Algorithm Architecture & Decision Matrices
Detailed comparison cards highlighting algorithmic trade-offs, strengths, weaknesses, and recommended production setups.
Primary Software & Algorithms in Single-Cell & Spatial Omics
Direct command-line recipes, Conda environment specifications, memory footprints, and license metadata.
Industry leading R toolkit for single-cell genomics, featuring sketch-based million-cell analysis, bridge integration across modalities (RNA + ATAC), and spatial transcriptomics.
R -e 'install.packages("Seurat")'
Scalable toolkit for analyzing single-cell gene expression data. Integrates preprocessing, Leiden graph clustering, diffusion pseudotime trajectories, and GPU RAPIDS acceleration.
pip install scanpy
Deep probabilistic modeling framework for single-cell omics (scVI, totalVI, scArches, DestVI). Uses Variational Autoencoders for zero-shot batch integration and spatial deconvolution.
pip install scvi-tools
Official analysis pipelines for Chromium single-cell RNA, V(D)J, ATAC, and Feature Barcode libraries. Demultiplexes BCLs, aligns reads, generates cell-barcode matrices, and produces web summaries.
curl -O https://cf.10xgenomics.com/releases/cell-exp/cellranger-8.0.tar.gz
Fast, sensitive algorithm for integrating single-cell transcriptomes across multiple donors, technologies, and tissues. Projects cells into a shared low-dimensional embedding iteratively.
R -e 'install.packages("harmony")'
Infers, visualizes, and analyzes intercellular communications from single-cell transcriptomics data using curated ligand-receptor pairs (integrating soluble agonists and co-factors).
R -e 'devtools::install_github("jinworks/CellChat")'
Combines spatial molecular data with high-resolution microscopy images. Analyzes spatial neighborhood graphs, co-occurrence scores, ligand-receptor spatial colocalization, and image features.
pip install squidpy
Proceed to Stage 7: ChIP-Seq, ATAC-Seq, Methylation & Hi-C
Sequencing pipelines proceed sequentially. Move forward to the next analytical domain to explore downstream algorithms and execution profiles.