Bypassing sanger confirmation for small variants in genetic disorder clinical testing

A computer-implemented method comprising:

• performing next generation sequencing (NGS) on nucleic acid obtained from a biological sample of a subject to generate sequencing data;
• extracting information of a set of variants from the sequencing data, wherein the information of the set of variants comprises a type of each variant in the set of variants and one or more quality features of each variant in the set of variants;
• clustering the set of variants into one or more subsets of variants based on the type of each variant in the set of variants;
• generating, using a first machine learning model, a predicted status of each variant in at least one subset of the one or more subsets of variants based on the one or more quality features, wherein the predicted status is a presence status, an absence status, or an unknown status;
• generating, using a second machine learning model, a confirmatory status of each variant with the unknown status as the predicted status, wherein the confirmatory status is a presence status or an absence status;
• and
• performing Sanger sequencing on nucleic acid molecules comprising variants with the absence status as the predicted status or the confirmatory status to confirm an existence of the variants.

A system comprising:

• one or more data processors;
• and
• a non-transitory computer readable medium storing instructions which, when executed on the one or more data processors, cause the one or more data processors to perform operations comprising:
• performing next generation sequencing (NGS) on nucleic acid obtained from a biological sample of a subject to generate sequencing data;
• extracting information of a set of variants from the sequencing data, wherein the information of the set of variants comprises a type of each variant in the set of variants and one or more quality features of each variant in the set of variants;
• clustering the set of variants into one or more subsets of variants based on the type of each variant in the set of variants;
• generating, using a first machine learning model, a predicted status of each variant in at least one subset of the one or more subsets of variants based on the one or more quality features, wherein the predicted status is a presence status, an absence status, or an unknown status;
• generating, using a second machine learning model, a confirmatory status of each variant with the unknown status as the predicted status, wherein the confirmatory status is a presence status or an absence status;
• and
• performing Sanger sequencing on nucleic acid molecules comprising variants with the absence status as the predicted status or the confirmatory status to confirm an existence of the variants.

A computer-program product tangibly embodied in a non-transitory machine-readable medium, including instructions configured to cause one or more data processors to perform operations comprising:

• performing next generation sequencing (NGS) on nucleic acid obtained from a biological sample of a subject to generate sequencing data;
• extracting information of a set of variants from the sequencing data, wherein the information of the set of variants comprises a type of each variant in the set of variants and one or more quality features of each variant in the set of variants;
• clustering the set of variants into one or more subsets of variants based on the type of each variant in the set of variants;
• generating, using a first machine learning model, a predicted status of each variant in at least one subset of the one or more subsets of variants based on the one or more quality features, wherein the predicted status is a presence status, an absence status, or an unknown status;
• generating, using a second machine learning model, a confirmatory status of each variant with the unknown status as the predicted status, wherein the confirmatory status is a presence status or an absence status;
• and
• performing Sanger sequencing on nucleic acid molecules comprising variants with the absence status as the predicted status or the confirmatory status to confirm an existence of the variants.