b57054c63c
-- For very large whole genome datasets with over 2M variants overlapping the training data randomly downsample the training set that gets used to build the Gaussian mixture model. -- Annotations are ordered by the difference in means between known and novel instead of by their standard deviation. -- Removed the training set quality score threshold. -- Now uses 2 gaussians by default for the negative model. -- Num bad argument has been removed and the cutoffs are now chosen by the model itself by looking at the LOD scores. -- Model plots are now generated much faster. -- Stricter threshold for determining model convergence. -- All VQSR integration tests change because of these changes to the model. -- Add test for downsampling of training data. |
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| .. | ||
| annotator | ||
| beagle | ||
| bqsr | ||
| compression/reducereads | ||
| diagnostics | ||
| diffengine | ||
| fasta | ||
| filters | ||
| genotyper | ||
| haplotypecaller | ||
| indels | ||
| phasing | ||
| validation | ||
| varianteval | ||
| variantrecalibration | ||
| variantutils | ||