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.
Abstract:
Provided herein are methods, processes and apparatuses for non-invasive assessment of genetic variations that make use of nucleic acid fragments from circulating cell free nucleic acid. Also provided herein are methods for partitioning one or more genomic regions of a reference genome into a plurality of portions according to one or more features.
Abstract:
Provided in part herein are methods and processes that can be used for non-invasive assessment of a genetic variation which can lead to diagnosis of a particular medical condition or conditions. Such methods and processes can, for example, identify dissimilarities or similarities for one or more features between a subject data set and a reference data set, generate a multidimensional matrix, reduce the matrix into a representation and classify the representation into one or more groups. Methods and processes described herein are applicable to data in biotechnology and other fields.
Abstract:
Provided herein are methods, processes and apparatuses for non-invasive assessment of genetic variations that make use of nucleic acid fragment length information.