Methods and systems for determining variant properties using machine learning

A system comprising:

• one or more processors;
• and
• a memory communicatively coupled to the one or more processors and configured to store instructions that, when executed by the one or more processors, cause the system to perform a method comprising:
• receiving, at the one or more processors, sequence read data associated with a plurality of samples;
• determining, using the one or more processors, one or more feature attributes based on the sequence read data of the plurality of samples, the one or more feature attributes associated with one or more input features;
• categorizing, using the one or more processors, the plurality of samples into a plurality of input feature sub-types based on the one or more feature attributes, wherein an input feature of the one or more input features is associated with one or more input feature sub-types of the plurality of input feature sub-types;
• obtaining, using the one or more processors, one or more input feature values based on the plurality of input feature sub-types;
• inputting, using the one or more processors, the one or more input feature values into a statistical model;
• and
• determining, using the one or more processors, a functional status of a variant based on an output of the statistical model.

A non-transitory computer-readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by one or more processors of a system, cause the system to:

• receive sequence read data associated with a plurality of samples;
• determine one or more feature attributes based on the sequence read data of the plurality of samples, the one or more feature attributes associated with one or more input features;
• categorize the plurality of samples into a plurality of input feature sub-types based on the one or more feature attributes, wherein an input feature of the one or more input features is associated with one or more input feature sub-types of the plurality of input feature sub-types;
• obtain one or more input feature values based on the plurality of input feature sub-types;
• input the one or more input feature values into a statistical model;
• and
• determine a functional status of a variant based on an output of the statistical model.