Single-Cell & Spatial Transcriptomics Analysis Architecture
Deconvolve tissue heterogeneity, resolve rare subclonal cell states, and map spatial ligand-receptor communication with reproducible computational workflows engineered for 10x Genomics and spatial platforms.
Input Data Modalities & Platform Support
Our bioinformaticians accept raw and pre-processed sequencing files across all standard high-throughput instrumentation:
Single-Cell RNA-seq
- 10x Chromium 3' and 5' gene expression (FASTQ / Cell Ranger outs)
- Single-cell immune profiling (TCR / BCR V(D)J sequencing)
- Single-cell ATAC-seq and multiome (RNA + ATAC)
Spatial Transcriptomics
- 10x Genomics Visium (FFPE and fresh frozen tissues)
- Subcellular high-plex in situ platforms (Xenium, CosMx, MERSCOPE)
- High-resolution histology image integration (H&E / DAPI)
Standardized Analytical Workflow
Every dataset undergoes rigorous computational quality control and statistical validation:
- Quality Control & Doublet Removal: Filtering ambient RNA contamination via SoupX, mitochondrial read percentage screening, and in silico homotypic doublet triage with DoubletFinder and Scrublet.
- Cross-Batch Normalization & Integration: Eliminating technical run variation across multi-patient cohorts using Harmony, Seurat v5 FastMNN, and scVI deep generative models without masking true biological variance.
- Unsupervised Clustering & Marker Discovery: Leiden and Louvain graph-based community detection, cell type annotation against reference atlases (SingleR, Azimuth, CellMarker 2.0), and differential expression testing using Wilcoxon and MAST tests.
- Cell-Cell Communication & Pathway Deconvolution: Intercellular signaling network inference via CellChat and SingleCellSignalR, coupled with single-cell gene set enrichment (AUCell, escape) and RNA velocity trajectory analysis.
SLA & Deliverables Package
Clients receive comprehensive, publication-ready research artifacts within 2 to 3 weeks:
- Structured Seurat (`.rds`) and AnnData (`.h5ad`) serialized objects compatible with Python and R.
- Interactive Cellxgene and UCSC Cell Browser web viewers for exploratory data analysis.
- Publication-ready vector figures (UMAP, DotPlots, Heatmaps, Spatial Feature Plots in PDF/SVG).
- Fully reproducible Nextflow pipeline execution logs, environment YAML files, and statistical reports.
Scope Your Single-Cell Transcriptomics Project
Consult with PhD-level computational biologists to establish optimal sequencing depth, cell numbers, and statistical power for your study.
Submit Technical Scoping Inquiry →