Unlocking the Secrets of Cellular Heterogeneity
Explore the intricate specifics of different cell types, states, and interactions with our comprehensive single-cell RNA sequencing services.
Our Single Cell Analysis Capabilities
Single-cell RNA sequencing (scRNA-seq) has revolutionized genomics by providing unparalleled insights into the diversity and complexity of cell populations. This state-of-the-art method allows scientists to examine gene expression in individual cells, granting them the ability to dissect biological systems with unprecedented detail.
Preprocessing & Exploratory Analysis
We cover the full spectrum of data analysis, from ensuring data quality and initial processing to in-depth exploratory analysis.
- Quality Control, Read Alignment, and Gene Quantification
- Normalization and Batch Effect Correction (Seurat, Scanpy)
- Dimensionality Reduction (PCA, UMAP, t-SNE)
- Gene Expression and Pathway Analysis
Cell Identification & Trajectory Inference
Identify distinct cell populations and understand their developmental relationships and dynamic processes.
- Cell Type Identification and Annotation using reference databases
- Trajectory Analysis to infer developmental paths (Monocle, PAGA)
- RNA Velocity Analysis for predicting future cell states
- Ligand-Receptor Interaction Analysis (CellChat, NicheNet)
Integrative & Spatial Analysis
Combine multiple datasets for a more powerful view, integrating single-cell data with other omics layers and spatial context.
- Multi-sample Integration Analysis across conditions and batches
- scRNA-seq and scATAC-seq Multiome Analysis
- Spatial Transcriptomic Analysis (10X Visium, Slide-seq)
- Integration with bulk RNA-seq and proteomic data
Our Single-Cell Analysis Workflow
Quality Control & Filtering
Comprehensive QC including mitochondrial content, gene counts, and doublet detection.
Normalization & Integration
Data normalization, batch correction, and integration of multiple samples.
Clustering & Annotation
Cell clustering, marker identification, and cell type annotation.
Advanced Analysis
Trajectory inference, differential expression, and functional analysis.
Get a Custom Quote for Your Clinical Project
Our team is ready to help you design the best analysis strategy for your clinical genomics needs.
Frequently Asked Questions
Find answers to common questions about our single cell RNA sequencing services and processes.
We support all major single cell technologies:
3', 5', Multiome, Feature Barcode, Fixed RNA
Drop-seq, inDrops, commercial platforms
Smart-seq2, Smart-seq3, CEL-seq2
10X Visium, Slide-seq, MERFISH
Cell number recommendations based on research goals:
We employ multiple annotation approaches for robust cell typing:
Expert curation using canonical marker genes and literature
SingleR, scType, CellID, and other ML-based approaches
CellMarker, PanglaoDB, Human Cell Atlas references
Integration of multiple annotation methods for confidence scoring
Trajectory Inference
Pseudotime ordering and branching analysis
RNA Velocity
Dynamical modeling and future state prediction
Note: Large datasets (>100K cells) or multi-sample integrations may require additional computational time.