Myriad Women's Health, Inc.

Myriad Genetics, Inc.

Counsyl, Inc.

Kevin R Haas

Xin Ru Wang

Kyle Allen Lapham

Dale E Muzzey

Kevin M D'Auria

Christopher Wong

Kyle Beauchamp

Peter Turner

Jeffrey R Tratner

Peter V Grauman

Ethan Nash

Sun Hong

A system and method for determining a respective carrier status of an individual is provided. In one implementation, a method includes training a neural network model based on predetermined information related to at least one genetic variant and determining the respective carrier status based on a normalized read depth for the gene in a genome of the individual and allele dosage data for the gene using a machine learning algorithm. The method is configured to receive, as inputs, the normalized read depth and allele dosage data, and output the respective carrier status of the individual for the at least one genetic variant. In another implementation a system includes a recurrent neural network. The recurrent neural network includes a plurality of long short-term memory (LSTM) network cells linked sequentially in the recurrent neural network, a plurality of layers of long short-term memory (LSTM) network cells; and a fully connected sigmoid module.

Deep learning based variant calling using machine learning

Fetal maternal samples taken from pregnant women include both maternal cell-free DNA and fetal cell-free DNA. Described herein are methods for determining a chromosomal abnormality of a test chromosome in a fetus by analyzing a test maternal sample of a woman carrying said fetus, wherein the test maternal sample comprises fetal cell-free DNA and maternal cell-free DNA. The chromosomal abnormality can be, for example, aneuploidy or the presence of a microdeletion. In some embodiments, the chromosomal abnormality is determined by measuring a dosage of the test chromosome, determining a depth-scaled variation value correlated to an initial number of sequencing reads obtained from an assay of the test maternal sample, and determining an initial value of statistical significance for the test chromosome based on the measured dosage of the test chromosome, an expected dosage of the test chromosome, and the depth-scaled variation value.

Noninvasive prenatal screening using dynamic iterative depth optimization with depth-scaled variance determination

Direct targeted sequencing (DTS) methods and a hidden Markov model (HMM) can be used to call the copy number of a segment of interest within a region of interest. Described herein are methods for calling a copy number variant or a copy number variant abnormality using an HMM, and methods for determining a copy number based on a copy number likelihood model, in a test sequencing library that has be sequenced using DTS methods. Also described herein are methods for determining a copy number of a segment, including accounting for spurious capture probes that may arise from the DTS methods.

Copy number variant caller

A robotic system is provided for accurately and quickly sorting sample tubes within or between sample tube racks.

Robotic system for sorting sample tubes

Growing community of inventors

Berkeley, CA, United States of America

Kevin R Haas