Systems and methods for diagnosing a disease or a condition

The method of any one of claims 1-42, further comprising filtering the plurality of alternative splicing events using a forward selection procedure comprising:

• obtaining a ranked sequence of alternative splicing events by ranking the plurality of alternative splicing events by their respective coefficients of effect;
• initializing a filtered subset of alternative splicing events with the highest ranked alternative splicing event in the ranked sequence of alternative splicing events;
• and
• performing a plurality of iterations, each respective iteration in the plurality of iterations comprising, for each respective alternative splicing event that is the next highest ranked alternative splicing event in the ranked sequence of alternative splicing events:
• obtaining a respective evaluation set of alternative splicing events comprising the respective alternative splicing event and the filtered subset of alternative splicing events,
• for each respective validation subject in a plurality of validation subjects:
• (i) for each respective alternative splicing event in the evaluation set of alternative splicing events, determining at least a corresponding fifth abundance metric for the respective alternative splicing event in a biological sample of the respective validation subject, and
• (ii) receiving, responsive to inputting the corresponding fifth abundance metric for each respective alternative splicing event in the evaluation set of alternative splicing events into the first model, a predicted infection status of the respective validation subject as output from the first model, and
• using the predicted infection status for each respective validation subject in the plurality of validation subjects to determine a corresponding evaluation metric for the respective evaluation set of alternative splicing events, wherein:
• when the corresponding evaluation metric satisfies a filtering criterion, adding the respective alternative splicing event to the filtered subset of alternative splicing events and performing a subsequent iteration in the plurality of iterations, and
• when the corresponding evaluation metric fails to satisfy the filtering criterion, ending the plurality of iterations thereby obtaining the filtered subset of alternative splicing events.

A computer system for determining an infection status of a test subject, the computer system comprising:

• one or more processors;
• and
• memory addressable by the one or more processors, the memory storing at least one program for execution by the one or more processors, the at least one program comprising instructions for:
• a) obtaining, in electronic form, a plurality of sequence reads from a biological sample of the test subject, wherein the plurality of sequence reads comprises at least 10,000 RNA sequence reads;
• b) determining, for each respective alternative splicing event in a plurality of alternative splicing events a corresponding first abundance metric of the respective alternative splicing event, wherein:
• each respective alternative splicing event in the plurality of alternative splicing events corresponds to a respective locus in a plurality of loci in a reference genome for the species of the test subject, and
• the plurality of alternative splicing events comprises at least 10 alternative splicing events;
• and
• c) receiving, responsive to inputting the corresponding first abundance metric for each respective alternative splicing event in the plurality of alternative splicing events into a first model, a predicted infection status of the test subject as output from the first model.

A non-transitory computer readable storage medium, wherein the non-transitory computer readable storage medium stores instructions, which when executed by a computer system, cause the computer system to perform a method for determining an infection status of a test subject, the method comprising:

• a) obtaining, in electronic form, a plurality of sequence reads from a biological sample of the test subject, wherein the plurality of sequence reads comprises at least 10,000 RNA sequence reads;
• b) determining, for each respective alternative splicing event in a plurality of alternative splicing events a corresponding first abundance metric of the respective alternative splicing event, wherein:
• each respective alternative splicing event in the plurality of alternative splicing events corresponds to a respective locus in a plurality of loci in a reference genome for the species of the test subject, and
• the plurality of alternative splicing events comprises at least 10 alternative splicing events;
• and
• c) receiving, responsive to inputting the corresponding first abundance metric for each respective alternative splicing event in the plurality of alternative splicing events into a first model, a predicted infection status of the test subject as output from the first model.

A method for determining a COVID-19 status of a test subject, the method comprising:

• at a computer system comprising one or more processors and a memory storing at least one program for execution by the one or more processors:
• a) obtaining, in electronic form, a plurality of sequence reads from a biological sample of the test subject;
• b) determining, for each respective alternative splicing event in a plurality of alternative splicing events a corresponding first abundance metric of the respective alternative splicing event, wherein:
• each respective alternative splicing event in the plurality of alternative splicing events corresponds to a respective locus in a plurality of loci in a reference genome for the species of the test subject, and
• the plurality of alternative splicing events consists of between 2 and 27 splicing events listed in Table 2;
• and
• c) receiving, responsive to inputting the corresponding first abundance metric for each respective alternative splicing event in the plurality of alternative splicing events into a first model, a predicted infection status of the test subject as output from the first model.

A method for determining a COVID-19 status of a test subject, the method comprising:

• at a computer system comprising one or more processors and a memory storing at least one program for execution by the one or more processors:
• a) obtaining, in electronic form, a plurality of sequence reads from a biological sample of the test subject;
• b) determining, for each respective alternative splicing event in a plurality of alternative splicing events a corresponding first abundance metric of the respective alternative splicing event, wherein:
• each respective alternative splicing event in the plurality of alternative splicing events corresponds to a respective locus in a plurality of loci in a reference genome for the species of the test subject, and
• the plurality of alternative splicing events consists of between 2 and 50 splicing events listed in Table 4;
• and
• c) receiving, responsive to inputting the corresponding first abundance metric for each respective alternative splicing event in the plurality of alternative splicing events into a first model, a predicted infection status of the test subject as output from the first model.