Transcriptomics & spatial biology
Resolve cellular heterogeneity and connect immune cell states with receptor and other molecular measurements.
Analyses are tailored to your experimental design, data quality and research question. The workflow and deliverables are agreed following project review.
Analysis modules
Cell and sample quality control, including ambient RNA and doublet assessment.
Normalization, dimensionality reduction and clustering.
Integration across samples with inspection for overcorrection.
Reference-assisted cell-type annotation and marker-based review.
Cell-state and gene-program characterization.
Donor-aware differential expression and differential abundance.
TCR/BCR repertoire integration with transcriptomic phenotypes.
RNA plus protein or RNA plus chromatin integration when measured.
Trajectory, regulatory-network and ligand–receptor hypothesis generation.
Data and metadata
Count matrices, compatible 10x outputs, h5ad or Seurat objects; donor/sample identifiers; experimental metadata; V(D)J, antibody-derived tags or chromatin measurements for multimodal extensions.
Proposed deliverables
Annotated analysis object; embeddings; cell-type and donor summaries; comparative results; receptor-linked views when available.
Interpretation and feasibility
Cells are not independent biological replicates. Annotation requires review. Pseudotime, inferred CNVs and ligand–receptor analyses are hypotheses rather than direct evidence of lineage, DNA alterations or functional signaling.
Methods and references
Methods, reference resources and software are selected for each project after protocol, feasibility and licence review. Applicable versions, references and interpretation limits are documented in the agreed workflow.