All functions |
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Perform diagnosis to check the consistency between the GWAS z-scores and LD matrix, and detect problematic z-scores (e.g. allele switch issue) using diagnostic functions from SuSiE RSS. |
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Assign GWAS SNPs to LD blocks |
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LD block view summary table |
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Cleans summary statistics |
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Compute gene PIPs based on fine-mapping result and functional annotations. |
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Extract gene-level result from SNP-level gene mapping result |
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Find the nearest genes for top SNPs in each locus. |
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Obtain credible gene sets from SNP-level gene mapping table |
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Make gene Manhattan plot |
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Gene view summary table |
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Get region info with filenames of LD matrices and variant information |
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Get locus level gene PIP |
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Harmonize GWAS summary statistics with LD reference |
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Load UK Biobank LD reference matrix and variant information |
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Make genomic annotations from a GTF file |
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Match GWAS sumstats with LD reference files. Only keep variants included in LD reference. |
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Match alleles between GWAS summary statistics and bigSNP reference panel. |
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merges SuSiE results with original summary statistics data frame |
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Get nearby interactions for enhancer regions near promoters |
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Partition PIPs into functional annotation categories. |
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Partition PIPs into disjoint functional annotation regions |
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Make a structure plot of partitioned PIP by locus |
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Prepare summary statistics with TORUS SNP-level priors as input data for SuSiE |
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Prepare TORUS input files |
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Process ABC scores and save as a GRanges object |
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Process fine-mapping summary statistics data |
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Process GWAS summary statistics and harmonize with LD reference |
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Process chromatin loop data and save as a GRanges object |
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Process PC-HiC data and save as a GRanges object |
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read LD matrix data by file format |
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Read all SNP info in LD reference |
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Run functional fine-mapping using summary statistics |
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Run enrichment analysis and compute SNP-level priors using TORUS |
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SNP view summary table |
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Run fine-mapping for one region with SuSiE using summary statistics (susie_rss) |
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Make gene track plot using Gviz |