Category Archives: How to’s and advanced workflows

Top-Quality GWAS Analysis: Part IV

Population Stratification This article is going to cover how to factor for population stratification in your association test to continue our blog series on top quality GWAS analysis (additional articles for this series are located at the bottom of this blog). Quality control steps up to this point have included assessing sample and marker statistics, LD pruning on markers, and… Read more »

Top-Quality GWAS Analysis: Part III

      Eli Sward    January 22, 2019    No Comments on Top-Quality GWAS Analysis: Part III

Sample Relatedness Pruning your data based on Linkage Disequilibrium (LD) values and filtering for sample “relatedness” are ideal quality assurance steps following the marker and sample quality filtering described in Part II of this blog series. The value of running an Identity by Decent estimation not only allows you to factor family relatedness in your samples but makes screening for… Read more »

Top-Quality GWAS Analysis: Part II

Eliminate Low-Quality Samples and Markers In Part I of this GWAS Analysis series, Dr. Eli Sward provided us with a great overview on the value SVS provides in managing the quality of your SNP or NGS data to maintain the high power and accuracy of your GWAS. He also gave a snapshot of what a typical genotype spreadsheet may look… Read more »

Considerations When Calling CNVs on Shallow Whole Genomes

CNV Annotations

We are happy to announce that our latest version of SVS includes the ability to call CNVs on low read depth Whole Genome Sequencing (WGS) data. Designed for calling large cytogenetic events, this algorithm can detect chromosomal aneuploidy events and other large events spanning one or more bands of a chromosome from genomes with average coverage as low as 0.05x…. Read more »

VarSeq PhoRank Part: 2 Sample PhoRank Gene Ranking

The PhoRank tool in VarSeq is further explored in this post by looking at the sample-specific capability. VarSeq PhoRank Part: 1 Variant Phorank Gene Ranking showed how the PhoRank algorithm could be applied to all the variants in a VarSeq project, regardless of the number of (or difference in) samples. There is another PhoRank algorithm in VarSeq that allows the… Read more »