SecActPy Example Datasets: Bulk RNA-seq, scRNA-seq, and Spatial Transcriptomics

Example datasets for https://github.com/data2intelligence/SecActpy, a Python package for inferring secreted protein activities from gene expression data using ridge regression. This deposit contains input and expected output files for the four Quick Start tutorials in the SecActPy documentation: Example 1 - Bulk RNA-seq: Differential expression (log-fold change) of Ly86-Fc vs Vehicle treatment (16,325 genes, 1 comparison). Example 2 - scRNA-seq: Ovarian cancer CD4 T cell subset (788 cells, 27,157 genes) with 3 annotated subtypes (CD4_Th1_like, CD4_central_memory, CD4_naive). Includes both cell-type aggregated and single-cell level outputs. Example 3a - Visium Spatial Transcriptomics: Hepatocellular carcinoma (HCC) 10X Visium data (3,415 spots, 33,514 genes) with spatial coordinates. Example 3b - CosMx Spatial Transcriptomics: Liver hepatocellular carcinoma (LIHC) NanoString CosMx data (443,515 cells, 1,000 genes) with 12 annotated cell types and spatial coordinates All output files were generated with SecActPy v0.2.0 using default parameters (SecAct signature, lambda=5e5, n_rand=1000, seed=0, GSL-compatible RNG). Results are identical to the R SecAct package.