AutOmicScience

Single-cell multiome (paired RNA + ATAC) — MuData assembly, per-modality preprocess, joint embedding (WNN / MultiVI), joint clustering & annotation, chromatin-aware velocity (MultiVelo), eGRN (SCENIC+), cross-modal interpretation.

Single-cell ATAC-seq — fragment import, ATAC QC (TSS / fragment-size / FRiP / doublets), feature matrix (tiles / MACS3 peaks), spectral (LSI) clustering, motif activity (chromVAR), gene activity, peak–gene linkage, scRNA label transfer.

Single-cell RNA-seq — QC & preprocessing, batch integration, clustering, marker genes, cell-type annotation (marker+LLM / reference), DE, functional, trajectory, cell-cell communication.

Cross-modality scverse foundations — data containers, dataset summary, standard preprocessing, evidence grounding, figure inspection. Load first for any omics task.

Spatial transcriptomics (Visium / Xenium / MERFISH / …) — loading, spatial QC, spatial statistics + SVGs (squidpy), spatial domains (SpaGCN), deconvolution & mapping (cell2location / Tangram), spatial cell-cell communication (squidpy / COMMOT), gene imputation (Tangram), 2D/3D visualization.