Data Analysis
Bioinformatics analysis and visualization for single-cell multi-omics data
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01
Quality Control
Cell filtering, doublet removal, and data quality assessment
02
Normalization & Integration
Cross-sample integration and batch effect correction
03
Clustering & Annotation
Cell type identification and subpopulation analysis
04
Differential Expression
Gene expression changes between conditions and perturbations
05
Perturbation Analysis
Perturb-seq specific: sgRNA assignment and perturbation effect quantification
06
Visualization & Reporting
Interactive plots, heatmaps, and comprehensive analysis reports
Specific analysis pipelines are customized based on project requirements.