Biology subjects

Korsunsky, I.

Publications and source records attributed to Korsunsky, I..

At least 19 recordsLinked to original sources

bioRxiv2026

Integration of large, complex single-cell datasets with Harmony2

Integrating single cell RNA-seq profiles is posing new challenges as datasets are rapidly expanding, now with over 100 million cells in the public domain. We present the latest version of the Harmony integration software, which efficiently scales to >100M cells and >1K datasets without specialized hardware. Moreover, optimizations to the underlying algorithm help prevent overintegration in biologically heterogeneous datasets. Harmony2 enables efficient, accurate integration of large, complex single-cell atlases.

bioinformatics↗

bioRxiv2025

Fibroblasts sense spatial proximity via an EGFR CREB5 axis to restore quiescent synovial lining in remission rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic inflammatory disease where the synovial lining membrane undergoes pathological changes resulting in joint destruction. In healthy joints, the synovial lining is essential for joint homeostasis, forming a selective barrier and secreting lubricating molecules, yet the mechanisms that restores homeostatic synovial lining during RA remission remains poorly understood. Here, we applied spatial transcriptomics to examine biopsies of RA patients in remission to identify a mechanism that orchestrates a phenotypic switch specifying synovial quiescent lining fibroblast differentiation. Spatial transcriptomics revealed a proximity-sensing program where at low cell-density, fibroblasts adopt proliferative and fibrotic transcriptional state characterized by expression of MKI67, COL1A2 and COL6A2, whereas at high cell-density, fibroblasts induce a quiescent lining fibroblast transcriptional program characterized by PRG4, CLU and PDPN. Mechanistically, fibroblasts sense spatial proximity through HB-EGF-EGFR signaling, which leads to phosphorylation of transcription factor CREB5. Perturbation of the EGFR-CREB5 axis abolishes fibroblast proximity-sensing and blocks synovial lining fibroblast differentiation. Conversely, EGFR activation by the ligand HB-EGF or pharmacologic activation of CREB5 is sufficient to induce synovial lining fibroblast differentiation. Together, our findings define a novel spatial proximity-sensing pathway underlying a return to homoeostatic fibroblast function during RA remission. By sensing their spatial proximity to neighboring fibroblasts, synovial fibroblasts translate these positional cues into signals that lead to restoration of normal, steady-state synovial lining membrane.

genomics↗

bioRxiv2025

An end-to-end framework for Cell DIVE multiplexed imaging and spatial immune microenvironment analysis

This paper describes an end-to-end workflow for highly multiplexed fluorescence imaging with the Cell DIVE platform, allowing simultaneous detection of 40+ markers at single-cell resolution. Combining whole-slide multiplexed imaging with a dedicated analysis pipeline provides a powerful approach to investigate immune cell interactions with stromal and vascular networks within human tissue microenvironments. With a focus on spatial investigation of human immune niches, here we provide a complete framework for tissue preparation, autofluorescence reduction, multiplex panel design and whole-slide image analysis. For complete details on the use and execution of this protocol, please refer to Korsunsky et al. (Med, 2022) [1]. HighlightsO_LIComplete workflow for Cell DIVE multiplex imaging and quantitative image analysis. C_LIO_LIHuman FFPE tissue preparation, LED-based reduction of tissue autofluorescence. C_LIO_LIAntibody panel design for 3-40 marker multiplexing, in-house antibody conjugation. C_LIO_LIQuPath and DeepCell based analysis workflows for whole-slide multi-marker images. C_LIO_LIAdaptable code templates to accelerate cell segmentation and spatial niche analysis. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/656440v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@1ef708dorg.highwire.dtl.DTLVardef@c6422dorg.highwire.dtl.DTLVardef@22d961org.highwire.dtl.DTLVardef@1ed7479_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2025

Spatial Transcriptomics Identifies Immune-Stromal Niches Associated with Cancer in Adult Dermatomyositis

Adult-onset dermatomyositis (DM) is an autoimmune inflammatory myopathy with distinct cutaneous manifestations and a strong malignancy association. Through comparative analysis with cutaneous lupus erythematosus (CLE), our integrated spatial and single-cell transcriptomics analysis revealed unique immune and stromal niches associated with DM subtypes. Unexpectedly, we found an association between cancer-associated DM skin lesions and the presence of dispersed immune infiltrates enriched with macrophages, CD8+ T cells, plasma cells, and B cells with preserved vascular architecture. In contrast, non-cancer associated DM skin exhibited dense myeloid cell infiltrates, including neutrophils, monocytes, and macrophages, with elevated expression of IL1B and CXCL10 localized near injured vascular endothelia. Cytokines produced by these myeloid infiltrates together with local tissue hypoxia triggered dramatic stromal remodeling, leading to loss of vascular-associated fibroblasts. In addition to the CXCL10+ myeloid signature, non-cancer-associated DM skin with pDC presence showed the emergence of specific cellular pairs: PD-L1-expressing mregDCs and activated Tregs expressing NFKB2 and TNF receptors. While both DM and CLE showed strong interferon signatures, DM uniquely displayed IFN-{beta} expression. Together, our study provides the first comprehensive spatial mapping of immune and stromal cells in adult-onset DM.

immunology↗

bioRxiv2025

Spatial patterning of fibroblast TGFβ signaling underlies treatment resistance in rheumatoid arthritis

Treatment-refractory rheumatoid arthritis (RA) is a major unmet need, and the mechanisms driving treatment resistance are poorly understood. To identify molecular determinants of RA non-remission, we performed spatial transcriptomic profiling on pre- and post-treatment synovial tissue biopsies from treatment naive patients who received conventional DMARDs or adalimumab for 6 months. In the baseline biopsies of non-remission patients, we identified significant expansion of fibrogenic fibroblasts marked by high expression of COMP, a fibrosis-associated extracellular matrix protein. COMPhi fibroblasts localized to perivascular niches that, unexpectedly, served as transcriptional hubs for TGF{beta} activity. We identified endothelial-derived Notch signaling as an upstream regulator of fibroblast TGF{beta} signaling via its dual role in driving TGF{beta} isoform expression and suppressing TGF{beta} receptors, generating a proximal-distal gradient of TGF{beta} activity. Further, disruption of steady-state Notch signaling in vitro enabled fibrogenic fibroblast activation. Analysis of post-treatment biopsies revealed marked expansion of COMPhi fibroblasts in non-remission RA patients, despite evidence of successful immune cell depletion, suggesting a spatiotemporal process of fibrogenic remodeling linked to treatment resistance. Collectively, our data implicates targeting of TGF{beta} signaling to prevent exuberant synovial tissue fibrosis as a potential therapeutic strategy for refractory RA.

immunology↗

bioRxiv2025

Powerful and accurate case-control analysis of spatial molecular data with deep learning-defined tissue microniches

As spatial molecular data grow in scope and resolution, there is a pressing need to identify key spatial structures associated with disease. Current approaches typically make restrictive assumptions such as representing tissue regions by local abundances of manually typed, discrete cell types, or representing samples in terms of abundances of manually called, discrete spatial structures; this risks overlooking important signals. Here we introduce variational inference-based microniche analysis (VIMA), a method that combines deep learning with principled statistics to discover associated spatial features with greater flexibility and precision. VIMA trains an ensemble of variational autoencoders to extract numerical "fingerprints" from small tissue patches that capture their biological content. It uses these fingerprints to define a large number of data-dependent "microniches" - small, potentially overlapping groups of tissue patches with highly similar biology that span multiple samples. It then meta-analyzes across the autoencoders to identify microniches whose abundance correlates with case-control status while controlling for multiple testing. We show in simulations that VIMA is well calibrated. We then apply VIMA to spatial datasets spanning three different diseases and spatial modalities: a 7-marker immunofluorescence (IF) microscopy dataset in rheumatoid arthritis (RA), a 52-marker CO-Detection by indEXing (CODEX) dataset in ulcerative colitis (UC), and a 140-gene spatial transcriptomics dataset in dementia. In each case, we recapitulate known biology and identify novel spatial features of disease that were not discoverable with current state-of-the-art methods.

genomics↗

bioRxiv2025

Accurate tiling of spatial single-cell data with Tessera

Single-cell spatial transcriptomics reveals how cells organize in healthy and diseased tissues. From these data, tissue segmentation analysis defines discrete compartments that organize cells into functional multicellular units. Existing methods for automated tissue segmentation rely on spatial smoothing to define spatially coherent regions but often blur the boundaries between adjacent tissue compartments. We describe Tessera, an algorithm that approaches tissue segmentation through a novel approach, dividing the tissue into small multicellular tiles whose edges track with natural tissue boundaries. Tessera achieves this by incorporating successful tools from edge-preserving smoothing, topological data analysis, and morphology-aware agglomerative spatial clustering. We show that Tessera identifies a range of known anatomical structures, in healthy mouse brain and human lymph nodes, and novel disease-associated niches, in human brain and in lung cancer. Tessera is a general-purpose tool that returns spatially coherent spatial structures with accurate boundaries across a range of spatial transcriptomics and proteomics technologies.

bioinformatics↗

bioRxiv2025

Wnt signaling drives stromal inflammation in inflammatory arthritis

The concept that fibroblasts are critical mediators of inflammation is an emerging paradigm. In rheumatoid arthritis (RA), they are the main producers of IL-6 as well as a host of other cytokines and chemokines. Their pathologic activation also directly causes cartilage and bone degradation. Yet, therapeutic agents specifically targeting fibroblasts are not available. Here, we find that Wnt receptors and modulators are predominantly expressed in stromal populations in the synovium. Importantly, non-canonical Wnt activation induces robust inflammatory gene expression including an abundance of cytokines and chemokines in synovial fibroblasts in vitro. Strikingly, the addition of Wnt ligands or inhibition of Wnt secretion exacerbates or reduces arthritis severity, respectively, in vivo in a murine model of inflammatory arthritis. These observations are relevant in human disease, as Wnt activation signatures are enhanced in fibroblasts derived from inflamed RA synovial tissue as well as fibroblasts across other inflammatory diseases. Together, these findings implicate Wnt signaling as a major driver of fibroblast-mediated inflammation and joint pathology. They further suggest that targeting the Wnt pathway is a therapeutically relevant approach to rheumatoid arthritis, particularly in patients who do not respond to conventional treatments and who often express fibroblast-predominant synovial phenotypes.

immunology↗

bioRxiv2024

CD4+ tissue resident memory Th17 cells drive IL-17A-mediated joint pathology in Spondyloarthritis

ObjectivesInterleukin (IL)-17A is a key driver of Spondyloarthritis (SpA) joint pathology. We aimed to identify its cellular source in synovial tissue from patients with two forms of SpA namely Axial SpA (AxSpA) and Psoriatic arthritis (PsA). MethodsSynovial tissue from patients with SpA was profiled using single-cell RNA sequencing (scRNA-seq: AxSpA, n=5 and PsA, n=6) or spatial RNA profiling (PsA, n=4). CellPhoneDB was used to infer cell-cell communication. Tissue resident memory Th17 (TRM17)-like cells were generated in vitro using blood memory CD4+ T cells from SpA patients. An epigenetic inhibitor library, siRNA and clustered regularly interspaced short palindromic repeats (CRISPR) were used to identify epigenetic regulator(s) for TRM17. ResultsscRNA-seq showed that CD4+CXCR6+ TRM17 cells are the predominant spontaneous IL17A producers in SpA synovium. Cell-cell communication and single-cell spatial analysis support the interaction between TRM17 and CLEC10A+ dendritic cells, which were activated in SpA. Both sublining and lining fibroblasts in SpA synovium showed evidence of IL-17A activation. In vitro-generated CD4+ TRM17-like cells phenocopied joint tissue TRM17, producing IL-17A/F upon T cell receptor (TCR) stimulation, which was further enhanced by cytokines. Perturbation of BRD1 inhibited the generation of TRM17-like cells. ConclusionsCD4+ TRM17 cells are the predominant source of IL-17A in SpA synovial tissue. TCR stimulation is essential for the secretion of IL-17A by CD4+TRM17-like cells. The epigenetic regulator BRD1 contributes to the generation of CD4+TRM17. Depleting CD4+TRM17 cells in SpA is thus a therapeutic strategy with potential to induce long-term remission. Key messagesO_ST_ABSWhat is already known on this topicC_ST_ABSInterleukin (IL)-17A plays a key role in the immunopathogenesis of Spondyloarthritis (SpA), but its cellular source in joint tissue has not been determined previously. The induction and accumulation of CD4+ tissue resident memory Th17 (TRM17) cells following the clearance of pathogens has been described in skin, lung and kidney. Whether CD4+ TRM17 cells also accumulate in the joint and contribute to the pathology of SpA is not clear. What this study addsO_LICD4+ TRM17 cells are present in SpA synovial tissue and are the predominant source of IL17A C_LIO_LICD4+ TRM17 cells in SpA joints express IL17A without any in vitro exogenous stimulation C_LIO_LIT cell receptor (TCR) rather than cytokine stimulation is essential for IL-17A production by CD4+ TRM17-like cells C_LIO_LIThe epigenetic regulator BRD1 contributes to the generation of CD4+ TRM17-like cells. C_LI How this study might affect research, practice or policyOur findings identify CD4+ TRM17 cells as the primary source of IL-17A in SpA synovium, a previously unrecognized role for these cells. Key questions remain: How do CD4+ TRM17 cells relate to IL-17A producers in synovial fluid? What mechanisms induce and maintain them in the joint? How do they interact with other cells to promote arthritis? These questions warrant further investigation. In addition, our data suggest that targeting CD4+ TRM17 cells, the "factory" of IL-17A in SpA synovial tissue, has the potential to induce long-term remission, encouraging future efforts to develop new therapies to deplete CD4+ TRM17 cells in SpA.

immunology↗

bioRxiv2024

Distinct tissue-niche localization and function of synovial tissue myeloid DC subsets in health, and in active and remission Rheumatoid Arthritis

Current rheumatoid arthritis (RA) treatments do not restore immune tolerance. Investigating dendritic cell (DC) populations in human synovial tissue (ST) may reveal pathways to re-instate tolerance in RA. With single-cell and spatial-transcriptomics of synovial tissue biopsies, validated by micro co-culture systems, we identified condition and niche-specific myeloid DC clusters with distinct differentiation trajectories and functions. Healthy synovium contains a unique tolerogenic AXLpos DC2 cluster in the superficial sublining layer. In active RA, a macrophage-rich lining-layer niche becomes populated with inflammatory DC3 clusters that specifically activate memory CCL5pos TEM and CCL5posCXCL13pos TPH, promoting synovitis. In the sublining lymphoid niche, CCR7pos DC2 mReg specifically interact with naive-T-cells, potentially driving the local expansion of new effector T-cells. Sustained remission sees the resolution of these niches but lacks the recovery of tolerogenic AXLpos DC2, indicating latent potential for disease flare. A human RA disease-flare model showed that the activation of blood predecessor of ST-DC3 clusters precedes the onset of inflammation in joints. Therapeutic strategies targeting pathogenic ST-DC3 clusters, or reinstating tolerogenic AXLpos DC2, may restore immune homeostasis in RA. In briefDeconstruction of human RA synovium, using single-cell spatial transcriptomics and micro-culture systems, reveals distinct neighbourhoods within the synovial architecture across health, and RA patients with active disease or sustained remission. Discrete niches are identified that contain distinct myeloid DC clusters that differ in frequency, differentiation trajectories, and effector functions. HighlightsO_LIHuman RA synovium exhibits condition and niche specific myeloid DC clusters that vary in their tissue differentiation trajectories and functions. C_LIO_LIST-CD14pos DC3 (iDC3) support inflammatory CCL5pos TEM and CCL5pos TPH cell activation in the hyperplastic lining layer. C_LIO_LIST-CCR7pos DC2 (mReg), driven by MIR155, interact with naive-T-cells in sublining lymphoid niches. C_LIO_LIA specific inflammatory signature of blood predecessors of ST-DC3s predict flare in RA. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=199 HEIGHT=200 SRC="FIGDIR/small/600758v1_ufig1.gif" ALT="Figure 1"> View larger version (74K): org.highwire.dtl.DTLVardef@27ab01org.highwire.dtl.DTLVardef@4be238org.highwire.dtl.DTLVardef@1f10734org.highwire.dtl.DTLVardef@1102056_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2024

Integrating spatial transcriptomics count data with Crescendo improves visualization and detection of spatial gene patterns

Spatial transcriptomics allows for the analysis of a cells gene expression in the context of its physical location. With spatial transcriptomics data, investigators often want to find genes of interest whose spatial patterns are biologically relevant in multiple samples. However, due to confounding factors in spatial data that produce noise across samples, datasets, and technologies, it is challenging to visualize genes and their spatial patterns across samples. We present Crescendo, an integration algorithm that performs correction directly on gene expression counts to reduce variation from technical confounders. We first apply Crescendo to a 3-sample spatial transcriptomics mouse brain dataset to show how Crescendo enables accurate visualization of gene expression across these spatial transcriptomic samples. We then demonstrate Crescendos scalability by integrating a 16-sample immuno-oncology dataset of 7 million cells. Finally, we show that Crescendo can perform cross-technology integration by merging a colorectal cancer (CRC) scRNA-seq dataset with two CRC spatial transcriptomics samples. By transferring information between technologies, Crescendo can impute poorly expressed genes to improve detection of gene-gene colocalization, such as ligand-receptor interactions.

bioinformatics↗

bioRxiv2023

Adipocytes regulate fibroblast function, and their loss contributes to fibroblast dysfunction in inflammatory diseases

Fibroblasts play critical roles in tissue homeostasis, but in pathologic states can drive fibrosis, inflammation, and tissue destruction. In the joint synovium, fibroblasts provide homeostatic maintenance and lubrication. Little is known about what regulates the homeostatic functions of fibroblasts in healthy conditions. We performed RNA sequencing of healthy human synovial tissue and identified a fibroblast gene expression program characterized by enhanced fatty acid metabolism and lipid transport. We found that fat-conditioned media reproduces key aspects of the lipid-related gene signature in cultured fibroblasts. Fractionation and mass spectrometry identified cortisol in driving the healthy fibroblast phenotype, confirmed using glucocorticoid receptor gene (NR3C1) deleted cells. Depletion of synovial adipocytes in mice resulted in loss of the healthy fibroblast phenotype and revealed adipocytes as a major contributor to active cortisol generation via Hsd11{beta}1 expression. Cortisol signaling in fibroblasts mitigated matrix remodeling induced by TNF- and TGF{beta}, while stimulation with these cytokines repressed cortisol signaling and adipogenesis. Together, these findings demonstrate the importance of adipocytes and cortisol signaling in driving the healthy synovial fibroblast state that is lost in disease.

cell biology↗

bioRxiv2023

Spatial analysis of human lung cancer reveals organized immune hubs enriched for stem-like CD8 T cells and associated with immunotherapy response

The organization of immune cells in human tumors is not well understood. Immunogenic tumors harbor spatially-localized multicellular immunity hubs defined by expression of the T cell-attracting chemokines CXCL10/CXCL11 and abundant T cells. Here, we examined immunity hubs in human pre-immunotherapy lung cancer specimens, and found that they were associated with beneficial responses to PD-1-blockade. Immunity hubs were enriched for many interferon-stimulated genes, T cells in multiple differentiation states, and CXCL9/10/11+ macrophages that preferentially interact with CD8 T cells. Critically, we discovered the stem-immunity hub, a subtype of immunity hub strongly associated with favorable PD-1-blockade outcomes, distinct from mature tertiary lymphoid structures, and enriched for stem-like TCF7+PD-1+ CD8 T cells and activated CCR7+LAMP3+ dendritic cells, as well as chemokines that organize these cells. These results elucidate the spatial organization of the human intratumoral immune response and its relevance to patient immunotherapy outcomes.

immunology↗

bioRxiv2022

A cellular and spatial map of salivary glands at single cell resolution reveals the functional basis of tertiary lymphoid structure formation in Sjogren's syndrome

The key role of tertiary lymphoid structures in autoimmune and non-autoimmune conditions has been recently appreciated. While many of the molecular mechanisms involved in tertiary lymphoid structure (TLS) formation have been identified, their cellular sources and their temporal and spatial relationship to each other during the development of TLS remain unknown. Here we have constructed a cellular and functional map of key components involved in the formation of TLS in the minor salivary glands (SG) in humans. We have confirmed the presence of an immunofibroblast cell state and identified an undescribed immunopericyte cell state with potential immunological functions within TLS. The identification of TLS cellular and functional properties and their relevant modulators provided by this analysis provides key therapeutic cues for TLS associated conditions in autoimmunity and cancer.

immunology↗

bioRxiv2021

IL-1-driven stromal-neutrophil interaction in deep ulcers defines a pathotype of therapy non-responsive inflammatory bowel disease

Current inflammatory bowel disease (IBD) therapies are ineffective in a high proportion of patients. Combining bulk and single-cell transcriptomics, quantitative histopathology, and in situ localisation, we describe heterogeneity of the tissular inflammatory response in IBD treatment failure. Among inflammatory pathotypes, we found high neutrophil infiltration, activation of fibroblasts, and vascular remodelling at sites of deep ulceration was a feature of non-response to several anti-inflammatory therapies. Activated fibroblasts in the ulcer bed display neutrophil chemoattractant properties that are IL-1R- but not TNF-dependent. The identification of distinct, localised, tissular pathotypes associated with treatment non-response will aid precision targeting of current therapeutics and provide a biological rationale for IL-1 signalling blockade in ulcerating disease.

immunology↗

bioRxiv2021

Cross-tissue, single-cell stromal atlas identifies shared pathological fibroblast phenotypes in four chronic inflammatory diseases

Pro-inflammatory fibroblasts are critical to pathogenesis in rheumatoid arthritis, inflammatory bowel disease, interstitial lung disease, and Sjogrens syndrome, and represent a novel therapeutic target for chronic inflammatory disease. However, the heterogeneity of fibroblast phenotypes, exacerbated by the lack of a common cross-tissue taxonomy, has limited the understanding of which pathways are shared by multiple diseases. To investigate, we profiled patient-derived fibroblasts from inflamed and non-inflamed synovium, intestine, lung, and salivary glands with single-cell RNA-sequencing. We integrated all fibroblasts into a multi-tissue atlas to characterize shared and tissue-specific phenotypes. Two shared clusters, CXCL10+CCL19+ immune-interacting and SPARC+COL3A1+ vascular-interacting fibroblasts were expanded in all inflamed tissues and additionally mapped to dermal analogues in a public atopic dermatitis atlas. We further confirmed these human pro-inflammatory fibroblasts in animal models of lung, joint, and intestinal inflammation. This work represents the first cross-tissue, single-cell fibroblast atlas revealing shared pathogenic activation states across four chronic inflammatory diseases.

genomics↗

bioRxiv2020

Maximizing statistical power to detect clinically associated cell states with scPOST

As advances in single-cell technologies enable the unbiased assay of thousands of cells simultaneously, human disease studies are able to identify clinically associated cell states using case-control study designs. These studies require precious clinical samples and costly technologies; therefore, it is critical to employ study design principles that maximize power to detect cell state frequency shifts between conditions, such as disease versus healthy. Here, we present single-cell Power Simulation Tool (scPOST), a method that enables users to estimate power under different study designs. To approximate the specific experimental and clinical scenarios being investigated, scPOST takes prototype (public or pilot) single-cell data as input and generates large numbers of single-cell datasets in silico. We use scPOST to perform power analyses on three independent single-cell datasets that span diverse experimental conditions: a batch-corrected 21-sample rheumatoid arthritis dataset (5,265 cells) from synovial tissue, a 259-sample tuberculosis progression dataset (496,517 memory T cells) from peripheral blood mononuclear cells (PBMCs), and a 30-sample ulcerative colitis dataset (235,229 cells) from intestinal biopsies. Over thousands of simulations, we consistently observe that power to detect frequency shifts in cell states is maximized by larger numbers of independent clinical samples, reduced batch effects, and smaller variation in a cell states frequency across samples.

bioinformatics↗

bioRxiv2020

Efficient and precise single-cell reference atlas mapping with Symphony

Recent advances in single-cell technologies and integration algorithms make it possible to construct comprehensive reference atlases encompassing many donors, studies, disease states, and sequencing platforms. Much like mapping sequencing reads to a reference genome, it is essential to be able to map query cells onto complex, multimillion-cell reference atlases to rapidly identify relevant cell states and phenotypes. We present Symphony (https://github.com/immunogenomics/symphony), an algorithm for building integrated reference atlases of millions of cells in a convenient, portable format that enables efficient query mapping within seconds. Symphony localizes query cells within a stable low-dimensional reference embedding, facilitating reproducible downstream transfer of reference-defined annotations to the query. We demonstrate the power of Symphony by (1) mapping a multi-donor, multi-species query to predict pancreatic cell types, (2) localizing query cells along a developmental trajectory of human fetal liver hematopoiesis, and (3) inferring surface protein expression with a multimodal CITE-seq atlas of memory T cells.

bioinformatics↗