- [Resource Hub](/) - [Blog](/?resource-type=blog-post#library) - One core, every assay, one Singulator footprint Blog · 7 min read · Multi-Omics Cores # One core, every assay, one Singulator footprint scRNA-seq one day, snRNA-seq the next, ATAC-seq, CITE-seq, and a FACS sort in the same week. A shared multi-omics core can feed all of them from a single automated sample-prep step, held to one standard of quality. Key takeaways - One footprint feeds five different assays. The Yale Center for Genome Analysis (YCGA) runs scRNA-seq, snRNA-seq, ATAC-seq, CITE-seq, and FACS off a single Singulator footprint, so a shared core serves the whole menu from one bench. - That is possible because one automated platform turns fresh, frozen, OCT, and FFPE tissue into either cells or nuclei on the same software-controlled workflow, across a broad range of validated tissue types. - Running every assay off one prep means a single standard of quality across the whole menu — the same timing, force, temperature, and chemistry on every run, whoever is at the bench. - The quality is measurable. Head-to-head nuclei data show roughly 100% structurally intact nuclei with the lowest sample-to-sample variability of any compared method, and published multi-omics work resolved cell-type detail that one modality alone could not. A shared single-cell core is not one workflow. It is a dozen, running side by side. One PI wants a cell suspension off fresh tumor for scRNA-seq. The next needs nuclei from frozen cortex because the cells will not survive dissociation. A third is building a CITE-seq panel, a fourth wants a clean FACS sort, and a fifth has been waiting months for the core to say yes to an ATAC-seq request. Each of those assays has its own downstream chemistry. The question that decides whether the core can serve all of them is the same in every case: can you put a consistent, high-quality input in front of each one, from whatever tissue walks in? That is a real constraint, and it usually pushes a core toward a wall of methods. A rotor-stator dissociator for cells. A sucrose-gradient or column protocol for nuclei. A separate, manual, fume-hood path for anything archival. Each method has its own SOP, its own failure modes, and its own dependence on which person ran it. The breadth a multi-omics core is supposed to offer turns into a maintenance burden, and the assays at the edge of the menu — the ATAC-seq request, the precious biopsy, the FFPE block — are the ones that quietly get declined. ## What one footprint actually looks like There is a more direct way to build the front end, and it is already in use at the institutional level. A core can run a single automated sample-prep instrument and feed every assay on its menu from it. A customer reference The Yale Center for Genome Analysis runs the Singulator as the sample-preparation platform feeding its single-cell and multi-omics services — one footprint supporting: scRNA-seq snRNA-seq ATAC-seq CITE-seq FACS Source: the Yale Center for Genome Analysis, a Singulator customer (referenced with permission). Stated as a customer reference, not an endorsement. Read that list as a workflow diagram. It is the same physical prep step branching into five different downstream methods. The core does not maintain five front ends. It maintains one, and that one produces the input each assay needs: cells where the protocol wants cells, nuclei where the tissue or the chemistry demands nuclei. The breadth a multi-omics core offers does not have to mean a separate front end per assay. One automated sample-prep step turns diverse intake into the cells or nuclei each downstream method requires — the structure the Yale Center for Genome Analysis runs in practice. ## Why one prep can serve assays that want opposite things The reason one instrument can stand in front of five methods is that those methods do not actually need five different prep philosophies. They need two outputs — cells or nuclei — produced consistently. The Singulator makes both on one software-controlled workflow, and it does it across the range of tissue a core cannot predict from one week to the next. Cells ### scRNA-seq, CITE-seq, FACS A clean single-cell suspension off fresh tissue, with cold, gentle chemistry that preserves fragile and rare populations for sorting and surface-marker work. Nuclei ### snRNA-seq, ATAC-seq High-integrity nuclei from frozen, OCT, or archival tissue, where the cells will not survive dissociation and the assay reads chromatin or nuclear RNA. Any tissue ### The whole intake queue Fresh, frozen, OCT, and FFPE on one platform family, down to inputs as small as 2 mg, so the core says yes to the request instead of declining the hard ones. This is the point where breadth and standardization stop competing. With a wall of manual methods, every new assay you add is another SOP to maintain and another way for the result to track the operator instead of the sample. With one automated step, adding an assay downstream does not add a prep to babysit. The front end is already consistent, so the core can extend its menu without diluting its quality. That is the through-line of this whole series: the variability that usually drifts with whoever is at the bench moves into the instrument, where it holds still. The [variable middle](/resources/single-cell-sample-prep-most-variable-step/) becomes the steady one, for every assay at once. Add an assay downstream and you do not add a prep to babysit. The front end is already consistent. ## The quality holds, and it is measurable A capability list is only worth as much as the data behind it. The reason a core can run snRNA-seq and ATAC-seq off the same nuclei prep, and trust the result, is that the nuclei come out intact and clean enough for both. That has been measured directly, by an independent group, against the alternatives a core would otherwise use. Nuclei integrity, measured head-to-head In a published comparison of nuclei isolation methods on frozen mouse cortex, the Singulator-prepared nuclei held up where the common alternatives did not. ~100% / ~85% / ~35% Structurally intact nuclei: the Singulator versus a sucrose-gradient prep versus a column kit. The Singulator also showed the lowest sample-to-sample variability of any method compared. <0.5% Mitochondrial reads, with ambient contamination among the lowest of the methods tested. Cleaner inputs mean less to scrub before the biology is readable. Integrity and low contamination are exactly what an ATAC-seq or snRNA-seq core cares about, because damaged nuclei and ambient signal are what a bioinformatician spends downstream effort trying to rescue. Setting that quality upstream, on the same prep that also feeds the RNA assays, is what makes one footprint credible rather than just convenient (Kersey et al., 2026; Singulator 100, frozen mouse cortex). The multi-omics case has independent published support too. In work from a single-cell genomics lab (Haviv et al., 2024, Nature Biotechnology ), Singulator-derived single-nucleus RNA-seq identified the same major cell types as matched spatial data and resolved immune-cell differences that the spatial modality alone could not. That is the multi-omics promise stated as a result: two methods, fed from the same prep, each contributing what the other misses, and the combined picture sharper than either one. None of this requires the core to fabricate a number or take a vendor's word for it. The integrity data is third-party and peer-reviewed. The multi-omics result is published. The capability list is a working core's own account of how it runs. Together they answer the only question that matters when a director is deciding whether one instrument can really sit in front of the whole menu: does the quality hold across assays, or does consolidating the front end cost you something downstream? The evidence says it holds. ## What this changes for the core The practical shift is in what the core can offer without growing its method count. Instead of one front end per assay, with the training, drift, and maintenance each one carries, the core runs a single automated prep and lets the downstream methods branch off it. New requests at the edge of the menu stop being special cases that need a new protocol: the ATAC-seq the core kept declining, the precious biopsy, the archival block. Each becomes one more thing the existing front end already handles. It also changes who carries the standard. When every assay traces back to one software-controlled step, the core's reputation does not rest on which technician happened to run the prep that week. It rests on the instrument, which runs the same way on every shift. That is the difference between a core that is as good as its current staff and one that is as good as its method, made concrete across five assays instead of one. The same versatility argument plays out sample type by sample type in the case for [one platform across every sample your core sees](/resources/one-platform-every-sample-type/), and the operator-consistency question is answered directly in [whether one instrument can really standardize prep across every operator](/resources/standardize-single-cell-prep-one-instrument/). The intake queue still changes every day. A multi-omics core would not want it any other way. What does not have to change with it is the quality of the input feeding every assay on the menu. Your intake queue changes every day. Your prep quality shouldn't. For research use only. On this page - [One footprint](#one-footprint) - [Cells or nuclei](#cells-or-nuclei) - [The quality holds](#quality-holds) - [What it changes](#what-changes) ### Weighing whether one front end could serve every assay on your menu? [Talk to a Specialist](https://precisioncellsystems.com/request-a-quote/) ## Have a tissue, nuclei, or FFPE workflow to solve? [Talk to a Specialist](https://precisioncellsystems.com/request-a-quote/) [Back to all resources](/#library) ## Similar resources [Blog](/resources/fully-automated-nuclei-isolation-fresh-frozen-ffpe/) Singulator 100 Singulator 200 Singulator 200+ 2026 ### What "fully automated nuclei isolation" actually means — across fresh, frozen, and FFPE One software-controlled workflow from tissue to sequencing-ready nuclei, whatever you start with. Here's what "fully automated" rules out — and the hardest case that proves it. [Read Blog](/resources/fully-automated-nuclei-isolation-fresh-frozen-ffpe/) [Blog](/resources/lowest-tissue-input-nuclei-prep-platform/) Singulator 100 Singulator 200 Singulator 200+ 2026 ### The Lowest Tissue Input for Nuclei Prep — and Why It Matters More Than Throughput Why the minimum input a platform can run — 2 mg fresh/frozen, a 50 µm FFPE curl on the Singulator — is the most consequential spec for labs with scarce or irreplaceable samples, and matters more than throughput. [Read Blog](/resources/lowest-tissue-input-nuclei-prep-platform/) [Blog](/resources/software-controlled-vs-software-locked-protocol-fidelity/) Singulator 100 Singulator 200 Singulator 200+ 2026 ### Software-controlled, not software-locked: why the wording matters for protocol fidelity Why “software-controlled” (not “software-locked”) is the accurate description of Singulator protocol fidelity — and what that distinction means for core facilities and S10 grant reproducibility. [Read Blog](/resources/software-controlled-vs-software-locked-protocol-fidelity/) [App Note](/resources/singulator-200-plant-nuclei-isolation/) Singulator 100 Singulator 200 Singulator 200+ 2026 ### Automated Nuclei Isolation from Diverse Plant Tissues Using the Singulator 200 A University of Minnesota Genomics Center study validating the Singulator 200 for automated, standardized single-nucleus isolation across diverse plant species — pennycress, soybean, corn, and tobacco — from leaf, root, and flower tissue using just 50–150 mg of input. Automating the mechanical disruption and filtration steps standardizes an otherwise tedious, operator-dependent workflow; frozen leaf tissue yielded nuclei comparable to fresh, validating the method for stored and field-collected samples and producing preparations suitable for downstream 10x Genomics snRNA-seq. For Research Use Only. [View App Note](/resources/singulator-200-plant-nuclei-isolation/) [Ebook](/resources/tissue-dissociation-protocol-guide/) Singulator 100 Singulator 200 Singulator 200+ 2026 ### Tissue Dissociation Guide The most comprehensive tissue dissociation reference available. Interactive protocols for single-cell isolation and nuclei extraction across 57+ tissue types with community and Singulator-optimized methods. [Read Ebook](/resources/tissue-dissociation-protocol-guide/) [Field Guide](/resources/core-director-standardization-field-guide/) Singulator 200+ Singulator 200 2026 ### The Core Director's Standardization Field Guide A practical playbook for delivering one standard of single-cell sample prep across every operator, every shift, and every sample type your core takes in. Your intake queue changes every day. Your prep quality shouldn't. [Read Field Guide](/resources/core-director-standardization-field-guide/) [Blog](/resources/low-input-single-cell-prep-2-mg/) Singulator 200+ Singulator 200 2026 ### The smallest sample in your core: standardized single-cell prep down to 2 mg When the sample is a needle biopsy, a sorted population, or a few milligrams of rare tissue, there is no second curl if the prep fails. Here is what it takes to turn inputs that small into sequencing-ready cells or nuclei without grinding the material away, and how to make it a standard your whole core can run. [Read Blog](/resources/low-input-single-cell-prep-2-mg/) [Blog](/resources/one-platform-every-sample-type/) Singulator 200+ Singulator 200 2026 ### One platform for every sample your core sees: fresh, frozen, FFPE, cells or nuclei Fresh, frozen, and FFPE tissue. Cells or nuclei. A core's intake range is the reason most labs end up running a method for each problem. One automated sample-prep instrument holds the whole range to a single standard of quality. [Read Blog](/resources/one-platform-every-sample-type/) [Blog](/resources/s10-grant-standardized-single-cell-prep/) Singulator 200+ 2026 ### Make the S10 case write itself An S10 reviewer scores documented need, utilization across an NIH-funded user base, and whether the resource will hold up. Standardized, auditable single-cell sample prep maps to all three, and gives a shared core the run logs and reproducibility data to put in front of a study section. [Read Blog](/resources/s10-grant-standardized-single-cell-prep/) [Blog](/resources/single-cell-sample-prep-most-variable-step/) Singulator 200+ 2026 ### Your intake queue changes every day. Your prep quality shouldn't. A shared core takes in different tissue from different labs every shift. The one step that should hold steady is the one that drifts most with whoever is at the bench. It does not have to. [Read Blog](/resources/single-cell-sample-prep-most-variable-step/) [Blog](/resources/standardize-single-cell-prep-one-instrument/) Singulator 200+ 2026 ### Will one instrument really standardize prep across every operator you have? Two questions come up in every core that weighs this: our senior tech already gets clean prep, and won't we get locked into one vendor's protocols. Both are fair. Here is the honest answer to each. [Read Blog](/resources/standardize-single-cell-prep-one-instrument/) [Field Guide](/resources/brain-tissue-complexity-myelin-lipids-neuronal-nuclei/) Singulator 200+ 2026 ### Overcoming Brain Tissue Complexity: Myelin, Lipids, and Fragile Neuronal Nuclei Brain FFPE tissue creates unique nuclei isolation challenges. Myelin debris, lipid contamination, and fragile neuronal nuclei require controlled automated processing to preserve cell-type diversity for single-nucleus sequencing. [Read Field Guide](/resources/brain-tissue-complexity-myelin-lipids-neuronal-nuclei/)