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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.