Roughly 30 trillion cells. That's where recent estimates place the total number of cells in the human body (1). It’s certainly an overwhelming number. For some perspective, current estimates have the number of stars in the Milky Way galaxy at 100–400 billion (2). So let’s narrow it down a bit.
How many cells are in the human brain? Published work has the number of neurons at 86 billion, and this number excludes other, non-neuronal cells (3). Research on the human heart states that cardiomyocytes alone account for about 2 billion cells (4). Clearly, there are a lot of cells at work as we go about our days. And no wonder, there’s a lot going on. These cells keep us going through development, injury, disease, stress, and more.
But which of those cells hold the key to understanding mechanisms behind disease onset and progression? Behind treatment success or failure? Understanding biology at a single cell level means unlocking a wealth of information into our most complicated questions about human health—and large-scale studies allow you to dive deep enough to find those answers. Read on to see how researchers are putting this to use across a wide range of applications. Plus, learn how single cell technology is rapidly advancing to streamline workflows and accelerate results for ambitious projects.
Large-scale single cell studies magnify impact
While single cell profiling, at its core, reveals sample heterogeneity that would otherwise be missed with bulk techniques, many projects benefit even further by scaling up, providing the ability to accelerate research, increase impact, and improve statistical power.
Benefits of scaling up with scRNA-seq
In general, best practices for more complex samples call for profiling a larger number of cells. For example, very heterogeneous samples like those from the tumor microenvironment (TME) or samples that include fragile cells that are typically more difficult to maintain through sample preparation require larger cell numbers.
Increasing the number of cells and samples per experiment also boosts statistical power, improving confidence in results and enabling effective comparisons in large cohort studies.
Additionally, detection of rare or small subpopulations requires sequencing a large number of individual cells to start with. Large-scale methods enable deeper profiling of samples, meaning there is less of a need to enrich for a specific cell type of interest, allowing sequencing of the whole sample at a depth sufficient to yield the necessary data without introducing bias into the project.
Identification of rare cells and the discovery of novel cell types
Large-scale studies can help find rare cells of incredible consequence. Rare or small subpopulations might prove to be the missing piece researchers have been trying to find for years, revealing early signs of disease or transitional states in disease progression.
For example, there is only one CFTR+ pulmonary ionocyte present for every 200 human lung epithelial cells, yet this rare cell type may have an important role in mediating the progression of cystic fibrosis (5). Dysfunction in the Enteric Nervous System (ENS) is linked to both digestive disorders and the progression of neurological diseases, but just one enteric neuron is found in every 300 cells in the human colon (6). Recent investigations into T-cell therapies and possible latent virus reactivation identified an even rarer cell population: CAR T cells that occur once for every 10,000 cells in the infusion product. Notable for their high human herpesvirus 6 transcriptional activity, these cells may contribute to reactivation of HHV-6 virus in those undergoing therapy (7).
Generation of disease and cell atlases
Detailed, accurate cell atlases provide a comprehensive reference for all manner of studies in health and disease, whether you’re tracing expected changes in development or unpredictable disease progression. To empower research into how our bodies’ defenses naturally change over time, researchers at the Allen Institute for Immunology generated a 16 million single cell atlas of the healthy human immune system, resolving rare yet functionally important peripheral immune cell subtypes (8). Now, this incredible resource is helping to uncover cellular mechanisms that keep us healthy and those at work in immune dysregulation.
In the quest to understand dysfunctional immune response in COVID-19 patients, researchers in another study profiled 1.46M cells from nearly 300 samples, resulting in a thorough map of the immune landscape that revealed diverse epithelial and immune cell types, dramatic transcriptomic changes, and avenues for the development of therapeutic strategies (9).
Biomarker discovery and validation
Whether it's a disease-associated gene mutation or a protein level indicative of disease progression, the importance of biomarkers cannot be overstated. And methods that enable accelerated discovery and validation of biomarkers provide researchers with critical tools to better understand disease mechanisms, advance efforts in disease detection, and improve treatment development.
In one study, scientists at the University of Pennsylvania analyzed over one million cells from 60 healthy donors, 36 recovered donors, and 125 hospitalized COVID-19 patients in their efforts to understand how immune dysregulation contributes to COVID-19 severity (10). By integrating PBMC immune profiling data with clinical metadata (including disease severity), they were able to identify three immunotypes associated with clinical outcomes.
Target identification and validation
In the drug discovery pipeline, target identification and validation are critical early steps that set the stage for downstream success. High-throughput studies can help accelerate this process, enabling larger screens that can uncover novel insights into underlying disease mechanisms, including cell signaling pathways and regulatory networks.
In the fight against cancer, tumor heterogeneity and variation in treatment response make for a challenging enemy, with high heterogeneity known to impede treatment in certain cancers (11). A better understanding of immune checkpoint inhibitor resistance would certainly go a long way to identifying novel targets that could lead to the development of more successful treatments. To that end, in recent work, scientists performed multimodal profiling of over 200,000 cells coupled with large-scale CRISPR screens (over 750 perturbations) to yield novel mechanisms influencing resistance (12). In looking more broadly at the challenges facing drug development pipelines, the capacity to perform million-cell studies with multiomic readouts shows great promise in removing bottlenecks.
So many cells, so little time: Overcoming the challenges of scaling up
As you look to more ambitious studies and move to build single cell libraries at scale, it can feel a little daunting. Depending on the assay, processing a large amount of cells and/or samples can be laborious and may also be a time-sensitive consideration for some single cell methods. (And let’s be honest, your time is an incredibly valuable resource to keep in mind when planning your experiments.) Furthermore, your research demands that you retain high data quality at every scale. Our Flex family of assays takes these challenges head-on, with workflows that let you easily scale up without compromise.
Scale up on your schedule, with more sample types
Quick and easy fixation protocols with the Flex assay empower single cell studies with fresh, frozen, and fixed cells (even fixed whole blood and FFPE), and at incredible scale. These robust protocols also alleviate the urgency of sample processing and enable sample storage (up to 1 year) without loss of data quality. This means samples can be stored, brought to a central location (if necessary), and batched at a later time, making it ideal for multi-site, large-scale, and longitudinal studies.
Maintain high-quality data for large-scale single cell
Transformative discoveries are driven by precise, accurate data that you can trust. Flex’s optimized probe-based chemistry means you can count on highly sensitive protein-coding gene coverage for human or mouse samples, even from samples with damaged RNA. Multiomic options further enable comprehensive analysis with capture of CRISPR guides, cell surface protein, or intracellular protein.
As part of the Chromium single cell platform, Flex benefits from the high cell capture rate (up to 80%) and exceptional reproducibility that comes with automated partitioning of millions of cells in just minutes. These assays demonstrate minimal technical variability and high reproducibility across a variety of technical replicates, with an R2 of 0.97 across runs, users, and timepoints. Truly efficient workflows empower you to scale up without sacrificing performance.
Lead the way with Apex for large-scale studies
Our latest assay, Flex Apex, builds on these capabilities with incredible advances in sample processing and workflow logistics that are ideal for large-scale scRNA-seq. The key? Plate-based multiplexing that unlocks game-changing scale and enables profiling of up to 384 samples or 100 million cells per week.
“The new 384-plex Flex assay [Apex] from 10x Genomics is a game changer— enabling the profiling of millions of cells at a fraction of the cost. By fixing cells for batching and ensuring compatibility with liquid-handling automation, we can now explore functional immune responses with unprecedented depth and precision.”
Peter Skene, PhD, Senior Director, High Resolution Immunology at the Allen Institute
This convenient 96-well format streamlines workflows with automation compatibility and reduced sample handling, while also providing the ability to run partial plates and scale at your pace. Need to run pilot studies first? Not to worry. On-demand reagent flexibility allows you to run even smaller studies without waste—use only the reagents you need, when you need them.
And this flexibility extends even further, as experiments can be designed to either maximize the number of samples, increase the cell count within a sample, or use a combination of both strategies. We invite you to explore these options in detail on pages 25 and 26 of the User Guide.
Plate-based multiplexing accelerates both pooled and arrayed CRISPR screens, facilitating large-scale functional genomics screens. Any work that relies on archival tissue (e.g., retrospective studies) can also be easily scaled up: a faster, heat-based sample preparation protocol for FFPE tissue sections in plate format enables higher throughput (up to 96 FFPE scrolls).
Dream bigger: Start planning your next high-impact study
T cells that mediate immune response. Subpopulations of drug-resistant cells. Rare circulating tumor cells that point to metastasis. What groundbreaking details will your large-scale studies uncover? We’re excited to find out, and we’re here to answer your questions every step of the way. Check out our Experiment Builder to start planning, or contact us to speak with a specialist.
References:
- Hatton IA, et al. The human cell count and size distribution. Proc Natl Acad Sci U S A 120: e2303077120 (2023). doi: 10.1073/pnas.2303077120
- Milky Way. Wikipedia. Updated February 24, 2026. Accessed February 26, 2026. https://en.wikipedia.org/wiki/Milky_Way
- Maroso M. A quest into the human brain. Science 382: 166–167(2023). doi: 10.1126/science.adl0913
- Malliaras K, Terrovitis J. Cardiomyocyte proliferation vs progenitor cells in myocardial regeneration: The debate continues. Glob Cardiol Sci Pract 2013: 303–315 (2013). doi: 10.5339/gcsp.2013.37
- Montoro D, et al. A revised airway epithelial hierarchy includes CFTR-expressing ionocytes. Nature 560: 319–324 (2018). doi: 10.1038/s41586-018-0393-7
- Drokhlyansky E, et al. The Human and Mouse Enteric Nervous System at Single-Cell Resolution. Cell 182: 1606-1622.e23 (2020). doi: 10.1016/j.cell.2020.08.003
- Lareau CA, et al. Latent human herpesvirus 6 is reactivated in CAR T cells. Nature 623: 608–615 (2023). doi: 10.1038/s41586-023-06704-2
- Gong Q, et al. Longitudinal Multi-omic Immune Profiling Reveals Age-Related Immune Cell Dynamics in Healthy Adults. bioRxiv (2024). doi: 10.1101/2024.09.10.612119
- Ren X, et al. COVID-19 immune features revealed by a large-scale single-cell transcriptome atlas. Cell 184: 1895–1913e19 (2021). doi: 10.1016/j.cell.2021.01.053
- Mathew D, et al. Deep immune profiling of COVID-19 patients reveals distinct immunotypes with therapeutic implications. Science 369: eabc8511 (2020). doi: 10.1126/science.abc8511
- Guillen KP, et al. A breast cancer patient-derived xenograft and organoid platform for drug discovery and precision oncology. bioRxiv (2021). doi: 10.1101/2021.02.28.433268
- Frangieh CJ, et al. Multimodal pooled Perturb-CITE-seq screens in patient models define mechanisms of cancer immune evasion. Nat Genet 53: 332–341 (2021). doi: 10.1038/s41588-021-00779-1
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