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FinnGen Handbook
  • Introduction
  • Where to begin
    • Quick guides
      • New to FinnGen
      • Green data users
      • Red data users
    • I'm new to FinnGen, where is the best place for me to start?
    • What kind of questions can I ask of FinnGen data?
    • How do I make a custom endpoint?
    • How do I run a GWAS of a phenotype I created myself?
    • I'm interested in FinnGen rare variant phenotypes
  • Background Concepts
    • Basics of Genetics
    • Linkage Disequilibrium (LD)
    • Genotype Imputation
    • Genotype Data Processing and Quality Control (QC)
    • GWAS Analysis
    • P Values
    • Heritability and genetic correlations
    • Finemapping
    • Conditional analysis
    • Colocalization
    • Using Polygenic Risk Scores
    • PheWAS analysis
    • Survival analysis
    • Longitudinal Data Analysis
    • GWAS Association to Biological Function
    • Genetic Data Resources outside FinnGen
    • Getting Started with Unix
    • Getting Started with R
    • Structure of the FinnGen project
    • Finnish gene pool and health register data
  • FinnGen Data Specifics
    • FinnGen Data Freezes and Releases
    • Analysis proposals
      • What is a FinnGen analysis proposal and when do I need to submit one?
      • How do I submit an analysis proposal?
      • How are analysis proposals handled?
      • What is a FinnGen bespoke analysis proposal and when do I need to submit one?
      • How do I submit a bespoke analysis proposal?
      • How are bespoke analysis proposals handled?
      • What is the difference between FinnGen analysis proposals and FinnGen bespoke analyses?
      • Existing analysis proposals
    • Finnish Health Registries and Medical Coding
      • Finnish health registries
      • Register data pre-processing
      • Data Masking/Blurring of Visit Dates
      • International and Finnish Health Code Sets
      • More information on health code sets
      • VNR code mapping to RxNorm
      • Register code translation files
    • Endpoints
      • FinnGen clinical endpoints
      • History of creating the FinnGen endpoints
      • Location of FinnGen Endpoint and Control Description Files
        • What's new in DF13 endpoints
        • What’s new in DF12 endpoints
        • What’s new in DF11 endpoints
        • What’s new in the DF10 endpoints
        • What’s new in DF9 endpoints
        • What’s new in DF8 endpoints
      • Interpretation of Endpoint Definition file
      • Location of Endpoint Quality Control Report
      • Creating a User-defined Endpoint(s)
      • Requesting a User-defined Endpoint to be included in Core Analysis
      • Complete follow-up time of the FinnGen registries – primary endpoint data
        • Survival analysis using the truncated endpoint file – secondary endpoint data
    • Biobanks in Finland
    • Publishing FinnGen results
      • Preparing manuscripts or conference abstracts
      • The 1-year “Exclusivity Period” Policy
      • List of Publications using FinnGen Data
      • How to share GWAS summary statistics with FinnGen community
      • How to publish GWAS summary statistics
      • Public Result Releases
    • Red Library Data (individual level data)
      • Genotype data
        • Genotype Arrays Used
          • Legacy cohorts and chips
        • Imputation Panel
          • Sisu v4 reference panel
          • Sisu v3 reference panel
          • Sisu v4.2 reference panel
            • Variant-wise QC metrics file
        • Genome build used in FinnGen
        • Genotype Data Processing Flow
        • Genotype Files in Sandbox
          • Imputed genotypes in VCF format
          • Imputed genotypes in BGEN format
          • Imputed genotypes in PLINK format
          • Chip data
          • Imputed HLA alleles
          • Principal components analysis (PCA) data
          • Kinship data
          • Analysis covariates
          • Polygenic risk scores (PRS)
          • Genetic Ancestry
          • Genetic relationships (GRM)
          • Mosaic chromosomal alterations (mCA)
          • Prune data (R9)
          • Imputed STR genotypes (R8)
      • Phenotype data
        • Register data
        • Detailed longitudinal data
          • Splitting combination codes in detailed longitudinal data
        • Service sector data
          • Service sector data code translations
        • Endpoint and endpoint longitudinal data
        • Kanta lab values
          • Data
          • FAQ
          • How-to guides
        • Kanta prescriptions
        • Minimum extended phenotype data
          • Extracting minimum phenotype data per biobank
          • DNA isolation protocols per biobank
        • Minimum longitudinal data
        • Minimum phenotype data (before R11)
        • Cohort data (before R11)
        • Other register data files in Sandbox
          • Register of Congenital Malformations
          • Finnish Registry for Kidney Diseases
          • Reproductive history data
          • Finnish Cancer Registry: Cervical cancer screening
          • Finnish Cancer Registry: Breast cancer screening
          • Finnish Cancer Registry: Detailed cancer data
          • Finnish Register of Visual Impairment
          • Parental cause of death data
          • Ejection fraction data
          • Finnish National Infectious Disease Register
          • Finnish National Vaccination Register
          • Covid-19 primary care data
          • Blood donor data from the Finnish Red Cross Blood Service (FRCBS)
          • Dental data
          • Socioeconomic data
          • Hilmo and avohilmo extended data
      • Omics data
        • Proteomics
          • Expansion Area 5 proteomics data
          • FinnGen 3 proteomics data
        • Metabolomics
        • Single-cell transcriptomics and immune profiling
        • High-content cell imaging
        • Full blood counts and clinical chemistry
      • Hospital administered medications
      • Whole exome sequencing (WES) data
    • Green Library Data (aggregate data)
      • What is "Green" Data?
      • Accessing Green Data
      • Other analyses available
        • Colocalizations in FinnGen
        • Autoreporting – information on overlaps
          • Index of Autoreporting variables
        • HLA
        • LoF burden test
        • Meta-analyses
      • Core analysis results files
        • Recessive GWAS results format
        • Variant annotation file format
        • Genotype cluster plots format
        • GWAS results format
        • Finemapping results format
        • Colocalization results format
          • Results format in colocalization before DF13
        • Autoreporting results format
        • Sex-specific GWAS results format
        • UKBB-FinnGen meta-analysis file formats
        • Pairwise endpoint genetic correlation format
        • Heritabilities
        • Coding variant associations format
        • HLA association results
        • Proteomics results
        • Coding variant results including CHIP EWAS (Exome-Wide Association Scan)
        • Kanta lab association results v1
    • Disease specific Task Force data
      • Inflammatory bowel disease (IBD) SNOMED codes data
    • Expansion Area 3 (EA3) studies
      • EA3 study: Fatty liver disease study and data in Sandbox
      • EA3 study: Age-related macular degeneration study and data in Sandbox
      • EA3 study: Women's health studies
        • EA3 study: Women’s health – Endometriosis and data in Sandbox
        • EA3 study: Human papilloma virus-related gynecological lesions, and data in Sandbox
        • EA3 study: Women’s health – PCOS and infertility study, and data in Sandbox
      • EA3 study: Diabetic Kidney Disease and Rare Kidney Disease study and data in Sandbox
      • EA3 study: Oncology studies
        • EA3 study: Oncology – Breast cancer study and data in Sandbox
        • EA3 study: Oncology –Prostate cancer study and data in Sandbox
        • EA3 study: Oncology – Ovarian cancer study and data in Sandbox
      • EA3 study: Pulmonary diseases (IPF, asthma and COPD) study and data in Sandbox
      • EA3 study: Immune-mediated diseases
      • EA3 study: Heart Failure study and data in Sandbox
      • FinnGen EA3 leads
  • Disease Specific Task Forces
    • Inflammatory bowel disease (IBD)
    • Kidney Diseases
    • Eye Diseases
    • Rheumatic Diseases
    • Atopic Dermatitis
    • Pulmonary Diseases
    • Neurological Diseases
    • Heart Failure
    • Fibrotic Diseases
    • Metabolic diseases
    • Parkinson's diseases
  • Working in the Sandbox
    • How to get started with Sandbox
    • What is Sandbox and what can you do there
    • What do we mean by "red" and "green" data?
    • General workflows for the most common analyses
    • Quirks and Features
      • Managing your files in Sandbox
      • Navigating the Sandbox
      • How to save Sandbox window configuration
      • Copying and pasting in and out of your IVM
      • How to report issues from within the Sandbox
      • Sharing individual-level data within the Sandbox
      • How to download results from your IVM
        • Sandbox download requests – rules and examples for minimum N
      • Keyboard combinations
      • Running analyses in your IVM vs. Pipelines
      • Timeouts and saving your work (backups, github)
      • How to install a R package into Sandbox?
        • How to install R packages with many dependencies
      • Install R and Python packages from the local Sandbox repository
      • How to install a Python package into Sandbox
      • How to install GNU Debian package
      • How to upload your own files to IVM via /finngen/green
      • How to remove files from /finngen/green
      • Using Sandbox as a Chrome application (full screen mode)
      • How to reset your finngen.fi account password
      • Sandbox IVM tool request handling policy
      • Docker images
        • How to get a new Docker image to Sandbox
        • How to mount data into Docker container image
        • Containers available to Sandbox
        • Containers with user customized tool sets
        • How to write a Docker file
        • Anaconda Python environment in the Sandbox
      • Python Virtual Environment in Sandbox
      • How to shut down your IVM
    • Which tools are available?
      • FinnGen exome query tool
      • Custom GWAS tools
        • Custom GWAS GUI tool
        • Custom GWAS command line (CLI) tool
          • Custom GWAS CLI Binary mode
          • Custom GWAS CLI Quantitative mode
        • How to make your summary stats viewable in a PheWeb-style?
        • Finemapping of Custom GWAS analyses
        • PheWeb Users Input Validator tool
        • Conditional analysis of Custom GWAS analyses
      • Pipelines
      • Pre-installed Linux tools
      • PGS Browser
      • Lmod Linux tools
      • Anaconda Python module with ready set of scientific packages
      • Python packages
      • R packages
      • Atlas
        • Quick guide
          • Introduction to OHDSI, OMOP CDM and Atlas
          • From research question to concepts and cohort building
          • Using Atlas in Sandbox
          • Examples on cohort building with Atlas
        • Detailed guide
          • Atlas data model
          • Standard and non-standard codes
          • How to define a cohort in Atlas
            • Select FinnGen data release in Atlas for Search
            • How to define a simple ICD case-control cohort in Atlas
              • Define a simple ICD Concept Set in Atlas
              • Define a simple ICD case cohort in Atlas
              • Define a simple ICD control cohort in Atlas
            • Concept Sets
              • Create Concept Sets using descendants
              • Exclude and Remove codes from Concept Set
              • Simplify Concept Sets that use standard code descendants
              • Create Concept Sets using equivalent standard and non-standard codes
              • View standard code hierarchy in Atlas
            • Cohort Definitions
              • Using the Death register in Atlas
              • Filtering by clinical registries in Atlas
              • Filtering by demographic criteria in Atlas
              • Defining exit rules for a cohort in Atlas
              • Selecting the correct box in Atlas for events and medical codes
            • How to export FinnGen IDs from Atlas
          • Downstream analyses after the Atlas cohorts are created
          • Data Release Summary Statistics in Atlas
          • Cohort Summary Statistics in Atlas
            • Time-dependent Cohort Summary Statistics in Atlas
            • Event inclusion in Cohort Summary Statistics in Atlas
          • Cohort Pathways
      • BigQuery (relational database)
      • Atlas vs BigQuery cohorts
      • Genotype Browser
      • Cohort Operations tool (CO)
        • Upload cohorts to CO
        • Combine cohorts with CO
        • Operate on Atlas cohorts and data with entries and exit events
        • Explore code and endpoint enrichments with CO (CodeWAS)
        • Explore endpoint overlaps with CO
        • Compare custom endpoint to FinnGen endpoint with CO
        • Launch custom GWAS with CO
        • Export FinnGen IDs using CO
        • Understanding phenotypic overlaps using CO
      • Trajectory Visualization Tool (TVT)
        • Running TVT
          • Filtering timelines with TVT
          • Reordering timelines with TVT
          • Clustering timelines with TVT
          • Viewing TVT results
        • Viewing Atlas, CO, and Genotype cohorts in TVT
        • Exporting cohorts from TVT
        • TVT help page
      • LifeTrack
      • Miscellaneous helper scripts/tools
        • Tool to annotate variants with RSIDs
        • Proper translations of medical, service sector and provider codes
        • BigQuery Connection – R
          • Case study – All register data for a person
          • Case study – UpSet plot
          • Case study – Tornado plot
          • Case study – defining simple cohorts using medical codes for running case-control GWAS
        • BigQuery Connection - Python
          • BigQuery Python - Downstream analysis - Active Ingredient - Bar plot
          • BigQuery Python - Case Study - Sex different - Tornado plot
          • BigQuery Python - Case Study - Comorbidity - Upset plot
          • BigQuery Python - Case Study - Patient Timeline - Scatter plot
      • Sandbox internal API for software developers
    • Working with Phenotype Data
      • Variant PheWas
      • How to select controls for your cases
      • Using the R libraries to look at Phenotype data
      • How to check case counts from the data
      • Creating your own user-defined endpoint
    • Working with Genotype Data
      • Genotype Browser how to
      • Cluster Plots
      • ClusterPlot viewer V3C
      • Rare Variant Calling in V3C
      • Create map of allele
      • Genotypes from VCF files
      • Variant PheWas
      • Interpreting rare-variant analysis results
      • Tools for geno-pheno explorations
        • Example: transferring data from Genotype Browser to LifeTrack
        • Example: Visualizing Genotype Browser output data with TVT
    • Running analyses in Sandbox
      • How to run survival analyses
      • How to create custom endpoint using bigquery: example
      • How to use the Pipelines tool
      • How to submit a pipeline from the command line (finngen-cli)
      • How to run genome-wide association studies (GWAS)
        • How to run GWAS using REGENIE
        • Running quantitative GWAS with REGENIE
        • Conditional analysis
        • Conditional Analysis with custom regions and loci
        • How to run GWAS using SAIGE
        • Adding new covariates in GWAS using REGENIE and SAIGE
        • How to run GWAS using plink2 (for unrelated individuals only)
        • How to run GWAS using GATE (survival models)
        • How to run trajGWAS
        • How to run GWAS using the Regenie unmodifiable pipeline
        • How to run an interaction GWAS using the Regenie unmodifiable pipeline
        • How to run survival analysis using GATE unmodifiable pipeline
        • How to run GWAS on imputed HLA alleles using Regenie
      • How to run finemapping pipeline
        • Finemapping with custom regions in DF12
        • Unmodifiable Finemapping pipeline
      • How to run colocalization pipeline
      • How to run the LDSC pipeline
      • How to run PRS pipeline
      • How to calculate PRS weights for FinnGen data
      • Sandbox path and pipeline mappings
      • If your pipeline job fails
      • Tips on how to find a pipeline job ID
      • Managing memory in Sandbox and data filtering tips
      • Using Google Life Sciences API in Sandbox
      • Pipelines is based on Cromwell and WDL
    • Billing information and where to find more details
      • Monitoring Sandbox costs by Sandbox billing report
      • Monitoring Sandbox costs directly from your Google billing account
  • Working outside the Sandbox
    • Risteys
    • Endpoint Browser
    • PheWeb
      • Volcano plots with LAVAA
    • Meta-analysis PheWeb(s)
    • Coding variant browser
    • Multiple Manhattan Plot (MMP)
      • How to prepare an input file for MMP
      • How to use MMP
    • LD browser
    • Green library data
  • FAQ
    • FinnGen Spin Offs
    • FinnGen access and accounts
      • How do I apply for data access?
      • What is "red" or "green" data?
      • I already have green data access, how do I apply for red data access?
      • I cannot access the /finngen/red?
      • How do I enable two-factor authentication (2FA)?
      • I cannot access my FinnGen account?
      • How to reset account credentials
      • What to do if you suspect your account has been compromised
      • Can't access your smartphone for 2FA?
      • How do I access the FinnGen members' area?
      • How do I access FinnGen All Sharepoint?
      • How can I view existing analysis proposals?
      • How can I join the FinnGen Slack?
      • How do I join the FinnGen Teams group?
      • How to apply SES sandbox access
      • How to request a FinnGen account?
    • FinnGen data
      • What to do if I think I found a mistake in the data?
      • What are the field/column names in FinnGen?
      • What covariates are used in FinnGen's core GWAS analyses?
      • Does FinnGen have lab results available?
      • Does FinnGen have family and relatedness information available?
      • Where can I find a list of unrelated individuals in FinnGen?
      • When moving from BCOR to .txt files, what does the column called "correlation" mean?
      • Is there really no participant birth year data?
      • How do I calculate time between events?
      • Can I select only the columns needed for my analysis to import into RStudio?
      • What is the difference is between LD-clumping and the Saige conditional analysis?
      • Can I download all pairwise LD data across the genome at once?
      • How to find latest data releases?
      • Why are there differences in the GWAS results between Data Freezes/Releases?
    • Where can I find
      • COVID association results?
      • Users' Meeting materials?
      • A list of what coding variants are enriched in Finland?
      • A comprehensive list of key file locations in FinnGen?
      • Medical code translations?
    • PheWeb
      • What are QQ and Manhattan plots?
      • How can I access PheWeb?
      • Are fine-mapping results that available in PheWeb also available as flat files?
      • Do the autoreports report the 95% or 99% credible set?
    • Registries
      • What do KELA reimbursement codes map to?
      • What's the cutoff date for FinnGen data?
    • Sandbox
      • What is the FinnGen Sandbox?
      • Why does my IVM freeze while loading data into R/Rstudio
      • Where can I find tutorials and documentation on Sandbox?
      • How do I get my own analysis code into Sandbox?
      • Where to ask for software you'd like to see in Sandbox
      • Can I share individual level data between different Sandbox users?
      • Is there a sun grid engine for running long scripts?
      • How to clear browser cache after sandbox update
      • How do I increase the window resolution on my IVM?
      • How can I view pdf, jpg and HTML files?
      • My Sandbox job was killed - why?
      • How to unzip files in the command line
      • Why aren't my keyboard/shortcuts working in Sandbox like they do in my local computer?
      • How to know if my pipeline job was failed due preemption of worker VM
    • Risteys
      • Why is the case number dropping after the "Check pre-conditions, main-only, mode, ICD version" step?
    • Endpoints
      • Where do I find the most recent list of FinnGen endpoints?
      • What does it mean when an endpoint has “mode” at the end?
      • What scenario would cause an NA (missing data) entry rather than a zero?
      • Does it mean anything when a value is written as $!$ instead of NA?
      • Why is there an inconsistency between ICD10 code J84.1 (IPF) and J84.112?
      • How are control endpoints calculated?
      • Can I get a list of FinnGen IDs by control group for my endpoint?
      • What does Level C mean in the endpoints data table?
      • What does the SUBSET_COV field show?
      • Why is there a "K." prefix on some endpoints?
      • Why there are fewer endpoints going from R5 (N = 2,925) to R8 (N = 2,202)?
      • Should I include primary care registry (PRIM_OUT) codes in my cohort definitions?
      • I found BL_AGE after FU_END_AGE in the endpoint data, how is it possible?
      • Why do individuals who are not dead have death age in endpoint data?
      • I found EVENT_AGE after FU_END_AGE in endpoint data, how is it possible?
    • Pipelines
      • Are there example SAIGE pipelines?
      • How do I apply finemapping to my SAIGE results?
      • Why Pipelines is claiming that my files or folders are not in /finngen/red?
    • Citing
      • How do I cite analysis using publicly available FinnGen results?
      • How do I cite FinnGen results that use individual level data?
    • For biobanks
      • How to apply for data return
    • Data Security and Protection
      • How do I report a data breach?
  • Release Notes
    • Data Releases 2025
    • Data Releases 2024
    • Data Releases 2023
    • Data Releases 2022
    • Data Releases 2021
  • Tool Catalog
  • Glossary
  • User Support
  • Data Protection & Security
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  1. Working in the Sandbox
  2. Working with Genotype Data

Variant PheWas

PreviousGenotypes from VCF filesNextInterpreting rare-variant analysis results

Last updated 1 year ago

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Analyzing phenotype data for individual variant(s)

Some of the variants in FinnGen are too rare to be and available in the, so you need to do a different analysis to look at the phenotypes associated with them.

Using the we can download individuals with a certain genotype and then conduct PheWas analysis to examine which medical codes or FinnGen endpoints might be enriched in that set of individuals. To test if these differences are significant from the background rate in FinnGen (all FinnGen individuals) or from the control cohort (e.g. persons not in cases), one might use a test suitable for small counts such as Fisher's exact test. As thousands of correlated endpoints and codes might be examined in such an exploratory analysis, finding top results around p=.001 may be expected by chance and therefore not necessarily meaningful.

A series of analyses of similarly rare synonymous and non-coding variants may provide an empirical distribution of the types of extreme p-values expected by chance.

You may easily conduct PheWas analysis and Fisher's exact test between cases and background or control cohorts is to using the . With the Cohort Operations tool, you can also use matched controls in order to standardize the effect of sex and age between cases and controls.

We provide a .

Data available for coding variants in PheWeb

For coding and LoF variants that were common enough to be included in the imputation, you can find the association tests directly from PheWeb by searching for the gene they are included in:

Working with rare variant phenotypes

Alternatively, you may also use ready-made R scripts. To use R scripts follow the steps below.

Step 1:

To work with these R scripts you will need to take the largest Sandbox as you will be reading large amounts of data into R.

Step 2:

Step 3:

Open RStudio via Applications>Development>RStudio

Step 4:

Next you need to bring in the R libraries for PheWAS into your IVM. (Note that you can copy and paste the pathname below to the clipboard of your Sandbox rather than needing to type it all in.)

cp /finngen/shared/fgphewasdf9/20220214_062607/files/FGphewasDF9_0.0.0.9000.tar.gz /home/ivm

Step 5:

Within R studio you then need to install the libraries. In RStudio, on the middle right side, click "Install" and then "Browse" to the FGphewasDF9_0.0.0.9000.tar.gz file you just copied over.

Step 6:

From this point there a couple ways you can work through the code. One is to use the vignettes feature of R by typing in the RStudio Console (lower left side):

vignette("simple tutorial", package="FGphewasDF9")

or

vignette("compare_medical_codes", package="FGphewasDF9")

Step 7:

You will see in both these examples that you can look for enrichment of particular medical codes or FinnGen endpoints. Generally, looking at enrichment of FinnGen endpoints is the best way to go (this is the second option). This is because many synonymous medical codes are combined into one FinnGen endpoint (e.g. ICD8, ICD9 and ICD10 are all included, whereas for the code test they will be listed separately).

The libraries will then statistically use Fisher's exact test to compare the cases and controls in each group.

Step 8:

A message like this one means you need to shutdown your current Sandbox and take the largest Sandbox:

Analyzing rarer variants than those present in PheWeb can be done with tool. The Cohort Operations tool has a graphical user interface (GUI) needing no coding skills from the user.

Prepare your list of individuals genotype file either using or (V3C enables you to correct rare variant calls). In the File Browser, you will be able to browse to see these names so that you can tell the code where to also find the file. The name will likely be quite long if coming from GenotypeBrowser. (You can also make lists of individuals through other means, but this topic mainly follows variant analysis.)

\

Another option is to load the code files into R so you can edit them yourself.

Here is an example of the output for a codes-based analysis: (note that sometimes non-standard codes are found in the raw data. You can always check the to see if there is a nearby code. However there are also many typos in the original registry data, especially the older ICD8 and ICD9 codes. Note also that some codes are Finnish specific.)

The next step is to interpret your results. We provide information on which p-values are significant at . Please note also that this method with the Fisher test used in these libraries may not be the best for common phenotypes. For common phenotype s it is important to also take into account the principal components due to population distribution.

CodeWAS analysis in the Cohort Operations
Genotype Browser
V3C
full list of codes
Interpreting rare-variant analysis results
imputed
PheWeb
Genotype Browser
Cohort Operations tool
guideline for interpreting rare variant results