Classification trees¶

In order to end up with a small list of candidate variant records for interpretation VIP performs variant filtration by:

1. Classify all variant-consequences based on variant annotations
2. Remove variant-consequences based on their classes
3. Annotate remaining variant records using inheritance matcher
4. Classify all variant-consequences based on variant annotations in the context of samples
5. Remove variant-consequences based on their classes.
6. Remove variants that had all their variant-consequences removed

The following sections describe the default variant filtration strategies and how to customize classification and filtration.

Default¶

VIP contains default filtration strategies for variant-consequences as well as variant-consequences in the context of samples.

Variant-consequences¶

The default decision tree to classify variant-consequences works as follows:

1. Each variant-consequence is classified as Benign, Likely Benign, VUS, Likely Pathogenic, Pathogenic or Remove
2. Variant-consequences classified as Benign, Likely Benign and Remove are removed

Above: default GRCh38 variant classification tree

Variant-consequences (samples)¶

The default decision tree to classify variant-consequences in the context of samples works as follows:

1. Each variant-consequence-sample is classified as U1 (usable: probably), U2 (usable: maybe) and U3 (usable: probably not)
2. Variant-consequences classified as U3 for all samples are removed

Above: default variant sample classification tree

Customization¶

The default variant filtration strategy can be customized using the following parameters (see here):

• vcf.classify.GRCh38.decision_tree
• vcf.filter.classes
• vcf.classify_samples.GRCh38.decision_tree
• vcf.filter_samples.classes

The following repositories might be of interest when creating a new decision tree:

• vip
• vip-decision-tree

You are free to use your own set of classes in your decision tree. Keep in mind to update the filter classes parameters accordingly.