Fundamentals

Genome-Wide SNP Association Tutorial

The following short tutorial covers an abbreviated SNP analysis workflow on a whole-genome scale.

» Access the Tutorial  |  Runtime: 9 minutes

Genetic Association in Complex Disease

The following video tutorial covers a whole genome SNP analysis workflow while highlighting SVS 7.4 functionality.

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Intermediate

Quantitative Haplotype Association and Haplotype Trend Regression

This tutorial provides a step-by-step workflow for creating an LD plot from a marker mapped spreadsheet, defining a haplotype block for a region of interest, and generating haplotype frequency tables for that block.

» Access the Tutorial  |  Runtime:2:35

Fundamentals

Importing and Merging Data in SVS 7

This tutorial leads you through a typical workflow of importing your pedigree data (if applicable), phenotype data, genetic data, and marker map data separately, and then merging them together in a single spreadsheet for analysis.

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SNP Genome-Wide Association

The following tutorial is designed to systematically introduce you to a number of techniques for genome-wide association studies. It is not meant to replicate all the workflows you might use in a complete analysis, but instead touch on a sampling of the more typical scenarios you may come across in your own studies.

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Intermediate

Comparing Copy Number Variations Between Tumors and Normals Using the Affymetrix MIP Array

This tutorial leads you through analyzing MIP (Molecular Inversion Probe) copy number data, as provided by Affymetrix, to detect differences between 17 normal and 25 tumor samples. Though this tutorial applies specifically to Affymetrix MIP data, the concepts can be applied to any copy number project where two or more sets of samples are being compared.

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Family-Based Analysis

This tutorial leads you through family-based association analysis using the PBAT statistical package incorporated into SNP & Variation Suite 7. Covered workflows include data preparation, quality assurance testing, association analysis, and basic visualization of results.

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LD and Haplotype Analysis

This tutorial leads you through various LD and haplotype analyses in SVS 7. For demonstration purposes, a simulated dataset is used consisting of actual Affymetrix 500K genotypes from the four HapMap populations (Phase II) and a fake case/control status.

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Quantitative Haplotype Association and Haplotype Trend Regression

This tutorial provides a step-by-step workflow for generating haplotype frequency tables from and LD plot of your genotype data and then using those tables to perform numerical association or regression.

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Regression with Covariates

This tutorial provides an in-depth look at the SVS 7 Regression Module.  It will cover controlling for confounding variables, model comparison, and stepwise regression.  The genotype spreadsheet included in the project file contains PCA-corrected numeric SNP columns for an additive model.  The phenotype information is simulated.

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Runs of Homozygosity Analysis

Using a simulated dataset, this tutorial will lead you step-by-step through the workflow for finding runs of homozygosity outlined in Dr. Lencz’s paper.

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Advanced

CNV - Quality Assurance

This tutorial covers a typical workflow for quality assurance procedures for whole genome CNV analysis. It also includes some discussion of importing and processing raw data files prior to beginning a CNV analysis project. The tutorial is built around the Affymetrix 500K array, but the workflows are generally applicable to most genotyping arrays and aCGH platforms. There are some anomalies with Illumina data where certain analysis steps may not directly apply.

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Copy Number Variation (CNV) Univariate Analysis

This tutorial covers a basic workflow for whole genome CNV analysis and association testing using the univariate segmentation process in SVS. The tutorial is built around the Affymetrix 500K array, but the workflows are generally applicable to most SNP microarray platforms as well as most aCGH platforms. There are some anomalies with Illumina microarray data where certain analysis steps may not directly apply.

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CNV PCA Search

This tutorial leads you through a holistic approach to determine the optimal number of principal components to correct for with copy number data by utilizing both PCA and association analysis techniques.

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Creating a Genome Map in SVS 7

Currently there are several available genome maps within SVS 7, including the human, cattle and soybean genomes. But what if you are studying corn and you find that there is no genome map available for the species Zea Mays (maize or corn)? Well if you have the necessary information available or you are willing to locate it independently, you will find that it is simple and straightforward to create your own genome map in SVS.

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Recalling Genotypes with BEAGLECALL

This tutorial focuses on BEAGLECALL showcasing add-on scripts required for importing and exporting back and forth between SVS to BEAGLECALL. It also provides a workflow to maximize the efficiency of these products. Many of the scripts featured in this tutorial can also be used with BEAGLE, which has the same file formats as BEAGLECALL.

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Variant Data Import and Analysis Tutorial

This tutorial covers a comprehensive sequencing analysis workflow for importing VCF files, performing quality assurance, and running association tests on sequence data and a simulated phenotype.

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Variant Classification and Visualization Tutorial

This tutorial covers a comprehensive variant classification workflow for filtering variants, classifying variants according to position relative to a gene transcript, classifying variants according to the variant's effect on the amino acid sequence, and visualizing variants of interest.

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Please Help Me Get My Regression Model Set Up!

This blog post is designed to be a thorough introduction and provide more details on how to set up linear regression models. This post will explain:

• How to do a simple regression model that tests every genetic marker against one dependent variable.
• How to adjust for covariates and run a full versus reduced model.
• How to look at SNPs in a range to see if adjacent markers have a combined effect on the dependent variable.
• A few common FAQs regarding running regression.

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