Methods and processes for non invasive assessment of a genetic variation
AssigneeSequenom, Inc.
InventorsLin Tang, Cosmin Deciu
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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.
Claims23
1-63. (canceled)
A method for non-invasive prenatal assessment of a fetal genetic variation comprising:
- (a) obtaining genomic nucleic acid sequence information of a sample from a subject and obtaining genomic nucleic acid sequence information of a biological specimen from one or more reference persons;
- (b) identifying one or more dissimilarities for a feature between a subject data set and a reference data set by a statistical analysis wherein the subject data set comprises genomic nucleic acid sequence information of the sample from the subject and the reference data set comprises genomic nucleic acid sequence information of the biological specimen from the one or more reference persons, wherein the statistical analysis is a paired t-test;
- (c) generating, using a microprocessor, a multidimensional matrix from the dissimilarities;
- (d) reducing the multidimensional matrix into a reduced data set representation of the matrix;
- (e) classifying into one or more groups the reduced data set representation by one or more linear modeling analysis algorithms thereby providing a classification;
- and
- (f) determining the presence or absence of a fetal genetic variation for the sample based on the classification, wherein a statistical sensitivity and a statistical specificity is determined from the classification.
The method of claim 63, wherein reducing the multidimensional matrix in (d) comprises employing one or more of metric and non-metric multi-dimensional scaling, Sammon's non-linear mapping, principle component analysis and combinations thereof.
Dependencies are inferred from the claim text.