Genetic Copy Number Alteration Classifications
AssigneeSequenom, Inc.
InventorsAmin Mazloom, Cosmin Deciu, Chen Zhao, Tong Liu, Yijin Wu
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Abstract
Technology provided herein relates in part to non-invasive classification of one or more genetic copy number alterations (CNAs) for a test sample. Certain methods include sampling a quantification of sequence reads from parts of a genome, generating a confidence determination, and using the confidence determination to enhance classification. Technology provided herein is useful for classifying a genetic CNA for a sample as part of non-invasive pre-natal (NIPT) testing and oncology testing, for example.
Claims20
A method comprising:
- selecting, by a computing device, a set of genomic portions each coupled to a sequence read quantification for a test sample, wherein:
- the set of genomic portions comprise portions of a reference genome to which sequence reads obtained for sample nucleic acid from the test subject have been mapped,
- the set of genomic portions comprise (i) genomic portions within a candidate region identified as a candidate copy number variation region, and/or (ii) genomic portions outside the candidate region and within a selected region larger than the candidate region that includes the candidate region, and
- the candidate region is a chromosome or sub-chromosome region;
- shifting, by the computing device, a quantification of the sequence reads mapped to the genomic portions for the candidate region at or near a quantification of sequence reads mapped to genomic portions outside the candidate region and within the selected region;
- sampling, by the computing device, the genomic portions from the selected region, wherein a number of sampled genomic portions is about equal to a number of genomic portions in the candidate region, thereby generating a sampled region, and repeating the sampling to generate a plurality of sampled regions;
- normalizing, by the computing device, a sequence read quantification for each of the sampled regions, thereby generating a normalized quantification for each of the sampled regions;
- generating, by the computing device, a confidence determination for the candidate region by a process comprising comparing each normalized quantification to a measure of variability of sequence read quantifications for the candidate region for reference samples not having a significant copy number variation in the candidate region;
- and
- providing a classification for presence or absence of the copy number variation for the candidate region for the test sample according to the confidence determination.
A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, including instructions configured to cause one or more data processors to perform actions including:
- selecting a set of genomic portions each coupled to a sequence read quantification for a test sample, wherein:
- the set of genomic portions comprise portions of a reference genome to which sequence reads obtained for sample nucleic acid from the test subject have been mapped,
- the set of genomic portions comprise (i) genomic portions within a candidate region identified as a candidate copy number variation region, and/or (ii) genomic portions outside the candidate region and within a selected region larger than the candidate region that includes the candidate region, and
- the candidate region is a chromosome or sub-chromosome region;
- shifting a quantification of the sequence reads mapped to the genomic portions for the candidate region at or near a quantification of sequence reads mapped to genomic portions outside the candidate region and within the selected region;
- sampling the genomic portions from the selected region, wherein a number of sampled genomic portions is about equal to a number of genomic portions in the candidate region, thereby generating a sampled region, and repeating the sampling to generate a plurality of sampled regions;
- normalizing a sequence read quantification for each of the sampled regions, thereby generating a normalized quantification for each of the sampled regions;
- generating a confidence determination for the candidate region by a process comprising comparing each normalized quantification to a measure of variability of sequence read quantifications for the candidate region for reference samples not having a significant copy number variation in the candidate region;
- and
- providing a classification for presence or absence of the copy number variation for the candidate region for the test sample according to the confidence determination.
A system comprising:
- one or more data processors;
- and
- a non-transitory computer readable storage medium containing instructions which, when executed on the one or more data processors, cause the one or more data processors to perform actions comprising:
- selecting a set of genomic portions each coupled to a sequence read quantification for a test sample, wherein:
- the set of genomic portions comprise portions of a reference genome to which sequence reads obtained for sample nucleic acid from the test subject have been mapped,
- the set of genomic portions comprise (i) genomic portions within a candidate region identified as a candidate copy number variation region, and/or (ii) genomic portions outside the candidate region and within a selected region larger than the candidate region that includes the candidate region, and
- the candidate region is a chromosome or sub-chromosome region;
- shifting a quantification of the sequence reads mapped to the genomic portions for the candidate region at or near a quantification of sequence reads mapped to genomic portions outside the candidate region and within the selected region;
- sampling the genomic portions from the selected region, wherein a number of sampled genomic portions is about equal to a number of genomic portions in the candidate region, thereby generating a sampled region, and repeating the sampling to generate a plurality of sampled regions;
- normalizing a sequence read quantification for each of the sampled regions, thereby generating a normalized quantification for each of the sampled regions;
- generating a confidence determination for the candidate region by a process comprising comparing each normalized quantification to a measure of variability of sequence read quantifications for the candidate region for reference samples not having a significant copy number variation in the candidate region;
- and
- providing a classification for presence or absence of the copy number variation for the candidate region for the test sample according to the confidence determination.
Dependencies are inferred from the claim text.