Below you'll find information about major improvements introduced in SVS 6. For a complete list see the release notes in the Manual.

Version 6.4

Improved Copy Number Workflow

Several modifications have been made to CNAM to better streamline copy number analysis, including:

• Importing LogRs into HelixTree can now be done directly from the CNAM menu without having to go through the entire copy number segmentation process.
• The capability to save a LogR DSF as CNT files has been added to the CNAM menu. This makes it computationally viable to export whole genome LogR data for a virtually unlimited number of samples as CNT files which can then be viewed in Affymetrix's GTC Browser. If desired, you can also choose to save selected chromomses rather than the entire DSF file.
• Two new scripts are available for download:
  • Export Univariate Segment Means to Wiggle Files
  • Export Multivariate Segment Means to Wiggle File
  In case you forget to check the Optional Bookmark File Output box when running Copy Number Segmentation, you can run these scripts to create Wiggle files directly from the resulting segment means spreadsheet. Wiggle files can be opened in supported genome browsers (e.g. UCSC, Affymetrix GTC) to view copy number segments across the genome.
  
  Visit our Scripts Repository to download.

Faster Extended Pedigree Analysis

A new optional algorithm is available that can make PBAT 10-100 times faster than the original implementation when analyzing large extended pedigrees. It can be applied to SNP, haplotype and copy number analysis.

See the following knowledge base article for more information:

• Rapid Extended Pedigree Algorithm

Convert Genotypes to DD/Dd/dd

A new option has been added to the marker statistics window enabling the output of a separate spreadsheet with genotypes encoded in the DD/Dd/dd format (where the major and minor alleles are clearly identified as d and D, respectively).

Version 6.3

View Tutorial SNP & Variation Suite 6.3: New Feature Training

Family-Based Copy Number Association Analysis

PBAT now supports the testing for copy-number variation (CNV) in a family-based setting as discussed in [Ionita-Laza 2008]. In conjunction with the Copy Number Analysis Module (CNAM), you can quickly:

• Normalize copy number intensity data
• Correct for batch effects using Eigenstrat-based PCA
• Filter out "poor quality" markers
• Join log2 ratios with pedigree/phenotype information
• Perform whole genome association tests

All robustness properties of the FBAT approach are maintained as in PBAT for SNP analysis. In addition, all previously-developed FBAT extensions, including FBATs for time-to-onset, multivariate FBATs, and FBAT-testing strategies, can be directly transferred to the analysis of CNVs.

Version 6.2

View Tutorial SNP & Variation Suite 6.1 and 6.2: New Feature Training

Whole Genome LogR Ratio Association Tests

In addition to performing association tests on copy number covariates using segmentation, CNAM now offers a straightforward approach to perform whole genome single marker associations (correlation/trend, t-test, and regression) directly on log2 ratios. Further, a median smoothing script is available and can be applied to real-value columns (i.e. p-values) to significantly improve signal to noise ratios.

Correcting for CNV-Based Batch Effects and Stratification

Similar to SNPs in HelixTree (see below), CNAM can correct logR ratios for batch effects and stratification using an Eigenstrat-based principal component analysis (PCA) method.

Version 6.1

Stratification correction using principal component analysis (enhanced “EIGENSTRAT” method) and genomic control

For most genetic models with binary or continuous traits, HelixTree now offers population stratification correction using one or both of the following methods:

• Correction of input data by principal components analysis
• Correction of output chi-square values and p-values by genomic control

Principal components as determined by PCA may also be output into a separate spreadsheet without doing association testing.

Affymetrix 500k, 5.0, 6.0 CEL and CNCHP import and normalization for Copy Number Analysis

CNAM substantially replicates the Affymetrix workflow for converting CEL files to logR ratios, including:

• Quantile normalization (without gender bias)
• Virtual Array Generation (merging CN and SNP data, or NSP and STY)
• Normalizing logR ratios against reference populations (samples can be their own reference for all platforms)

This can be done for 500k, SNP 5.0, and SNP 6.0 arrays. Further, it is relatively high speed and works for thousands of samples. (2,000 samples can be processed overnight.) If preferred, CNAM can also read CNT and CNCHP files from Affymetrix's CNAT Batch Analysis and Genotyping Console Software 2.0 Software tools. 

New Case/Control and Quantitative Trait Association Tests

A new Genetic Association Test window (below) offers a straightforward way of testing for genetic association against either cases vs. controls (binary traits) or quantitative traits using one or more statistical measures under any one of several genetic model assumptions. An array of additional options enables you to detect and correct for stratification using principal components analysis and genomic control, apply multiple testing corrections (including permutation testing), and output overall marker statistics, such as call rate, minor allele frequency, Hardy-Weinberg equilibrium, etc., which can be used to filter "problematic" SNPs from analysis.

Genetic association test screenshots (click to expand)

Version 6.0

New Copy Number Analysis Module (CNAM)

The Copy Number Analysis Module (CNAM), the newest application of the SNP & Variation Suite, is the first software application capable of performing whole genome association studies on copy number variations.

CNAM uses a proprietary dynamic optimal segmenting algorithm capable of rapidly scanning through high-resolution microarray intensity data to identify copy number deletions and amplifications, which can then be used to perform association analysis with HelixTree software.

View Webcast Whole Genome Copy Number Association Analysis with Golden Helix

Runs of Homozygosity Association

Whole Genome Homozygosity Association is a novel analytic method that first identifies patterned clusters of SNPs demonstrating extended homozygosity (runs of homozygosity or "ROHs") and then employs both genome-wide and regionally-specific statistical tests for association to disease. This approach can identify chromosomal segments that may harbor rare, penetrant recessive loci. WGHA is included in the Whole Genome Analysis Module.

View Webcast Using Runs of Homozygosity to Identify Recessive Loci