To run this module, please select Analysis | GWAS | QC, The input files should be in PLINK bed format. This wiki page is designed to give users a detailed step-by-step description on running typical GWAS imputation experiments. https://genome.sph.umich.edu/w/index.php?title=Minimac3_Imputation_Cookbook&oldid=12660.
Useful Wiki Pages.
and removing samples with high missingness rate, unusual heterozygosity, high inbreeding coefficient, clear evidence of being genetic ancestry outliers, evidence of relatedness etc. Replicate Sample Check: For samples that are identified as technical replicates, a test for within family Identity by State is applied. The default values are given in the above figure. Note that if you are using the output of the preprocessing step, the default settings will generate file names that are the same as the raw data. Unexpected Sample Relatedness: The output of the test for pairwise relationship across families (or unrelated individuals). GWAS Tutorial¶ This notebook is designed to provide a broad overview of Hail’s functionality, with emphasis on the functionality to manipulate and query a genetic dataset. In the below example, PC1 is plotted against PC2. You signed in with another tab or window. Of course, the PAR and non-PAR regions need to be imputed separately. Any pair of samples that fails the replicate check test is output here. *Genetic distance
This page has been accessed 26,159 times. *Paternal ID The fields in a MAP file are: This wiki page is designed to give users a detailed step-by-step description on running typical GWAS imputation experiments. *Physical position In this example, the vast majority of the GWAS subjects are clustered with Europeans. See our wiki page on Chromosome X Imputation for details on imputing chromosome X. Minimac3 is currently available as a pre-release. as well as a file (FreqPlot) of cohort allele frequency vs reference panel allele frequency, make .vcf.gz files for upload to Michigan Imputation Server. See our wiki page on Pre-Phasing for further details on pre-phasing on GWAS of different samples sizes. The five super-populations, Africans (AFR), Ad Mixed Americans (AMR), East Asians (EAS), Europeans (EUR) and South Asians (SAS), are represented by different colors as shown in the right hand view controller. *Allele 2, FAM files
There are a few pages in this Wiki that may be useful to for Minimac3 users. Jared: PLINK There are a few pages in this Wiki that may be useful to METAL users.
*Sex (1=male; 2=female; other=unknown) AWGs, SWAG, WAGs, swag, wags If pre-phased data is already available in VCF format, users can skip this step. This page also describes some options for PostGSF90 which is designed for genome-wide assocication study (GWAS).. Ignacio Aguilar and Ignacy Misztal, University of Georgia email: iaguilar at inia.org.uy; ignacy at uga.edu 01/29/09 - 07/30/14 The final step for imputation involves running Minimac3 to perform the imputation analysis.
Marker Exclusion List: The set of markers that did not meet marker QC thresholds are summarized in the marker exclusion list along with the reason for exclusion. GWAS (plural GWASes) Acronym of genome-wide association study: an analysis of allelic association for genes or genetic markers throughout a genome. Alexa: PLINK, filtering Related terms . The output bed files are then good as input for the next GWAS imputation step.
With older genotyping platforms, low frequency SNPs are also often excluded because they are hard to genotype accurately.
With more modern genotyping arrays, the accuracy of genotype calls for low frequency SNPs is less of a concern. Welcome to your wiki! Genetic ancestry of a GWAS subject is further predicted using the k-Nearest Neighbors algorithm. ), automate the merge with HapMap3 genotypes (/home/wheelerlab2/Data/HAPMAP3_hg1*/), run smartpca to get principal components (see documentation in /home/wheelerlab2/EIG-6.1.4/EIGENSTRAT/README), plot and choose threshold for filtering people (probably can’t automate), rerun smartpca with filtered set (no HapMap3), Plate effects analysis (if data is available), use [HRC or 1000G Imputation prep tool] (. Minimac3 is a lower memory and more computationally efficient implementation of minimac2. The main purpose of data QC is to identify problematic subjects or markers for follow-up investigation or data exclusion. Top 100 PC scores are saved n the PCA results table. Focus
To add a new page simply reference it within brackets, e.g. Otherwise, see our wiki page on Converting to VCF for further details/tools on converting files to VCF. All of these steps can be easily carried out using PLINK. This is the default page, edit it as you see fit. Specifically, it must be normalized such that the first allele in the bim file is the reference allele and the second allele is the alternative allele. Imputing the PAR on chromosome X is same as usual imputation, since both males and females are diploids at these sites. *Marker ID However, statistical analyses will need to be carefully conducted and the use of dedicated genetics software will be required.