Function reference • ctwas

All functions
`add_pos()`	Add SNP and gene positions to cTWAS finemapping result.
`anno_finemap_res()`	Map finemapping result of molecular traits to genes.
`anno_susie_alpha_res()`	Map molecular traits to genes in susie alpha result.
`assemble_region_data()`	Assembles data for all the regions
`combine_gene_pips()`	Combines gene PIPs by context, type or group.
`compute_gene_z()`	Computes z-scores of molecular traits
`compute_region_cor()`	Computes correlation matrices for a single region
`compute_region_nonSNP_PIPs()`	Computes non-SNP PIPs for all regions from finemapping result
`compute_weight_LD_from_ref()`	Computes LD for weight variants using reference LD
`convert_fusion_to_predictdb()`	Converts fusion weights to predictDB format
`convert_geno_to_LD_matrix()`	Converts PLINK genotype data to LD matrices and SNP info files, saves LD matrices as .RDS files and SNP info as .Rvar files
`convert_to_ukb_varIDs()`	Convert variant IDs from Open GWAS format or PredictDB weight format
`create_predictdb_from_QTLs()`	Creates weight files in PredictDB format from QTL data
`create_snp_LD_map()`	Map SNPs to regions using region meta table.
`create_snp_map()`	Map SNPs to regions using all the variants in the LD reference.
`ctwas_sumstats()`	cTWAS analysis using summary statistics
`ctwas_sumstats_noLD()`	cTWAS analysis using summary statistics with "no LD" version
`diagnose_LD_mismatch_susie()`	Diagnose LD mismatch using SuSiE RSS
`est_param()`	Estimates cTWAS parameters using EM
`estimate_region_L()`	Estimate L for all regions by running finemapping with uniform prior
`expand_region_data()`	Expands region_data with all SNPs
`filter_z_gene_by_group_size()`	Filter z_gene by group size
`finemap_regions()`	Runs cTWAS fine-mapping for regions
`finemap_regions_noLD()`	Runs cTWAS fine-mapping for regions without LD (L = 1)
`get_gene_annot_from_ens_db()`	Get gene annotation table from Ensembl database
`get_gene_info()`	Get gene info from weights
`get_gene_regions()`	Get regions for each gene
`get_molecular_ids()`	Get original molecular IDs
`get_predictdb_genome_build()`	Get genome build of PredictDB weight
`get_problematic_genes()`	Gets problematic genes from problematic SNPs
`get_region_cor()`	Gets correlation matrices for a single region.
`load_LD()`	Load LD matrix
`load_fusion_weights()`	Loads weights in FUSION format
`load_predictdb_weights()`	Loads weights in PredictDB format
`load_region_cor()`	Loads precomputed correlation matrices for a single region.
`load_weights()`	Loads weights in PredictDB or FUSION format
`make_convergence_plots()`	Make convergence plots for the estimated parameters
`make_locusplot()`	Plots the cTWAS result for a single locus
`merge_region_data()`	Merges region data for cross-boundary genes
`merge_region_data_noLD()`	Merges region data for cross-boundary genes without using LD
`preprocess_weights()`	Preprocess PredictDB/FUSION weights and harmonize with LD reference
`preprocess_z_snp()`	Preprocess GWAS z-scores, harmonize GWAS z-scores with LD reference
`read_gwas()`	Read GWAS summary statistics
`read_snp_info_file()`	Read a single SNP info file as a data frame
`read_snp_info_files()`	Read multiple single SNP info files as a data frame
`screen_regions()`	Screens regions with strong signals to be used in fine-mapping step.
`screen_regions_noLD()`	Screens regions with strong signals without using LD.
`summarize_param()`	Summarizes estimated parameters
`z2p()`	convert z-scores to pvalues

Reference

All functions