Tutorials

Fundamentals

Introduction to SVS: Importing, combining datasets, spreadsheet manipulation, and filtering

This tutorial seeks to guide you through basic importing and spreadsheet manipulation. The steps outlined aim to make you a power user by providing examples of functions that are often under-utilized but can make spreadsheet manipulation a breeze.

Follow the Tutorial »

Working with Marker Maps

The following tutorial is designed to introduce you to marker maps in SVS and will cover some of the common steps for creating, applying, and augmenting genetic marker maps in SVS.

Follow the Tutorial »

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.

Follow the Tutorial »

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.

Follow the Tutorial »

Introduction to DNA-Seq

This tutorial covers the introductory steps and procedures that will prepare your dataset for further NGS analysis and filtering. The steps include data import, annotation track download and filtering, and variant classficiation.

Follow the Tutorial »

LD and Haplotype Analysis

This tutorial leads you through various LD and haplotype analyses in SVS. 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.

Follow the Tutorial »

Regression with Covariates

This tutorial provides an in-depth look at the regression capabilities in SVS. 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.

Follow the Tutorial »

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.

Follow the Tutorial »

Advanced

Analyzing RNA Sequence Data

The following tutorial is designed to systematically introduce you to a number of techniques for analyzing your RNA-Seq or other high throughput sequencing data output within SVS. 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.

Follow the Tutorial »

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.

Follow the Tutorial »

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.

Follow the Tutorial »

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.

Follow the Tutorial »

Creating a Genome Assembly

Currently there are several available genome assemblies within SVS, including the human, cattle and soybean genomes. But what if you are studying corn and you find that there is no genome assembly 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 assembly in SVS.

Follow the Tutorial »

Finding the Causal Variant of a Novel X-Linked Disorder

This tutorial covers an advanced workflow that aims to find the causal variant in the X-linked fatal disorder, Ogden Syndrome. Several filtering procedures are applied to the family data that narrow down the variant set based on our knowledge of the syndrome.

Follow the Tutorial »

NGS Family Analysis

This tutorial covers a comprehensive NGS family-based analysis workflow. The tutorial assumes prior filtering to narrow the variant set to rare and functional variants.

Follow the Tutorial »

Rare Variant Analysis of Complex Diseases

This tutorial covers a complex case/control variant analysis workflow. The steps include variant collapsing and association testing using sequence data and a simulated phenotype.

Follow the Tutorial »

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.

Follow the Tutorial »

Variant Filtering on Unrelated Samples

This tutorial covers a comprehensive filtering workflow to narrow down a variant set to damaging nonsynonymous rare variants. The dataset used in this tutorial has been filtered down to exon regions where at least one sample has a variant.

Follow the Tutorial »