| single-cell-foundation-model-scrna-seq-geneformer | Geneformer workflows for tokenization, cell/gene classification, embedding extraction, and perturbation analysis. |
| single-cell-foundation-model-scrna-seq-langcell | LangCell for zero-shot and few-shot cell type annotation with multimodal cell-text matching. |
| single-cell-foundation-model-scrna-seq-scgpt | scGPT for preprocessing, binning, cell embedding extraction, fine-tuning, and reference mapping. |
| spatial-transcriptomics-foundation-model-stofm | SToFM for spatial transcriptomics preprocessing and cell embedding generation. |
| single-cell-scrna-seq-analysis-scanpy | Complete scRNA-seq analysis workflow with Scanpy including QC, normalization, clustering, and marker gene identification. |
| single-cell-multi-omics-analysis-scvi | Probabilistic deep learning for single-cell multi-omics analysis including scVI, scANVI, totalVI. |
| cellxgene-census-query | Query CZ CELLxGENE Census (61M+ cells) for single-cell expression data. |
| spatial-transcriptomics-spatial-data-io | Load spatial transcriptomics data from Visium, Xenium, MERFISH, Slide-seq, and other platforms. |
| single-cell-atac-seq-qc-processing | Trim adapters, align reads, remove duplicates, and evaluate chromatin accessibility data quality. |
| single-cell-atac-seq-peak-calling-annotaion | Call accessible chromatin peaks with MACS2 and identify differentially accessible regions. |
| single-cell-proteomics-data-processing | Load, inspect, centroid, and extract features from raw LC-MS/MS data files using pyOpenMS. |
| single-cell-proteomics-peptide-identification | Search MS2 spectra against protein databases with MSFragger/Comet. |
| single-cell-multi-omics-data-harmonization | Prepare multi-omics datasets for joint integration with normalization and batch correction. |
