biocontext-knowledge-queries
BioContext knowledge: UniProt, AlphaFold, STRING, Reactome, GO, PanglaoDB, PubMed, OpenTargets queries via ov.biocontext for gene annotation.
bulk-rna-seq-batch-correction-with-combat
Bulk RNA-seq batch correction with pyComBat: remove batch effects from merged cohorts, export corrected matrices, and benchmark visualizations.
bulk-rna-seq-differential-expression-with-omicverse
Bulk RNA-seq DEG pipeline: gene ID mapping, DESeq2 normalization, statistical testing, volcano plots, and pathway enrichment in OmicVerse.
bulk-rna-seq-deseq2-analysis-with-omicverse
PyDESeq2 differential expression: ID mapping, DE testing, fold-change thresholding, and GSEA enrichment visualization in OmicVerse.
string-protein-interaction-analysis-with-omicverse
STRING protein-protein interaction network analysis with pyPPI: query STRING database, build PPI graphs, expand with add_nodes, and visualize styled networks for bulk gene lists.
bulk-rna-seq-deconvolution-with-bulk2single
Turn bulk RNA-seq cohorts into synthetic single-cell datasets using omicverse's Bulk2Single workflow for cell fraction estimation, beta-VAE generation, and quality control comparisons against reference scRNA-seq.
bulktrajblend-trajectory-interpolation
Extend scRNA-seq developmental trajectories with BulkTrajBlend by generating intermediate cells from bulk RNA-seq, training beta-VAE and GNN models, and interpolating missing states.
bulk-wgcna-analysis-with-omicverse
WGCNA co-expression network: soft-threshold, module detection, eigengenes, hub genes, and trait correlation in OmicVerse.
data-export-excel
Export analysis results, data tables, and formatted spreadsheets to Excel files using openpyxl. Works with ANY LLM provider (GPT, Gemini, Claude, etc.).
data-export-pdf
Create professional PDF reports with text, tables, and embedded images using reportlab. Works with ANY LLM provider (GPT, Gemini, Claude, etc.).
data-io-loading
OmicVerse data I/O: use ov.read(), ov.io.read_h5ad, read_10x_h5, read_10x_mtx, read_visium, read_visium_hd, read_nanostring instead of scanpy. Covers h5ad, 10x, spatial, CSV formats.
data-stats-analysis
Perform statistical tests, hypothesis testing, correlation analysis, and multiple testing corrections using scipy and statsmodels. Works with ANY LLM provider (GPT, Gemini, Claude, etc.).
data-transform
Transform, clean, reshape, and preprocess data using pandas and numpy. Works with ANY LLM provider (GPT, Gemini, Claude, etc.).
data-viz-plots
Publication-quality matplotlib/seaborn plots: scatter, heatmap, violin, bar, line, multi-panel figures. Works with ANY LLM provider.
datasets-loading
OmicVerse built-in datasets: pbmc3k, pancreas, dentategyrus, zebrafish, immune, spatial, multiome, plus create_mock_dataset() and predefined_signatures GMT gene sets.
fastq-analysis-pipeline
Guide through omicverse's alignment module for SRA downloading, FASTQ quality control, STAR alignment, gene quantification, and single-cell kallisto/bustools pipelines covering both bulk and single-cell RNA-seq workflows.
foundation-model-analysis
Foundation model workflows: scGPT, Geneformer, UCE, CellPLM cell embedding, annotation, integration via ov.fm unified API. 22 models.
gsea-enrichment-analysis
Gene set enrichment analysis with correct geneset format handling. Critical guidance for loading pathway databases and running enrichment in OmicVerse.
omicverse-visualization-for-bulk-color-systems-and-single-cell-d
OmicVerse plotting: volcano, venn, boxplot, embedding, density, heatmap families, dotplot, convex hull, stacked bar, and Forbidden City color palettes.
single-cell-annotation-skills-with-omicverse
Cell type annotation: SCSA, MetaTiME, CellVote consensus, CellMatch, GPTAnno, weighted KNN label transfer in OmicVerse.
cellfate-pseudotime-gene-analysis
CellFateGenie: Adaptive Threshold Regression for pseudotime-associated gene discovery, Mellon density, lineage scoring via ov.single.Fate.
single-cell-cellphonedb-communication-mapping
CellPhoneDB v5 ligand-receptor analysis, CellChatViz plots, and the newer ccc_heatmap / ccc_network_plot / ccc_stat_plot communication visualizations in OmicVerse.
single-cell-clustering-and-batch-correction-with-omicverse
Single-cell clustering (Leiden, Louvain, scICE, GMM), batch correction (Harmony, scVI, BBKNN, Combat), topic modeling, and cNMF in OmicVerse.
single-cell-downstream-analysis
AUCell pathway scoring, metacell DEG, scDrug response, SCENIC regulons, cNMF programs, and NOCD community detection in OmicVerse.
single-cell-multi-omics-integration
Multi-omics integration: MOFA factor analysis, GLUE unpaired alignment, SIMBA batch correction, TOSICA label transfer, StaVIA trajectory. Covers scRNA+scATAC paired/unpaired workflows.
single-popv-annotation
PopV population-level cell annotation: 10 algorithms (SCVI, SCANVI, CellTypist, OnClass, RF, SVM, XGBoost, BBKNN, HARMONY, SCANORAMA), consensus voting, pretrained hub models.
single-cell-preprocessing-with-omicverse
Single-cell QC, normalization, HVG detection, PCA, neighbor graph, UMAP/tSNE embedding pipelines in OmicVerse (CPU/GPU).
scenic-gene-regulatory-network
SCENIC gene regulatory network: RegDiffusion GRN inference, cisTarget regulon pruning, AUCell scoring, RSS, regulon embeddings in OmicVerse.
single2spatial-spatial-mapping
Map scRNA-seq atlases onto spatial transcriptomics slides using omicverse's Single2Spatial workflow for deep-forest training, spot-level assessment, and marker visualisation.
single-trajectory-analysis
Trajectory & RNA velocity: PAGA, Palantir, VIA, dynamo, scVelo, latentvelo, graphvelo backends via ov.single.Velo. Pseudotime, stream plots.
spatial-transcriptomics-tutorials-with-omicverse
Spatial transcriptomics: Visium/HD, Stereo-seq, Slide-seq preprocessing (crop, rotate, cellpose), deconvolution (Tangram, cell2location, Starfysh), clustering (GraphST, STAGATE), integration, trajectory, communication.
tcga-bulk-data-preprocessing-with-omicverse
TCGA bulk RNA-seq preprocessing with pyTCGA: GDC sample sheets, expression archives, clinical metadata, Kaplan-Meier survival analysis, and annotated AnnData export.