Research institutions connected through collaborations, published studies, and prior projects with CD Genomics.
Start with the biological question. The most suitable workflow depends on the molecular readout, required spatial or cellular resolution, and sample format.
Resolve heterogeneous populations, rare states, trajectories and condition-specific responses.
Retain morphology and spatial coordinates while profiling localized transcriptional programs.
Recover paired TCR/BCR chains and relate clonotype identity to transcriptional state.
Link RNA with chromatin accessibility, surface proteins, immune repertoire or methylation readouts.
Use single-cell references with spatial data to localize populations and compare neighborhoods or boundaries.
Access spatial omics services spanning whole-transcriptome discovery, targeted in situ profiling, spatial epigenomics, spatial genomics, and bioinformatics.
A continuous 2 μm × 2 μm grid supports dense spatial gene-expression profiling. Probe-based workflows accommodate FFPE, fresh-frozen and fixed-frozen tissue, with 6.5 × 6.5 mm and 11 × 11 mm capture formats available for selected studies.
Approximately 500 nm DNB spacing supports fine spatial sampling, while large-format options extend to fields of view up to 13 × 13 cm for selected organ-scale studies.
Xenium and CosMx support high-plex in situ RNA mapping at cellular or subcellular scale. Targeted spatial workflows can also localize approved DNA or variant signals and other predefined molecular targets while preserving tissue architecture.
Map chromatin accessibility, histone modifications, and transcription factor binding directly in tissue using spatial ATAC-seq and spatial CUT&Tag while retaining spatial coordinates.
Analysis can extend from primary processing to spatial domains, cell-type mapping, deconvolution, spatially variable genes, neighborhood analysis, cell-cell communication and cross-sample comparison. Existing datasets can also be analyzed independently of wet-lab work.
Profile transcriptomes, chromatin accessibility, histone marks, DNA methylation, genomic variation, immune receptors, and integrated molecular layers at cell-resolved scale, with platform-specific routes for whole cells or nuclei.
Use single-cell RNA sequencing (scRNA-seq) with 10x Chromium or BD Rhapsody for viable cells, single-nucleus RNA sequencing (snRNA-seq) for frozen or difficult-to-dissociate tissues, and full-length or targeted RNA workflows when transcript structure or selected genes are the priority.
Reconstruct paired TCR or BCR clonotypes and use compatible targeted immune workflows to connect clonal expansion with transcriptional cell states.
Profile regulatory heterogeneity through chromatin accessibility and target-directed chromatin profiling, with 10x Chromium, BD Rhapsody, and cell-resolved CUT&Tag workflows available for different study designs.
Resolve cell-to-cell variation in DNA methylation using whole-genome or reduced-representation profiling, or combine methylation with chromatin accessibility, nucleosome organization, CNV, and ploidy in multi-epigenomic studies.
Resolve genomic heterogeneity using single-cell whole-genome sequencing, whole-exome sequencing, or CNV-focused workflows for clonal and cell-population studies.
Connect gene expression with chromatin accessibility, DNA methylation, immune repertoire, surface markers, or genomic features to investigate relationships between cell identity, regulation, and clonality.
Analyze newly generated, customer-provided, or public datasets through cell annotation, differential states, trajectories, regulatory analysis, cross-platform integration, and multi-omics data mining.
Single-cell profiling resolves cellular identities and states; spatial measurements retain tissue coordinates. Combining the two can show where specific populations, states and interactions occur within tissue.
Compare priority spatial transcriptomic and epigenomic services by the evidence they generate, the sample context they retain, and the research questions they are designed to address.
Choose from transcriptome-wide and targeted spatial workflows for compatible fresh-frozen, FFPE, and other tissue formats.
Probe-based workflows provide a practical route for archived samples when tissue quality, morphology, and RNA condition meet assay requirements.
Use spatial ATAC-seq and spatial CUT&Tag to profile chromatin accessibility, histone modifications, and transcription factor binding directly in intact tissue.
Choose among 10x and BD Rhapsody scATAC-seq, cell-resolved CUT&Tag, single-cell WGBS or RRBS, and multi-epigenomic workflows.
Apply spatial and cell-resolved approaches to investigate disease mechanisms, tissue organization, developmental processes, and treatment response.
Combine spatial localization, cell-resolved states, and immune repertoire information to characterize complex tumor ecosystems.
Map molecular and cellular diversity while preserving anatomical regions, tissue layers, and local neural environments.
Follow changing cell states and spatial organization as tissues, organs, and biological structures develop over time.
Connect treatment-associated molecular changes with the specific cells and tissue regions where those changes occur.
Access sequencing-based and imaging-based platforms for spatial transcriptomics, spatial epigenomics, targeted in situ mapping, and cell-resolved transcriptomic, epigenomic, immune, and integrated multi-omic studies.
Sample format directly affects which assays are feasible, how tissue or cells should be prepared, and which analysis route is realistic. Review the material you already have before committing it to sectioning, dissociation, or library preparation.
Suitable for archival and retrospective spatial studies when morphology and RNA condition meet assay requirements.
Supports broad spatial transcriptome discovery and nuclei-based profiling when viable whole-cell recovery is not practical.
Useful for scRNA-seq, immune repertoire and selected cell-resolved multi-omics when viability and debris levels are assay-compatible.
Useful for frozen, fibrotic, fragile or difficult-to-dissociate tissues and for chromatin-focused assays operating at nucleus level.
Supports paired single-cell and spatial designs where cellular identity and tissue localization are generated from biologically comparable material.
The experimental path changes by assay, but the same principle applies: protect sample quality, document critical QC checkpoints, and keep the final analysis tied to the original study comparison.
Read technical introductions, application-focused articles, and practical analysis guides for deeper study planning or follow-up interpretation.
Review sequencing-based and imaging-based spatial approaches, their readouts, and major research applications.
Read articleExplore four practical strategies for studying tumor heterogeneity, immune organization, tissue boundaries, and local response programs.
Read articleFollow a practical route from preprocessing and QC to spatial domains, cell-type mapping, deconvolution, neighborhoods, and interpretation.
Read articleShare the service or platform of interest, sample information, study groups, and the main biological question. These details help define the experimental scope, critical QC steps, and downstream analysis requirements.
