One 96-well platform for chromatin, DNA, RNA, and protein. Same prep for every layer — so your integration model learns biology, not batch effects.
Four matched-sample study patterns where one prep platform replaces three — and your integration model sees biology instead of instrument noise.
Matched-sample multi-omics
The same specimen goes to ChIP-seq, RNA-seq, and proteomics — three instruments, three protocols, three operators. Your integration model can't tell biology from the batch effect that introduces.
Column-level programming runs chromatin shearing, RNA fragmentation, and protein extraction on a single 96-well plate, one run. The matched sample stays matched — harmonized at the source, before any chemistry.
Archival multi-omics
Archival blocks and frozen specimens run on separate prep tracks — and block-age variability stacks on top of cross-platform noise before integration even starts.
One platform processes matched FFPE and frozen tissue across chromatin, DNA, RNA, and protein. MultiomicsTracks96 (2024) is the published reference workflow — 8-dimensional omics from matched archival and frozen samples.
Consortium standardization
A multi-site consortium study integrates only as well as its least-harmonized site. Every member lab running a different prep platform builds cross-site batch effects into the shared dataset.
One sample-prep platform, one parameter framework, every site. Run logs and processing parameters export for FAIR-compliant data sharing — the documentation trail NIH Data Management & Sharing submissions expect.
Longitudinal cohorts
Over a five-year cohort, your downstream mass spec and sequencer will be upgraded. Every instrument change introduces a batch effect that threatens the longitudinal interpretability of the whole study.
PIXUL stays constant as the upstream sample-prep layer while downstream platforms evolve. Parameter-locked runs documented in run logs — a longitudinal anchor that holds the cohort together across instrument generations.
Your integration model finds the strongest signal in the data. Prep each omics layer on a different instrument — and the strongest signal becomes the instruments, not the biology.
Column-level programming runs different applications in different columns of the same plate — chromatin in one, RNA in the next, protein in the next. Different programs, same run. The architecture is built for three-on-one-plate multi-omics.
Every omics layer prepped on the same instrument, the same parameter framework. The cross-platform batch effect that integration models can't recover from never enters the data — because the matched sample is harmonized before any chemistry happens.
Run logs and processing parameters export for FAIR-compliant data sharing and NIH Data Management & Sharing submissions. Standard polystyrene plates — non-proprietary labware, no cost that climbs as cohorts scale.
Bomsztyk et al., Nucleic Acids Research, 2019. The architecture paper — uniform acoustic energy, the same parameter framework for every application.
Read paperEvery omics layer PIXUL prepares — chromatin, DNA, RNA, and protein — validated in peer-reviewed publications across application areas. The breadth is the multi-omics proof.
Browse publicationsCell lysis, tissue homogenization, protein extraction. Probe-grade peptide IDs at high-resolution mass spec throughput. Discovery, quantitative, PTM, FFPE, antibody-based.
See proteomics workflowsFFPE, metagenomics, ChIP-seq chromatin, gDNA. Bias-free mechanical shearing on standard plates. Tight fragment-size CV across all 96 wells.
See genomics workflowsA 30-minute working call with the multi-omics applications team. Bring a matched-sample set — FFPE, frozen, cells — and see column-level programming run every omics layer on one plate, plus a walk-through of run-log export for FAIR-data submission.
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