What's New in SNP & Variation Suite 7.3

PBAT for Family-Based SNP and CNV Association Now Integrated into SVS

SVS now provides integrated tools for the design and analysis of family-based association studies through an exclusive version of the PBAT software package developed by Dr. Christoph Lange of Harvard University's School of Public Health. PBAT incorporates virtually all of the features of the FBAT package also released by Harvard but also provides many additional options for designing association/linkage studies and analyzing data with multiple continuous traits.

» More about Golden Helix PBAT

New PBAT Family-Based QC

The latest version of PBAT incorporates a novel test that assesses the genotyping quality of individual probands in family-based association studies. Published in PLoS Genetics [Fardo, 2009] these tests are “ideally suited as the final layer of quality control filters in the cleaning process of genome-wide association studies." You can also assess Mendelian errors, Hardy-Weinberg Equilibrium and Call Rates per Marker.

» More about Family-Based QC in PLos Genetics

Heat Maps

A new plotting option enables you to generate heat maps – two-dimensional intensity plots of numeric values – from a spreadsheet. Heat maps are useful for identifying non-random patterns in your data. In addition to other applications, they can be helpful in identifying samples, or groups of samples, with copy number losses and gains. Heat maps can also be plotted alongside other numeric plots (e.g. p-values, CNV segmentation results) as well as LD plots.

» More about SVS Visualization Capabilities

Hardy-Weinberg by Sample Statistics

Also included in the latest version is a global sample test to detect departures from Hardy-Weinberg Equilibrium within a single proband or case in a population based-association study. This test is especially valuable for genome-wide association studies.

» More about Quality Assurance

Advanced Printing and Exporting of Plots

Plots can now be more easily customized for publication, printing, and outputting to PDF with new print and image preview capabilities. Increase the scale and quality of an image, include Full Domain and Genome Track views, save to a variety of graphic formats and more.

» More about Saving and Printing Graphs

SVS 7.2 Release Notes

For a complete list of improvements and bug fixes in v7.1 see the Release Notes section of the SNP & Variation Suite Manual.

Linkage Disequilibrium (LD) and Haplotype Analysis

Interactively explore LD and haplotype analysis in an innovative and powerful new interface. You can view LD plots from one or more populations and explore them side-by-side with association results. For haplotype analysis it is easy to define and modify haplotype blocks from an LD plot or spreadsheet, compute haplotype and diplotype frequency tables, and perform a number of haplotype association tests, including per-block and per-haplotype methods.

» More about LD and Haplotype Analysis

Enhanced CNAM Optimal Segmenting

Achieve better precision and accelerated speed for detecting copy number variation. CNAM Optimal Segmenting now incorporates a new parallelized, unbiased randomization permutation procedure that uses all available cores on your computer. The new permutation procedure replaces a naïve, potentially biased randomization procedure with the unbiased Fisher and Yates method (also known as the Knuth shuffle). An added option allows you to further refine your segments by efficiently removing univariate outliers during the segmentation process.

» More about CNAM Optimal Segmenting

PCA Improvements

The time required for iterative use of Principal Component Analysis (PCA) has been significantly reduced by enabling the “recycling” of pre-computed principal components.  This lets you run PCA once and then reuse the principal components in subsequent analyses instead of performing the time-consuming computation each time. Further, new data centering options, by marker and by sample, are now available for numeric data values (such as log ratios), improving the calculation of and correction for principal components.

» More about Principal Component Analysis

PED/TPED/BED File Support

Support for importing and exporting PED, TPED, and BED file formats makes it easy to move your data back and forth between SVS and other genetic analysis.

» More about Supported File Types

New Strand Fields to Facilitate Strand Matching

For a variety of applications, such as imputation and meta-analysis, it is important that two or more datasets represent alleles from the same strand for a given set of markers. Marker maps for Affymetrix and Illumina data (when exporting as Golden Helix DSF from BeadStudio) now include fields for top and bottom strand alleles. This enables you to transcode all genotypic markers from the AB to ACGT formats based on one or the other strands, ensuring consistency among two or more datasets.

» More about Genetic Marker Maps

Additional Regression and Genotype Statistics

Regression results are now more informative with several new regression outputs added to the results spreadsheet (when regressing once on each data column). This makes it easy to both sort and plot on a number of regression-based statistics. Selecting Allele Frequencies under Genotype Statistics now displays the minor and major alleles, in addition to their frequencies, for each genotypic marker.

» More about Regression Analysis

SVS 7.1 Release Notes

For a complete list of improvements and bug fixes in v7.1 see the Release Notes section of the SNP & Variation Suite Manual.

Virtually Unlimited Data. Unparalleled Performance

Anticipating association studies with hundreds of millions of data points generated per sample by next generation sequencing, the core architecture of SVS 7 has been completely reinvented to efficiently handle datasets of virtually any size on a desktop computer. Smart memory management and data caching ensures you will experience accelerated performance at every step.

» More about Data Management

Intelligently Redesigned Interface

Seeing is believing with an intuitive interface that puts your data in genomic context at every step. Discover how rewarding it is to navigate whole genome data live within a spreadsheet - complete with genomic annotations - or visually in a genome browser. For follow up analyses you can quickly look up significant markers in supported online databases. More consistent workflows make performing complex analyses quick, easy, and efficient.

Most Extensive Collection of Genetic Association Tests

Find more associations with the most extensive collection of genetic association tests, including allele, genotype, haplotype, copy number variation, runs of homozygosity, multi-locus, LD, and regression-based testing. Many tests can be run individually or simultaneously while also controlling for false positives by employing multiple testing corrections and permutation testing. Additional outputs of expected values enable you to generate Q-Q and P-P plots.

» More about SNP Analysis

Complete Copy Number Variation (CNV) Analysis

SVS 7 offers a complete workflow for copy number analysis and related CNV association studies. Process raw intensity data and simultaneously correct for batch effects, genomics waves and population stratification, while significantly improving signal-to-noise ratios. Employ optimal segmentation to detect copy number segment boundaries both on a per-sample (univariate) and multi-sample (multivariate) basis in the presence of mosaicism, even at a single probe level, and with controllable sensitivity and false discovery rates. Further, calculate CNV covariates for association testing and visualize copy number data in a genome browser.

» More about Copy Number Analysis

Richly Interactive Visualization

A new dynamic analytic visualization tool with integrated genome browser offers exceptional flexibility in how you visualize data and present results. Gain greater insights with unprecedented whole genome views and navigation control. Apply data transformations or analytic functions in real-time. When you finalize the view you want, save your plots to a number of publication quality formats, including scalable vector graphics.

» More about Visualization Capabilities

Robust Quality Assurance

Having collaborated on over twenty SNP and CNV genome-wide association studies, we understand how critical high quality data is for achieving quality results. Therefore, considerable effort has been made to enhance quality assurance at every step. You can now easily generate a number of genotype statistics, view cluster plots of allele intensities, check gender and marker concordance, perform variance analysis on log ratios, filter poor quality markers and samples, and more

» More about Quality Assurance

Batch Effect, Genomic Wave, and Stratification Correction

In addition to standard quality assurance measures, SVS 7 offers a powerful principal component analysis (PCA) approach for both SNP and CNV data to simultaneously correct for batch effects, genomic waves, and population stratification. New enhancements include streamlined plotting of principal components and the ability to correct data using pre-computed principal components from a subset of markers (e.g. ancestry informative markers).

» More about Principal Component Analysis

Real-Time Editing, Manipulation, and Enrichment

The sheer size and complexity of whole genome data makes it extremely difficult to work with. SVS 7 eliminates the hassles with real-time spreadsheet manipulation, data editing, and enrichment. Easily combine multiple sample sets and data of different types, from different arrays, or even platforms. Quickly recode genotypes based on a specified genetic model, flip DNA strands, transcode from AB to AGCT formats, and more. Further, an integrated spreadsheet editor facilitates data editing and transformation on a grand scale.

» More about Data Editing and Manipulation

Advanced Regression

An advanced regression module allows you to perform linear and logistic regression, stepwise regression (both backward elimination and forward selection), and permutation tests with numeric variables and recoded genotypes. Use a moving window along with numeric or categorical covariates, against a single dependent variable. Regressions may either be performed with all variables and covariates together (“full model”) or with some of the covariates grouped into a “reduced model” (yielding a full-vs-reduced model p-value).

» More about Regression Analysis

Fully Programmatic Scripting and Automation

Automate workflows, incorporate custom methods, or interoperate with other programs. These are just a few examples of how you can enhance the utility of SVS 7 with a fully programmatic Python scripting interface. New to SVS 7 is an integrated Python script editor that makes it easy to read and write scripts helping even novice users realize the power of scripting.

» More about Scripting and Automation