{
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  "Package": "TwoSampleMR",
  "Title": "Two Sample MR Functions and Interface to MRC Integrative\nEpidemiology Unit OpenGWAS Database",
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  "Authors@R": "c(\nperson(\"Gibran\", \"Hemani\", , \"g.hemani@bristol.ac.uk\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-0920-1055\")),\nperson(\"Philip\", \"Haycock\", , \"philip.haycock@bristol.ac.uk\", role = \"aut\",\ncomment = c(ORCID = \"0000-0001-5001-3350\")),\nperson(\"Jie\", \"Zheng\", , \"Jie.Zheng@bristol.ac.uk\", role = \"aut\",\ncomment = c(ORCID = \"0000-0002-6623-6839\")),\nperson(\"Tom\", \"Gaunt\", , \"Tom.Gaunt@bristol.ac.uk\", role = \"aut\",\ncomment = c(ORCID = \"0000-0003-0924-3247\")),\nperson(\"Ben\", \"Elsworth\", , \"Ben.Elsworth@bristol.ac.uk\", role = \"aut\",\ncomment = c(ORCID = \"0000-0001-7328-4233\")),\nperson(\"Tom\", \"Palmer\", , \"remlapmot@hotmail.com\", role = \"aut\",\ncomment = c(ORCID = \"0000-0003-4655-4511\")),\nperson(\"Marina\", \"Vabistsevits\", role = \"ctb\",\ncomment = c(ORCID = \"0000-0003-1121-6790\"))\n)",
  "Description": "A package for performing Mendelian randomization using\nGWAS summary data. It uses the IEU OpenGWAS database\n<https://opengwas.io> to automatically obtain data, and a wide\nrange of methods to run the analysis.",
  "License": "MIT + file LICENSE",
  "URL": "https://github.com/MRCIEU/TwoSampleMR,\nhttps://mrcieu.github.io/TwoSampleMR/",
  "BugReports": "https://github.com/MRCIEU/TwoSampleMR/issues/",
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  "Remotes": [
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    "MRPRESSO=rondolab/MR-PRESSO",
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  "Repository": "https://mrcieu.r-universe.dev",
  "Date/Publication": "2026-06-07 06:36:52 UTC",
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  "Author": "Gibran Hemani [aut, cre] (ORCID:\n<https://orcid.org/0000-0003-0920-1055>),\nPhilip Haycock [aut] (ORCID: <https://orcid.org/0000-0001-5001-3350>),\nJie Zheng [aut] (ORCID: <https://orcid.org/0000-0002-6623-6839>),\nTom Gaunt [aut] (ORCID: <https://orcid.org/0000-0003-0924-3247>),\nBen Elsworth [aut] (ORCID: <https://orcid.org/0000-0001-7328-4233>),\nTom Palmer [aut] (ORCID: <https://orcid.org/0000-0003-4655-4511>),\nMarina Vabistsevits [ctb] (ORCID:\n<https://orcid.org/0000-0003-1121-6790>)",
  "Maintainer": "Gibran Hemani <g.hemani@bristol.ac.uk>",
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      "title": "Add meta data to extracted data",
      "topics": [
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      "title": "Estimate r-squared of each association",
      "topics": [
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      "title": "Estimate allele frequency from SNP",
      "topics": [
        "allele_frequency"
      ]
    },
    {
      "page": "available_outcomes",
      "title": "Get list of studies with available GWAS summary statistics through API",
      "topics": [
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      "title": "Perform LD clumping on SNP data",
      "topics": [
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    },
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      "title": "Combine all mr results",
      "topics": [
        "combine_all_mrresults"
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      "title": "Combine data",
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      "topics": [
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      "title": "List of parameters for use with MR functions",
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      "title": "Perform MR Steiger test of directionality",
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      "title": "Perform enrichment analysis",
      "topics": [
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      "title": "Find instruments for use in MR from the OpenGWAS database",
      "topics": [
        "extract_instruments"
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    },
    {
      "page": "extract_outcome_data",
      "title": "Supply the output from 'read_exposure_data()' and all the SNPs therein will be queried against the requested outcomes in remote database using API.",
      "topics": [
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    {
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      "title": "Fisher's combined test",
      "topics": [
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    {
      "page": "forest_plot_1_to_many",
      "title": "1-to-many forest plot",
      "topics": [
        "forest_plot_1_to_many"
      ]
    },
    {
      "page": "forest_plot_basic2",
      "title": "A basic forest plot",
      "topics": [
        "forest_plot_basic2"
      ]
    },
    {
      "page": "format_1_to_many",
      "title": "Format MR results for a 1-to-many forest plot",
      "topics": [
        "format_1_to_many"
      ]
    },
    {
      "page": "format_aries_mqtl",
      "title": "Get data from methylation QTL results",
      "topics": [
        "format_aries_mqtl"
      ]
    },
    {
      "page": "format_data",
      "title": "Read exposure or outcome data",
      "topics": [
        "format_data"
      ]
    },
    {
      "page": "format_gtex_eqtl",
      "title": "Get data from eQTL catalog into correct format",
      "topics": [
        "format_gtex_eqtl"
      ]
    },
    {
      "page": "format_gwas_catalog",
      "title": "Get data selected from GWAS catalog into correct format",
      "topics": [
        "format_gwas_catalog"
      ]
    },
    {
      "page": "format_metab_qtls",
      "title": "Get data from metabolomic QTL results",
      "topics": [
        "format_metab_qtls"
      ]
    },
    {
      "page": "format_mr_results",
      "title": "Format MR results for forest plot",
      "topics": [
        "format_mr_results"
      ]
    },
    {
      "page": "format_proteomic_qtls",
      "title": "Get data from proteomic QTL results",
      "topics": [
        "format_proteomic_qtls"
      ]
    },
    {
      "page": "generate_odds_ratios",
      "title": "Generate odds ratios",
      "topics": [
        "generate_odds_ratios"
      ]
    },
    {
      "page": "get_p_from_r2n",
      "title": "Calculate p-value from R-squared and sample size",
      "topics": [
        "get_p_from_r2n"
      ]
    },
    {
      "page": "get_population_allele_frequency",
      "title": "Estimate the allele frequency in population from case/control summary data",
      "topics": [
        "get_population_allele_frequency"
      ]
    },
    {
      "page": "get_r_from_bsen",
      "title": "Estimate R-squared from beta, standard error and sample size",
      "topics": [
        "get_r_from_bsen"
      ]
    },
    {
      "page": "get_r_from_lor",
      "title": "Estimate proportion of variance of liability explained by SNP in general population",
      "topics": [
        "get_r_from_lor"
      ]
    },
    {
      "page": "get_r_from_pn",
      "title": "Calculate variance explained from p-values and sample size",
      "topics": [
        "get_r_from_pn"
      ]
    },
    {
      "page": "get_se",
      "title": "Get SE from effect size and p-value",
      "topics": [
        "get_se"
      ]
    },
    {
      "page": "harmonise_data",
      "title": "Harmonise the alleles and effects between the exposure and outcome",
      "topics": [
        "harmonise_data"
      ]
    },
    {
      "page": "harmonise_ld_dat",
      "title": "Harmonise LD matrix against summary data",
      "topics": [
        "harmonise_ld_dat"
      ]
    },
    {
      "page": "Isq",
      "title": "I-squared calculation",
      "topics": [
        "Isq"
      ]
    },
    {
      "page": "ld_matrix",
      "title": "Get LD matrix for list of SNPs",
      "topics": [
        "ld_matrix"
      ]
    },
    {
      "page": "ldsc_h2",
      "title": "Univariate LDSC",
      "topics": [
        "ldsc_h2"
      ]
    },
    {
      "page": "ldsc_rg",
      "title": "Bivariate LDSC",
      "topics": [
        "ldsc_rg"
      ]
    },
    {
      "page": "make_dat",
      "title": "Convenient function to create a harmonised dataset",
      "topics": [
        "make_dat"
      ]
    },
    {
      "page": "mr",
      "title": "Perform all Mendelian randomization tests",
      "topics": [
        "mr"
      ]
    },
    {
      "page": "mr_density_plot",
      "title": "Density plot",
      "topics": [
        "mr_density_plot"
      ]
    },
    {
      "page": "mr_egger_regression",
      "title": "Egger's regression for Mendelian randomization",
      "topics": [
        "mr_egger_regression"
      ]
    },
    {
      "page": "mr_egger_regression_bootstrap",
      "title": "Run bootstrap to generate standard errors for MR",
      "topics": [
        "mr_egger_regression_bootstrap"
      ]
    },
    {
      "page": "mr_forest_plot",
      "title": "Forest plot",
      "topics": [
        "mr_forest_plot"
      ]
    },
    {
      "page": "mr_funnel_plot",
      "title": "Funnel plot",
      "topics": [
        "mr_funnel_plot"
      ]
    },
    {
      "page": "mr_grip",
      "title": "MR-GRIP: a modified MR-Egger model with the Genotype Recoding Invariance Property",
      "topics": [
        "mr_grip"
      ]
    },
    {
      "page": "mr_heterogeneity",
      "title": "Get heterogeneity statistics",
      "topics": [
        "mr_heterogeneity"
      ]
    },
    {
      "page": "mr_ivw",
      "title": "Inverse variance weighted regression",
      "topics": [
        "mr_ivw"
      ]
    },
    {
      "page": "mr_ivw_fe",
      "title": "Inverse variance weighted regression (fixed effects)",
      "topics": [
        "mr_ivw_fe"
      ]
    },
    {
      "page": "mr_ivw_mre",
      "title": "Inverse variance weighted regression (multiplicative random effects model)",
      "topics": [
        "mr_ivw_mre"
      ]
    },
    {
      "page": "mr_ivw_radial",
      "title": "Radial IVW analysis",
      "topics": [
        "mr_ivw_radial"
      ]
    },
    {
      "page": "mr_leaveoneout",
      "title": "Leave one out sensitivity analysis",
      "topics": [
        "mr_leaveoneout"
      ]
    },
    {
      "page": "mr_leaveoneout_plot",
      "title": "Plot results from leaveoneout analysis",
      "topics": [
        "mr_leaveoneout_plot"
      ]
    },
    {
      "page": "mr_median",
      "title": "MR median estimators",
      "topics": [
        "mr_median"
      ]
    },
    {
      "page": "mr_meta_fixed",
      "title": "Perform 2 sample IV using fixed effects meta analysis and delta method for standard errors",
      "topics": [
        "mr_meta_fixed"
      ]
    },
    {
      "page": "mr_meta_fixed_simple",
      "title": "Perform 2 sample IV using simple standard error",
      "topics": [
        "mr_meta_fixed_simple"
      ]
    },
    {
      "page": "mr_meta_random",
      "title": "Perform 2 sample IV using random effects meta analysis and delta method for standard errors",
      "topics": [
        "mr_meta_random"
      ]
    },
    {
      "page": "mr_method_list",
      "title": "Get list of available MR methods",
      "topics": [
        "mr_method_list"
      ]
    },
    {
      "page": "mr_mode",
      "title": "MR mode estimators",
      "topics": [
        "mr_mode"
      ]
    },
    {
      "page": "mr_moe",
      "title": "Mixture of experts",
      "topics": [
        "mr_moe"
      ]
    },
    {
      "page": "mr_penalised_weighted_median",
      "title": "Penalised weighted median MR",
      "topics": [
        "mr_penalised_weighted_median"
      ]
    },
    {
      "page": "mr_pleiotropy_test",
      "title": "Test for horizontal pleiotropy in MR analysis",
      "topics": [
        "mr_pleiotropy_test"
      ]
    },
    {
      "page": "mr_raps",
      "title": "Robust adjusted profile score",
      "topics": [
        "mr_raps"
      ]
    },
    {
      "page": "mr_report",
      "title": "Generate MR report",
      "topics": [
        "mr_report"
      ]
    },
    {
      "page": "mr_rucker",
      "title": "MR Rucker framework",
      "topics": [
        "mr_rucker"
      ]
    },
    {
      "page": "mr_rucker_bootstrap",
      "title": "Run rucker with bootstrap estimates",
      "topics": [
        "mr_rucker_bootstrap"
      ]
    },
    {
      "page": "mr_rucker_cooksdistance",
      "title": "MR Rucker with outliers automatically detected and removed",
      "topics": [
        "mr_rucker_cooksdistance"
      ]
    },
    {
      "page": "mr_rucker_jackknife",
      "title": "Run rucker with jackknife estimates",
      "topics": [
        "mr_rucker_jackknife"
      ]
    },
    {
      "page": "mr_scatter_plot",
      "title": "Create scatter plot with fitted lines showing the causal effect estimate for different MR estimators",
      "topics": [
        "mr_scatter_plot"
      ]
    },
    {
      "page": "mr_sign",
      "title": "MR sign test",
      "topics": [
        "mr_sign"
      ]
    },
    {
      "page": "mr_simple_median",
      "title": "Simple median method",
      "topics": [
        "mr_simple_median"
      ]
    },
    {
      "page": "mr_simple_mode",
      "title": "MR simple mode estimator",
      "topics": [
        "mr_simple_mode"
      ]
    },
    {
      "page": "mr_simple_mode_nome",
      "title": "MR simple mode estimator (NOME)",
      "topics": [
        "mr_simple_mode_nome"
      ]
    },
    {
      "page": "mr_singlesnp",
      "title": "Perform 2 sample MR on each SNP individually",
      "topics": [
        "mr_singlesnp"
      ]
    },
    {
      "page": "mr_steiger",
      "title": "MR Steiger test of directionality",
      "topics": [
        "mr_steiger"
      ]
    },
    {
      "page": "mr_steiger2",
      "title": "MR Steiger test of directionality",
      "topics": [
        "mr_steiger2"
      ]
    },
    {
      "page": "mr_two_sample_ml",
      "title": "Maximum likelihood MR method",
      "topics": [
        "mr_two_sample_ml"
      ]
    },
    {
      "page": "mr_uwr",
      "title": "Unweighted regression",
      "topics": [
        "mr_uwr"
      ]
    },
    {
      "page": "mr_wald_ratio",
      "title": "Perform 2 sample IV using Wald ratio.",
      "topics": [
        "mr_wald_ratio"
      ]
    },
    {
      "page": "mr_weighted_median",
      "title": "Weighted median method",
      "topics": [
        "mr_weighted_median"
      ]
    },
    {
      "page": "mr_weighted_mode",
      "title": "MR weighted mode estimator",
      "topics": [
        "mr_weighted_mode"
      ]
    },
    {
      "page": "mr_weighted_mode_nome",
      "title": "MR weighted mode estimator (NOME)",
      "topics": [
        "mr_weighted_mode_nome"
      ]
    },
    {
      "page": "mr_wrapper",
      "title": "Perform full set of MR analyses",
      "topics": [
        "mr_wrapper"
      ]
    },
    {
      "page": "mv_basic",
      "title": "Perform basic multivariable MR",
      "topics": [
        "mv_basic"
      ]
    },
    {
      "page": "mv_extract_exposures",
      "title": "Extract exposure variables for multivariable MR",
      "topics": [
        "mv_extract_exposures"
      ]
    },
    {
      "page": "mv_extract_exposures_local",
      "title": "Attempt to perform MVMR using local data",
      "topics": [
        "mv_extract_exposures_local"
      ]
    },
    {
      "page": "mv_harmonise_data",
      "title": "Harmonise exposure and outcome for multivariable MR",
      "topics": [
        "mv_harmonise_data"
      ]
    },
    {
      "page": "mv_ivw",
      "title": "Perform IVW multivariable MR",
      "topics": [
        "mv_ivw"
      ]
    },
    {
      "page": "mv_lasso_feature_selection",
      "title": "Apply LASSO feature selection to mvdat object",
      "topics": [
        "mv_lasso_feature_selection"
      ]
    },
    {
      "page": "mv_multiple",
      "title": "Perform IVW multivariable MR",
      "topics": [
        "mv_multiple"
      ]
    },
    {
      "page": "mv_residual",
      "title": "Perform basic multivariable MR",
      "topics": [
        "mv_residual"
      ]
    },
    {
      "page": "mv_subset",
      "title": "Perform multivariable MR on subset of features",
      "topics": [
        "mv_subset"
      ]
    },
    {
      "page": "power_prune",
      "title": "Power prune",
      "topics": [
        "power_prune"
      ]
    },
    {
      "page": "read_exposure_data",
      "title": "Read exposure data",
      "topics": [
        "read_exposure_data"
      ]
    },
    {
      "page": "read_outcome_data",
      "title": "Read outcome data",
      "topics": [
        "read_outcome_data"
      ]
    },
    {
      "page": "run_mr_presso",
      "title": "Wrapper for MR-PRESSO",
      "topics": [
        "run_mr_presso"
      ]
    },
    {
      "page": "run_mrmix",
      "title": "Perform MRMix analysis on harmonised dat object",
      "topics": [
        "run_mrmix"
      ]
    },
    {
      "page": "size.prune",
      "title": "Size prune",
      "topics": [
        "size.prune"
      ]
    },
    {
      "page": "sort_1_to_many",
      "title": "Sort results for 1-to-many forest plot",
      "topics": [
        "sort_1_to_many"
      ]
    },
    {
      "page": "split_exposure",
      "title": "Split exposure column",
      "topics": [
        "split_exposure"
      ]
    },
    {
      "page": "split_outcome",
      "title": "Split outcome column",
      "topics": [
        "split_outcome"
      ]
    },
    {
      "page": "standardise_units",
      "title": "Try to standardise continuous traits to be in standard deviation units",
      "topics": [
        "standardise_units"
      ]
    },
    {
      "page": "steiger_filtering",
      "title": "Steiger filtering function",
      "topics": [
        "steiger_filtering"
      ]
    },
    {
      "page": "steiger_sensitivity",
      "title": "Evaluate the Steiger test's sensitivity to measurement error",
      "topics": [
        "steiger_sensitivity"
      ]
    },
    {
      "page": "subset_on_method",
      "title": "Subset MR-results on method",
      "topics": [
        "subset_on_method"
      ]
    },
    {
      "page": "trim",
      "title": "Trim function to remove leading and trailing blank spaces",
      "topics": [
        "trim"
      ]
    },
    {
      "page": "weighted_median",
      "title": "Weighted median method",
      "topics": [
        "weighted_median"
      ]
    },
    {
      "page": "weighted_median_bootstrap",
      "title": "Calculate standard errors for weighted median method using bootstrap",
      "topics": [
        "weighted_median_bootstrap"
      ]
    }
  ],
  "_readme": "https://github.com/MRCIEU/TwoSampleMR/raw/HEAD/README.md",
  "_rundeps": [
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  ],
  "_vignettes": [
    {
      "source": "exposure.Rmd",
      "filename": "exposure.html",
      "title": "Exposure data",
      "author": "Gibran Hemani",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "Reading in from a file",
        "Example 1: The default column names are used",
        "Example 2: The text file has non-default column names",
        "Using an existing data frame",
        "Obtaining instruments from existing catalogues",
        "GWAS catalog",
        "Metabolites",
        "Proteins",
        "Gene expression levels",
        "DNA methylation levels",
        "IEU OpenGWAS database",
        "Clumping"
      ],
      "created": "2020-01-11 20:36:35",
      "modified": "2026-05-15 15:05:51",
      "commits": 14
    },
    {
      "source": "harmonise.Rmd",
      "filename": "harmonise.html",
      "title": "Harmonise data",
      "author": "Gibran Hemani",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "Dealing with strand issues",
        "Correct, unambiguous",
        "Incorrect reference, unambiguous",
        "Ambiguous",
        "Palindromic SNP, inferrable",
        "Palindromic SNP, not inferrable",
        "Options",
        "Drop duplicate exposure-outcome summary sets"
      ],
      "created": "2020-01-11 20:36:35",
      "modified": "2025-08-27 10:42:11",
      "commits": 11
    },
    {
      "source": "introduction.Rmd",
      "filename": "introduction.html",
      "title": "Introduction",
      "author": "Gibran Hemani",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Background",
        "Installation",
        "Overview",
        "Authentication",
        "References"
      ],
      "created": "2020-01-11 20:36:35",
      "modified": "2026-05-15 15:05:51",
      "commits": 11
    },
    {
      "source": "gwas2020.Rmd",
      "filename": "gwas2020.html",
      "title": "Major changes to the IEU GWAS resources for 2020",
      "engine": "knitr::rmarkdown",
      "headings": [
        "What has changed",
        "Dataset IDs",
        "Authentication",
        "UKBiobank data has been curated",
        "All data is now harmonised",
        "LD reference panel is now harmonised",
        "Instrument lists are up-to-date",
        "dbSNP rs IDs",
        "Everything is faster",
        "What is new",
        "Browse available datasets online",
        "Chromosome and position",
        "INDELs are retained",
        "Multi-allelic variants are retained",
        "More data",
        "Error messages are more informative",
        "Easier programmatic access to the database",
        "Local LD operations",
        "Access the data directly",
        "Connect the data to different analytical tools",
        "Key links",
        "How to request new data"
      ],
      "created": "2020-01-11 20:36:35",
      "modified": "2026-05-04 10:07:54",
      "commits": 9
    },
    {
      "source": "outcome.Rmd",
      "filename": "outcome.html",
      "title": "Outcome data",
      "author": "Gibran Hemani",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Available studies in IEU GWAS database",
        "Extracting particular SNPs from particular studies",
        "LD proxies",
        "Using local GWAS summary data",
        "Outcome data format",
        "More advanced use of local data"
      ],
      "created": "2020-01-11 20:36:35",
      "modified": "2026-05-04 10:07:54",
      "commits": 12
    },
    {
      "source": "perform_mr.Rmd",
      "filename": "perform_mr.html",
      "title": "Perform MR",
      "author": "Gibran Hemani and Philip Haycock",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "MR methods",
        "Sensitivity analyses",
        "Heterogeneity statistics",
        "Horizontal pleiotropy",
        "Single SNP analysis",
        "Leave-one-out analysis",
        "Plots",
        "Scatter plot",
        "Forest plot",
        "Forest plot with categories",
        "RadialMR outlier example",
        "MR-PRESSO outlier example",
        "Leave-one-out plot",
        "Funnel plot",
        "1-to-many forest plot",
        "Step 1: Generate 1-to-many MR results",
        "Step 2: Make the 1-to-many forest plot",
        "Example 1. Effect of multiple risk factors on coronary heart disease",
        "Example 2. MR results for multiple MR methods grouped by multiple exposures",
        "Example 3. Stratify results on a grouping variable",
        "Example 4. Effect of BMI on 103 diseases",
        "MR-RAPS: Many weak instruments analysis",
        "MR-GRIP",
        "Reports",
        "MR Steiger directionality test",
        "Multivariable MR",
        "Note about multivariable methods",
        "Note about visualisation",
        "Using your own summary data",
        "From local files",
        "From data frames",
        "Mixing local and OpenGWAS data",
        "Converting to MVMR format",
        "MR estimates when instruments are correlated",
        "MR-MoE: Using a mixture of experts machine learning approach",
        "Post MR results management",
        "Split outcome names",
        "Split exposure names",
        "Generate odds ratios with 95% confidence intervals",
        "Subset on method",
        "Combine all results",
        "References"
      ],
      "created": "2020-01-11 20:36:35",
      "modified": "2026-06-07 06:36:52",
      "commits": 27
    }
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