimise an array for Indian populations?
Yes — imputation-based SNP selection enriches the design with markers informative for South Asian variation, improving imputation accuracy and GWAS power for Indian cohorts.
advancedWhich association models do you use?
Human: GEMMA, GCTA, BOLT-LMM, SAIGE (binary traits with case–control imbalance). Plants: GAPIT, TASSEL, FarmCPU with Q+K models. Model choice is documented per project.
advancedCan you build polygenic risk scores from my GWAS?
Yes, where sample size and replication data support it — with honest power caveats and out-of-sample validation.
advancedCan GWAS hits become breeding markers?
Yes — we convert significant loci into low-density diagnostic marker sets, often via a small second custom array for routine selection screening.
References

Key literature & resources

Selected sources behind the methods and reference values on this page. Figures labelled "schematic" or "illustrative" are generated for this page, not client data.

  1. Thermo Fisher Scientific. Axiom myDesign Genotyping Array solution — design guide and technical specifications (1,500–2.6M markers; 384HT and GW formats; Axiom Genomic Database). Thermo Fisher documentation, 2023–2025.
  2. Thermo Fisher Scientific. Axiom Analysis Suite and GeneTitan instrument documentation. Thermo Fisher, 2024.
  3. Illumina. Infinium Global Screening Array and Infinium iSelect product documentation. Illumina, 2023–2025.
  4. Yang J, et al. GCTA: a tool for genome-wide complex trait analysis. American Journal of Human Genetics. 2011;88(1):76–82.
  5. Loh PR, et al. Efficient Bayesian mixed-model analysis increases association power in large cohorts (BOLT-LMM). Nature Genetics. 2015;47(3):284–290.
  6. Bradbury PJ, et al. TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics. 2007;23(2633–2635). (GAPIT: Lipka AE, et al. Bioinformatics. 2012;28(18):2397–2399. FarmCPU: Liu X, et al. PLoS Genetics. 2016;12(1):e1005764.)
  7. Zhou W, et al. Efficiently controlling for case-control imbalance when testing for interaction in GWAS (SAIGE). Nature Genetics. 2018;50(9):1285–1291.
  8. Das S, et al. Next-generation genotype imputation service and methods (Michigan Imputation Server; TOPMed/HRC panels). Nature Genetics. 2016;48(10):1284–1287.