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| <br> | | <br> |
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− | <br> | + | <br> |
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| === Analysis for QC === | | === Analysis for QC === |
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| |} | | |} |
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− | <br> | + | <br> |
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| === Secondary analyses (with BMI) === | | === Secondary analyses (with BMI) === |
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| ---- | | ---- |
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− | === 1. Typical DIAGRAM analysis using existing association pipeline<br> === | + | === A. Typical DIAGRAM analysis using existing association pipeline<br> === |
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| This is the typical DIAGRAM analysis using your current association pipeline and software. [[Image:1000Genomes march2012 imputation analysis plan 08312012.pdf]] | | This is the typical DIAGRAM analysis using your current association pipeline and software. [[Image:1000Genomes march2012 imputation analysis plan 08312012.pdf]] |
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| '''Important:''' To analyze dosages (not genotypes), you must specify the dosage field with the "--field EC" option. Without this option, you will be analyzing the hard genotypes (i.e. --field option defaults to "GT" or "genotypes")! | | '''Important:''' To analyze dosages (not genotypes), you must specify the dosage field with the "--field EC" option. Without this option, you will be analyzing the hard genotypes (i.e. --field option defaults to "GT" or "genotypes")! |
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− | === 2. Analysis of low frequency variants using Firth bias-corrected logistic regression === | + | === B. Analysis of low frequency variants using Firth bias-corrected logistic regression === |
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| The Firth bias-corrected test has well-controlled type I error rate and good power for analysis of balanced and unbalanced studies. However, it is more computationally intensive. We only run Firth on the subset of variants with 1<= MAC <= 200. | | The Firth bias-corrected test has well-controlled type I error rate and good power for analysis of balanced and unbalanced studies. However, it is more computationally intensive. We only run Firth on the subset of variants with 1<= MAC <= 200. |
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| '''Important:''' To analyze dosages (not genotypes), you must specify the dosage field with the "--field EC" option. Without this option, you will be analyzing the hard genotypes (i.e. --field option defaults to "GT" or "genotypes")! | | '''Important:''' To analyze dosages (not genotypes), you must specify the dosage field with the "--field EC" option. Without this option, you will be analyzing the hard genotypes (i.e. --field option defaults to "GT" or "genotypes")! |
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− | === 3. Analysis of chromosome 20 using logistic regression score test === | + | === C. Analysis of chromosome 20 using logistic regression score test === |
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| The score test has well-controlled type I error rate and good power for meta-analysis of balanced (equal numbers of cases and controls) studies. It is also very computationally efficient. Please run the score test using the EPACTS software. | | The score test has well-controlled type I error rate and good power for meta-analysis of balanced (equal numbers of cases and controls) studies. It is also very computationally efficient. Please run the score test using the EPACTS software. |
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| This command will run single variant analysis using the score test logistic regression on the DISEASE phenotype adjusting for AGE. Add the relevant additional covariates with additional "-cov" options. This assumes that the VCF files are separated by chromosomes (option -sepchr). All variants with at least one minor allele count will be analyzed (option -min-mac 1). It will annotate results by functional category (option -anno) and run the analysis on 10 parallel CPUs (option -run 10). | | This command will run single variant analysis using the score test logistic regression on the DISEASE phenotype adjusting for AGE. Add the relevant additional covariates with additional "-cov" options. This assumes that the VCF files are separated by chromosomes (option -sepchr). All variants with at least one minor allele count will be analyzed (option -min-mac 1). It will annotate results by functional category (option -anno) and run the analysis on 10 parallel CPUs (option -run 10). |
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− | === 4. Typical DIAGRAM analysis using existing association pipeline (with BMI)<br> === | + | === D. Typical DIAGRAM analysis using existing association pipeline (with BMI)<br> === |
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| This is the typical DIAGRAM analysis using your current association pipeline and software including BMI adjustment. [[Image:1000Genomes march2012 imputation analysis plan 08312012.pdf]] | | This is the typical DIAGRAM analysis using your current association pipeline and software including BMI adjustment. [[Image:1000Genomes march2012 imputation analysis plan 08312012.pdf]] |
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| <br> | | <br> |
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− | === 5. Analysis of low frequency variants using Firth bias-corrected logistic regression (with BMI) === | + | === E. Analysis of low frequency variants using Firth bias-corrected logistic regression (with BMI) === |
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| Again use the Firth test on EPACTS for your analysis with BMI | | Again use the Firth test on EPACTS for your analysis with BMI |