External tools tl.external

tl.external.calculate_ld(dd, prefix[, out, ...])	Estimate LD patterns using PLINK.
tl.external.run_jaxqtl(dd[, prefix, out, ...])	Run cis- or trans-eQTL mapping using jaxQTL on donor-level genotype and aggregated expression data.
tl.external.read_jaxqtl_results(prefix)	Read jaxQTL output TSV file.
tl.external.run_mixmil(dd[, n_pcs, ...])	Train a MixMIL model on donor-level data with flexible covariate encoding.
tl.external.calculate_pcs(dd, prefix[, out, ...])	Run PLINK to calculate genetic PCs using the --pca option.
tl.external.run_tensorqtl(dd[, n_pcs, mode, ...])	Run cis- or trans-QTL mapping using TensorQTL on donor-level aggregated expression and genotype data.
tl.external.read_tensorqtl_results([prefix, ...])	Read TensorQTL result files.
tl.external.run_scdrs(adata[, gs_file, ...])	Run scDRS (single-cell disease-relevance score) analysis on AnnData.
tl.external.run_seismic(adata, magma_file, ...)	Run seismic analysis to link cell types with GWAS traits using single-cell data.
tl.external.run_magma_pipeline(gwas_sumstats)	Complete MAGMA pipeline: prepare inputs, annotate SNPs, and run gene analysis.
tl.external.run_saigeqtl(dd, gene_col[, ...])	Run eQTL mapping using SAIGE-QTL with flexible step execution.
tl.external.configure_saigeqtl_runner([...])
tl.external.get_saigeqtl_runner()
tl.external.make_group_file([dd, ...])	Create group file for set-based rare variant tests.
tl.external.read_saigeqtl_results(prefix[, step])	Read SAIGE-QTL results
tl.external.load_gsmap_results(workdir, ...)	Load gsMap output files into DataFrames.
tl.external.format_gsmap_sumstats(sumstats, ...)	Convert GWAS summary statistics into gsMap-compatible format.