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 dissimiliarities 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:
A method and system for analyzing circulating cell-free nucleic acids from a pregnant female with reduced bias. Counts of sequence reads mapped to portions of a reference genome are obtained. A regression model is generated that models the relationship between the counts and the GC content. The read counts are normalized according to the regression model to remove the GC bias. The normalized counts are used for further analysis, such as the detection of fetal aneuploidy.
Abstract:
Methods for non-invasive assessment of genetic variations that make use of nucleic acid fragment length information, in particular length of fragments in circulating cell-free nucleic acids and compares the number of counts from fragments with different length.
Abstract:
Provided herein are methods, processes and apparatuses for non-invasive assessment of genetic variations that make use of nucleic acid fragment length information.