SVS 8.3.1 Release Notes

Bugs Fixed

  • Fixed Python error in KBAC with Regression when selecting No but precompute reduced models… for the Impute Wild Type… option.
  • SKAT-O bugs fixed:
    • Analysis will now run with the “Uniform” parameter selected for Marker Weighting.
    • Fixed index error that occurred when there were regions in the data with more markers than samples available, script now correctly skips over these regions.
  • On Mac OSX, fixed the bug that prevented scripts from being launched from submenus in the project navigator or from a spreadsheet.
  • Fixed handling of missing covariate information in Bayesian Genomic Prediction when “Predict random effects for samples with missing phenotypes” is selected.
  • GenomeBrowse bugs fixed:
    • Clicking on a folder URL now launches a file explorer window at that location instead of trying to launch and failing.
    • Fixed console information for categorical array fields to have the correct size instead of a list of missing values.
    • In the Expression Editor, the “Chr” field is now correctly handled as a string and the “Start” and “Stop” fields are correctly handled as integers. This will now allow you to add expressions such as “Chromosome”, “Start”, “Stop”, “Stop – Start <= 2”, etc.


  • File > Apply Genetic Marker Map is now case insensitive for matching marker names.
  • Updated DNA-Seq > Annotate and Filter Variants:
    • dbNSFP default options set to handle filtering of the 5 common scores.
    • Added support for new frequency data (1kG Phase3 and ExAC), so now able to filter based on unique Ref/Alt allele matching in a list of frequency values.
  • KBAC with Regression and CMC with Regression scripts now include the option to output the intermediate variables used in the calculations.
  • Updates to SKAT-O:
    • Included option for Madsen Browning weighting which assigns more weight to rare variants than common variants.
    • Allow rho of exactly one for generalized SKAT test.
  • Added option in Import > PED/TPED/BED and Export > PED/TPED/BED for PLINK import and export to keep chromosome names “as is”. This allows importing data in PLINK format from genomes that have chromosomes with non-numeric names. Made PED and TPED export also map non-autosomes to numeric chromosome identifiers if not exporting “as is”.
  • Always standardize phenotype values for Bayesian Genomic Prediction to make the method more robust.

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