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Voight Laboratory

Summary:

The central aim in my lab is to understand the genetic, biological, and evolutionary basis of metabolic, cardiovascular, and immune-mediated phenotypes in human populations. To build this understanding, the lab constructs computational and statistical tools grounded in principles of population biology and quantitative genetics and apply them to genetic data collected across thousands of entire human genomes.

My research has answered population genetic questions about recent demographic and selective events in human populations, and more recently I have focused on mapping risk alleles for common diseases, particularly type-2 diabetes and heart attack. I have also contributed to novel statistical approaches for population genetic inference and disease mapping studies, as well as leading the development of next generation sequencing and genotypic assay technologies designed to improve characterization of genetic variation in the human genome.

In the coming years, the lab activities will focus on developing informational and statistical tools which interrogate vast quantities of human genetic association data, together with other important information sources -- gene expression, protein-protein networks, Chip-SEQ, text-mining, epidemiology, and multiple phenotypic measurements in humans -- in order to construct credibly actionable information on pathways responsible for disease susceptibility.

Affiliations:

People:

Resources:

Databases

  • ADGC GWAS: Summary statistics for ADGC (2011) ( Database )

    "Two sets of summary statistics from Naj et al. are available: one with only p-values and one with allele frequencies and p-values. Each set of summary statistics contains six files: stage 1, stage 2, and stage 1+2 for both adjusted and unadjusted summary statistics. The p-value data is generally available to all users"

  • ADGC GWAS: Summary statistics for ADGC African Americans ( Database )

    "Genome-wide association summary statistics from an ADGC study of African Americans and their genetic risk for late-onset Alzheimer's disease is available. The files provided are both adjusted and unadjusted for APOE. The p-value data is available to all users."

  • ADGC GWAS: Summary statistics for neuropathologic features of Alzheimer's disease and related dementias ( Database )

    "A genome-wide association study and analysis of known genetic risk loci for Alzheimer's disease dementia using neuropathologic data from 4,914 brain autopsies was performed. Association analysis was performed within each cohort separately, and results were meta-analyzed across cohorts and provided here. The p-value data is generally available to all users."

  • AMD Gene Consortium: Macular degeneration scan meta-analysis results ( Database )

    Genome-wide association study, including >17,100 advance age-related macular degeneration cases and >60,000 controls of European and Asian ancestry

  • CARDIoGRAM+C4D: Summary Statistics ( Database )

    CARDIoGRAMplusC4D Metabochip is a two stage meta-analysis of Metabochip and GWAS studies of European and South Asian descent involving 63,746 cases and 130,681 controls.

    "When using data from the downloadable meta-analyses results please acknowledge the source of the data as follows: 'Data on coronary artery disease / myocardial infarction have been contributed by CARDIoGRAMplusC4D investigators and have been downloaded from www.CARDIOGRAMPLUSC4D.ORG'. In addition, please cite the relevant paper(s) for the data used."

  • EGG GWAS: Birth length summary statistics ( Database )

    "We are releasing the summary data from our discovery genome-wide meta-analysis of birth length, in order to enable other researchers to examine particular variants or loci of their interest for association with this trait. The file includes the beta, standard error, P-value and total sample size at over 2 million directly genotyped or imputed single nucleotide polymorphisms (SNPs) from the HapMap project (NCBI build 36). Trait values for birth length were transformed to sex and gestational age adjusted SD scores and assessed for association with each SNP using linear regression of the standardized birth length score against genotype using an additive genetic model.

    Dataset Details
    The birth length dataset was generated by performing a meta-analysis of 22 population-based studies (total N = 28,459 individuals)."

  • EGG GWAS: Birth weight summary statistics ( Database )

    "We are releasing the summary data from our genome-wide meta-analyses of birth weight, in order to enable other researchers to examine particular variants or loci of their interest for association with this trait. The file includes P-values and direction of effect at over 2 million directly genotyped or imputed single nucleotide polymorphisms (SNPs) from the HapMap project (release 27). To minimise the possibility of identification of individuals from these summary results, we are not releasing allele frequency data from our samples. Trait values for birth weight (BW) were transformed to a Z-score and assessed for association with each SNP using linear regression of the birth weight Z-score against genotype using an additive genetic model, with sex and, where available, gestational age as covariables.

    Dataset Details
    The birth weight dataset was generated by performing a meta-analysis of up to 18 population-based European studies (total n = 26,836 individuals)."

  • EGG GWAS: Childhood obesity summary data ( Database )

    "We are releasing the summary data from the genome-wide meta-analysis of childhood obesity (cases defined as BMI>95th percentile; controls defined as BMI<50th percentile) in subjects of European ancestry, in order to enable other researchers to examine particular variants or loci of their interest for association with this trait. The file includes P-values and direction of effect at over 2 million directly genotyped or imputed single nucleotide polymorphisms (SNPs) based on the HapMap Utah residents of Northern and Western European ancestry (CEU) SNPs (Phase 2, release 22). To minimize the possibility of identification of individuals from these summary results, we are not releasing allele frequency data from our samples. We assessed for association with each SNP in the case-control setting using an additive genetic model.

    Dataset Details
    The childhood obesity dataset was generated by performing a meta-analysis of up to 14 studies consisting of 5,530 cases (≥95th percentile of body mass index (BMI)) and 8,318 controls (<50th percentile of BMI). The data made available is where the genomic control was applied to the overall meta-analysis results and the results filtered to where there was data available for at least 8 participating cohorts for any given SNP."

  • EGG GWAS: Head circumference summary data ( Database )

    "We are releasing the summary data from our genome-wide meta-analyses of infant head circumference, in order to enable other researchers to examine particular variants or loci of their interest for association with this trait. The file includes the beta, standard error, P-values, effect allele frequencies and total sample size at over 2 million directly genotyped or imputed single nucleotide polymorphisms (SNPs) from the HapMap project (release 27). Trait values for infant head circumference (HC) were transformed to sex and age adjusted SD scores and assessed for association with each SNP using linear regression of the head circumference Z-score against genotype using an additive genetic model.

    Dataset Details
    The head circumference dataset was generated by performing a meta-analysis of 7 population-based European studies (total n = 10,678 individuals)."

  • EGG GWAS: Pubertal growth summary data ( Database )

    "Here we present the summary data from the genome-wide meta-analysis of three measures of the pubertal growth spurt in subjects of European ancestry. These data include directly genotyped SNPs and SNPs imputed against the HapMap CEU data (release 22).

    Three measures of the pubertal growth spurt were run separately for males and females, and then with both sexes combined. Please see the publication for more details on how each phenotype was calculated. To ensure high quality data, only SNPs for which 90% of samples were successful are included in these files. The number of study subjects for each SNP may vary, and the maximum number may differ from that in the paper due to different filtering criteria. P-values are corrected for genomic inflation."

  • EGG GWAS: Tanner Stage summary data ( Database )

    "Here we present the summary data from the genome-wide meta-analysis of Tanner Stage, a measure of sexual maturation, in subjects of European ancestry. These data include directly genotyped SNPs and SNPs imputed against the HapMap CEU data (release 22).

    Tanner stage data on male genital development and female breast development were run separately and combined. Please see the publication for more details on each phenotype. To ensure high quality data, only SNPs for which 90% of samples were successful are included. P-values are corrected for genomic inflation."

  • GEFOS GWAS: Summary Statistics ( Database )

    "The GEnetic Factors for OSteoporosis (GEFOS) Consortium is a large international collaboration comprising numerous prominent research groups. Osteoporosis is a common age-related complex disease with a strong genetic component. Osteoporotic fractures account for considerable disease burden and costs. The GEFOS.seq project used meta-analysis of whole genome sequencing, whole exome sequencing and deep imputation of genotype data to identify low-frequency and rare variants associated with risk of osteoporosis. Three (3) DXA-derived traits are included in this data release: Femoral Neck bone mineral density (BMD) (FN-BMD), Lumbar Spine BMD (LS-BMD), and Forearm BMD (FA-BMD)."

  • Genome Wide Associations Scans for HDL-C, LDL-C and triglycerides ( Database )

    Meta-analysis of seven GWASs of blood lipoprotein and lipid phenotypes (in 19,840 individuals) with follow-up replication analyses for up to five additional studies (in up to 20,623 individuals).

  • Genome Wide Associations Scans for HDL-C, LDL-C and triglycerides ( Database )

    Genotype imputation and meta-analysis were used to combine three genome-wide scans totaling 8,816 individuals. The 11 independent variants associated with increased LDL cholesterol concentrations in the study also showed increased frequency in a sample of coronary artery disease cases versus controls.

  • Genome Wide Associations Scans for Total Cholesterol, HDL-C, LDL-C and triglycerides ( Database )

    Meta-analysis of 46 lipid GWASs comprising >100,000 individuals of European descent, ascertained in the United States, Europe, or Australia.

    Tables that also include effect size estimates, in standard deviation units, for each variant are also available for download.

  • GIANT GWAS 2010-2013 Summary Statistics: BMI ( Database )

    Summary data from the GIANT consortium 2010-2013 meta-analyses of Genome-wide Association (GWA) data include p-values and direction of effect at over 2 million directly genotyped or imputed single nucleotide polymorphisms (SNPs). Allele frequency data was not released to prevent the possibility of identifying individuals from the summary results.

    Associations between body mass index (BMI) and ~ 2.8 million SNPs in up to 123,865 were examined with targeted follow up of 42 SNPs in up to 125,931 additional individuals.

  • GIANT GWAS 2010-2013 Summary Statistics: Height ( Database )

    Summary data from the GIANT consortium 2010-2013 meta-analyses of Genome-wide Association (GWA) data include p-values and direction of effect at over 2 million directly genotyped or imputed single nucleotide polymorphisms (SNPs). Allele frequency data was not released to prevent the possibility of identifying individuals from the summary results.

    Associations between height and 2,834,208 single nucleotide polymorphisms (SNPs) present in the HapMap Phase 2 European-American reference panel were examined.

  • GIANT GWAS 2010-2013 Summary Statistics: waist-hip ratio adjusted for BMI ( Database )

    Summary data from the GIANT consortium 2010-2013 meta-analyses of Genome-wide Association (GWA) data include p-values and direction of effect at over 2 million directly genotyped or imputed single nucleotide polymorphisms (SNPs). Allele frequency data was not released to prevent the possibility of identifying individuals from the summary results.

    In the discovery stage, up to 2,850,269 imputed and genotyped single nucleotide polymorphisms (SNPs) were examined in 32 GWA studies comprising up to 77,167 participants informative for anthropometric measures of body fat distribution. SNPs representing the top 16 independent regions of association were evaluated in 29 additional, independent studies (up to 113,636 individuals).

  • GIANT GWAS 2012-2015 Summary Statistics: Age-/Sex-Stratified 2015 BMI and WHR ( Database )

    Summary data from the GIANT consortium 2012-2015 meta-analyses of Genome-wide Association data.

    BMI and waist-hip ratio association stratified by age (over and under 50 years old) and sex.

  • GIANT GWAS 2012-2015 Summary Statistics: Anthropometric 2014 Height ( Database )

    Summary data from the GIANT consortium 2012-2015 meta-analyses of Genome-wide Association data.

    Results are reported from a GWAS meta-analysis of adult height in 253,288 individuals of European ancestry.

  • GIANT GWAS 2012-2015 Summary Statistics: Anthropometric 2015 BMI ( Database )

    Summary data from the GIANT consortium 2012-2015 meta-analyses of Genome-wide Association data.

    Data sets available are:

    BMI Men Only
    BMI Women Only
    BMI European descent
    BMI All Ancestries

  • GIANT GWAS 2012-2015 Summary Statistics: Anthropometric 2015 Waist ( Database )

    Summary data from the GIANT consortium 2012-2015 meta-analyses of Genome-wide Association data.

    Genome wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals were conducted. Each association is stratified by sex (male, female) and ancestry (European, All Ancestries). Secondary GWAS meta-analyses for five additional traits were performed:
    - unadjusted WHR
    - BMI-adjusted waist circumference
    - unadjusted waist circumference
    - BMI-adjusted hip circumference
    - unadjusted hip circumference

  • GIANT GWAS 2012-2015 Summary Statistics: Extremes of anthropometric traits summary statistics ( Database )

    Summary data from the GIANT consortium 2012-2015 meta-analyses of Genome-wide Association data.

    GWAS meta-analysis including up to 263,407 was carried out for the upper vs. lower 5th percentiles of body mass index, height, and waist-to-hip ratio, as well as clinical classes of obesity.

  • GIANT GWAS 2012-2015 Summary Statistics: Sex stratified anthropometrics summary statistics ( Database )

    Summary data from the GIANT consortium 2012-2015 meta-analyses of Genome-wide Association data.

    Sex-specific GWAS was performed for six anthropometric traits involving a total of 270,775 subjects from 94 studies.

  • GIANT GWAS 2012-2015 Summary Statistics: Variability in BMI and Height ( Database )

    Summary data from the GIANT consortium 2012-2015 meta-analyses of Genome-wide Association data.

    A meta-analysis was performed of genome-wide association studies of phenotypic variation for height and BMI in human populations.

  • GLGC GWAS: Lipid assocation scan meta-analysis results ( Database )

    Dense genotyping in individuals of European, East Asian, South Asian, and African ancestry

    Analysis of metabochip data and Joint analysis of metabochip and GWAS data are available.

    Each table includes ten columns: the marker names in build hg18 and hg19, the marker names in rsid format, the two alleles of the SNP, the effect size associated with the SNP, the corresponding standard error, the number of individuals evaluated for the SNP, the combined p-value for the SNP and the frequency of the first allele (the trait increasing allele) in the 1000 Genomes European sample. The files include both genotyped and imputed SNPs and are provided in a compressed text file to conserve space.

  • GPC GWAS: Big Five Personality traits summary statistics ( Database )

    "In the first phase of the project, we conducted a meta-analysis of Genome-Wide Association Studies (GWAS) in 10 discovery cohorts (N=17375) and 5 replication cohorts (N=3294) for each of the Big Five personality traits as assessed with the NEO-Five Factor Inventory (Neuroticism, Extraversion, Openness to Experience, Agreeableness and Conscientiousness). HAPMAP build 36 release 22 was used as a reference panel to impute missing genotypes in cohorts. Results of the meta-analysis are available under GPC-1. Please carefully read the ReadmeGPC-1.pdf file when downloading the data. If data end up in a scientific publication (e.g. scientific article, presentation at meeting), please make sure you cite the appropriate publications (see under References)."

  • GPC GWAS: Harmonized neuroticism and extraversion summary statistics ( Database )

    "In the second phase of the project, we conducted a meta-analysis of GWAS in 29 discovery cohorts (N=63661) and 1 replication cohort (N=9786) for two harmonized personality traits: Neuroticism and Extraversion. Personality item data from 9 different inventories were harmonized by applying Item Response Theory (IRT). This was followed by a meta-analysis of GWAS results for the harmonized Neuroticism and Extraversion scores. 1000G build 37 phase 1 v3 was used as a reference panel to impute missing genotypes in cohorts. Results of the meta-analysis are available under GPC-2. Please carefully read the ReadmeGPC-2.pdf file when downloading the data. If data end up in a scientific publication (e.g. scientific article, presentation at meeting), please make sure you cite the appropriate publications (see under References)."

  • ICBP GWAS: Summary Statistics ( Database )

    "This genome-wide association study of systolic and diastolic blood pressure, which used a multi-stage design in 200,000 individuals of European descent, identified sixteen novel loci: six of these loci contain genes previously known or suspected to regulate blood pressure (GUCY1A3–GUCY1B3, NPR3–C5orf23, ADM, FURIN–FES, GOSR2, GNAS–EDN3); the other ten provide new clues to blood pressure physiology.""

    This zipped file (“ICBP-summary-Nature.csv”) contains the genome-wide meta-analysis p-values. The definitions of the variables are as follows: rsid: SNP ID (rs number); chr.hg18: chromosome; pos.hg18: physical position in hg18 coordinates; pval.GC.SBP: genome-wide meta-analysis p-values for systolic blood pressure, corrected for genomic control; pval.GC.DBP: genome-wide meta-analysis p-values for diastolic blood pressure, corrected for genomic control.

  • IGAP GWAS: Summary statistics for Alzheimer's disease ( Database )

    "Two dataset are provided. The first one corresponds to the meta-analysis results obtained in stage 1 including genotyped and imputed data (7,055,881 single nucleotide polymorphisms, 1000G phase 1 alpha imputation, Build 37, Assembly Hg19) of 17,008 Alzheimer's disease cases and 37,154 controls. The second one corresponds to the meta-analysis results of the 11,632 SNPs that were genotyped and tested for association in an independent set of 8,572 Alzheimer's disease cases and 11,312 controls with the combined stage1/stage2 P-values."

  • IHGC GWAS: Summary statistics for migraine ( Database )

    Summary Statistics (top SNPs P<1e-5) for Gormley et al. Meta-analysis of 375,000 individuals identifies 38 susceptibility loci for migraine

  • IIBDGC GWAS: Summary Statistics ( Database )

    "There are two groups of files: (1) GWAS meta-analyses, and (2) GWAS plus Immunochip trans-ancestry MANTRA meta-analyses. Each group has outputs for Crohn's disease (CD), ulcerative colitis (UC), and both inflammatory bowel diseases (IBD) together."

  • MAGIC GWAS Summary Statistics: 2hr glucose datasets ( Database )

    The 2hr glucose datasets were generated by a meta-analysis of nine GWAS in 15,234 non-diabetic individuals and a follow-up of 29 independent loci in 6,958-30,620 individuals. Trait values for 2hr glucose are untransformed and are adjusted for BMI in addition to age, sex and study-specific covariates.

  • MAGIC GWAS Summary Statistics: Fasting insulin and fasting glucose datasets ( Database )

    The fasting insulin and fasting glucose datasets were generated by performing a meta-analysis of up to 21 genome-wide association studies (GWAS) informative for fasting glucose, fasting insulin and indices of β-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 non-diabetic participants. Fasting glucose trait values are not transformed. Trait values for Fasting insulin, HOMA-IR, HOMA-B and fasting proinsulin have been naturally log transformed. All datasets are adjusted for age, sex and study-specific covariates.

  • MAGIC GWAS Summary Statistics: Fasting proinsulin datasets ( Database )

    The fasting proinsulin datasets were generated by a meta-analysis of GWAS data in 10,701 non-diabetic adults of European ancestry. Fasting proinsulin values are adjusted for fasting insulin, age, sex and study-specific covariates.

  • MAGIC GWAS Summary Statistics: Glucose and insulin results accounting for BMI ( Database )

    Glucose results accounting for BMI are from an analysis of 29 studies in up to 58,074 non-diabetic participants and the insulin results accounting for BMI are from an analysis of 26 studies in up to 51,750 non-diabetic participants. Details of the analyses accounting for BMI are within the zip file containing the data.

  • MAGIC GWAS Summary Statistics: HbA1c association results ( Database )

    The HbA1c association results were available in up to 46,368 non-diabetic adults of European descent from 23 GWAS and combined using inverse-variance meta-analysis. HbA1c trait values are untransformed and adjusted for age, sex and study-specific covariates.

  • MAGIC GWAS Summary Statistics: Insulin secretion during OGTT ( Database )

    Meta-analysis results files for glucose-stimulated insulin secretion (GSIS) indices during an oral glucose tolerance test in up to 5318 non-diabetic participants from 9 cohorts.

    The GWAS discovery results for 9 traits from up to 7 cohorts are included in these files. Results from all traits are ln-­‐transformed and are adjusted for age, sex, BMI and study-­‐specific covariates.

  • MAGIC GWAS Summary Statistics: Metabochip replication datasets ( Database )

    Results for fasting glucose are from models adjusted for age and sex, and from up to 133,010 non-diabetic participants from 66 studies. Fasting insulin results are for ln-transformed fasting insulin as the outcome and are adjusted for age, sex and are reported both with and without BMI adjustment. These results are from up to 108,557 individuals from 56 studies. Results for 2h-glucose are from models adjusted for age and sex and from up to 42,854 individuals from 20 studies.

  • PGC GWAS: ADHD summary statistics ( Database )

    "Genome-wide association dataset for meta-analysis consisting of 2,960 individual childhood ADHD cases plus parental or independent control samples"

  • PGC GWAS: Autism summary statistics ( Database )

  • PGC GWAS: Bipolar disorder and schizophrenia summary statistics ( Database )

    "Here, we perform a combined genome-wide association study (GWAS) of 19 779 bipolar disorder (BP) and schizophrenia (SCZ) cases versus 19 423 controls, in addition to a direct comparison GWAS of 7129 SCZ cases versus 9252 BP cases."

  • PGC GWAS: Bipolar disorder summary statistics ( Database )

    Combined genome-wide association study (GWAS) of 7,481 individuals with bipolar disorder (cases) and 9,250 controls as part of the Psychiatric GWAS Consortium

  • PGC GWAS: Cross-disorder summary statistics ( Database )

    "We analysed genome-wide single-nucleotide polymorphism (SNP) data for the five disorders in 33,332 cases and 27,888 controls of European ancestory."

  • PGC GWAS: Major depressive disorder summary statistics ( Database )

    In the discovery phase, more than 1.2 million autosomal and X chromosome single-nucleotide polymorphisms (SNPs) were analyzed in 18 759 independent and unrelated subjects of recent European ancestry (9240 MDD cases and 9519 controls).

  • PGC GWAS: Schizophrenia summary statistics ( Database )

    Genome-wide association study that in stage 1 discovery comprised 21,856 individuals of European ancestry and a stage 2 replication sample of 29,839 independent samples.

  • PGC GWAS: Second schizophrenia mega-analysis summary statistics ( Database )

    "We report the results of a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We obtained genome-wide genotype data from which we constructed 49 ancestry matched, non-overlapping case-control samples (46 of European and three of East Asian ancestry, 34,241 cases and 45,604 controls) and 3 family-based samples of European ancestry (1,235 parent affected-offspring trios). These samples comprise the primary PGC GWAS meta-analysis."

  • PGC GWAS: Sweden 1-6 schizophrenia case-control study ( Database )

    "These data are from a meta-analysis of the Sweden 1-6 schizophrenia case-control study with the 2011 PGC SCZ report. Imputation is to 1000 Genomes, and there are 9.8M autosomal SNPs."

Software

  • Cross-Phenotype Meta-Analysis statistic algorithm ( Algorithmic software component )

    This novel statistic for Cross Phenotype Meta-Analysis (CPMA) detects association of a SNP to multiple, but not necessarily all, phenotypes.

    CPMA tests deviation from the expected exponential behaviour of -log(p) for a set of associations to a SNP.

    CPMA-signed algorithm was updated slightly, ensuring that the statistics is signed given the direction of the non-randomness (negative values if the distribution of p-values are non-random in favor of p-values > 0.5, say).

  • Integrated Haplotype Score calculator ( Algorithmic software component )

    "This program is designed to calculate the integrated Hapotype Score (iHS), described in Voight and Kudaravelli et al. (PLoS Biology, 2006). This tool modifies slightly upon that program found elsewhere, reporting scores of all SNPs with error codes."

    "The integrated haplotype Score (iHS) is a measure of the amount of extended haplotype homozygosity (EHH) at a given SNP along the ancestral allele relative to the derived allele. This measure is typically standardized (mean 0, variance 1) empirically to the distribution of observed iHS scores over a range SNPs with similar derived allele frequencies. Extended homozygosity for haplotypes on a high frequency derived allele relative to the ancestral background is a signature of a positively selected sweep which has not yet reached fixation. A classic signature is in the lactase region (LCT), where presumably selection on lactase-persistence into adulthood is a trait that has be subject to a selective sweep in European (and some African populations) which has not fixed completely."

  • Mendelian Randomization pipeline ( Algorithmic software suite )

    "MeRP is a free, open-source tool designed to streamline and automate large-scale Mendelian Randomization analysis.

    There are three components of the MeRP pipeline.

    Pulling Genetic Instruments from Public Data
    • Pulls down and cleans most recent NHGRI Catalog of GWAS studies
    • Creates valid instrumental variable trait files (IVs) from catalog
    Filtering to satisfy MR conditions
    • Removes SNPs associated with potential confounding factors from IV file
    • Eliminates Linkage Disequilibrium (LD) within IV file.
    MR Calculator
    • Estimates causal effect of selected trait and preselected GWAS disease data"

  • MR_predictor ( Software )

    "MR_predictor is a free, open-source simulation engine designed to guide the development and interpretation of statistical tests of causality between phenotypes using genetic instruments. MR_predictor provides a framework to model either individual traits or complex scenarios where multiple phenotypes are correlated or dependent on each other.

    MR_predictor can incorporate the effects of multiple, independent, biallelic loci contributing genotypic variability to one or more simulated phenotypes. The software has a range of options for sample generation, including ascertainment of a user-specified number cases under a disease model. The output files generated by MR_predictor port into commonly-used analysis tools (e.g., PLINK, R), facilitating a range of analyses germane for Mendelian Randomization studies.

    MR_predictor is currently implemented in PERL. The package is currently designed for the UNIX/Linux operating environment.

    MR_predictor is a development project by Benjamin F. Voight, Assistant Professor of Pharmacology and Genetics at the University of Pennsylvania – Perelman School of Medicine."

  • Whole-genome Association Mapping Machina ( Algorithmic software suite )

    "WHAMM is a free, open-source analysis package designed to estimate patterns of homozygosity in whole genome data sets, as well as perform a range of association analyses and summaries on the resultant output. Additional functionality will be added to also scan whole-genome platform data for signatures of extended haplotype homozygosity consistent with positive selection, summarized with the integrated Haplotype Score (iHS), though this functionality remains to be implemented."


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Last updated: 2016-06-09T14:07:49.025-04:00

Copyright © 2016 by the President and Fellows of Harvard College
The eagle-i Consortium is supported by NIH Grant #5U24RR029825-02 / Copyright 2016