seuratpreparing

What problem does it solve?

Load, QC, normalize, and integrate multi-sample single-cell RNA-seq data to produce ready-to-analyze Seurat objects, reducing manual preprocessing time.

Core Features & Use Cases

• Data Loading & QC: Load multiple samples from common formats (10x Genomics, h5, loom, or pre-loaded Seurat objects) and apply per-sample QC filtering.
• Normalization & Feature Selection: Normalize data with standard pipelines or SCTransform, and identify variable features for downstream analysis.
• Integration & Readiness: Integrate samples across batches using Harmony, RPCA, or other methods to produce a unified object ready for clustering and downstream analyses.
• Real-World Use Case: Combine several patient samples with varied sequencing depth into a single Seurat object and perform joint clustering.

Quick Start

Load your scRNA-seq samples, apply QC, normalize or SCTransform, and integrate them with Seurat to get a ready-to-analyze object.