Guardant Health, Inc.

Verinata Health, Inc.

Aqtual, Inc.

Diana Abdueva

Helmy A Eltoukhy

Darya Chudova

Stefanie Ann Ward Mortimer

Amirali Talasaz

Andrew Kennedy

Marcin Sikora

Darya I Chudova

Helmy Eltoukhy

Richard P Rava

The disclosure provides methods for processing nucleic acid populations containing different forms (e.g., RNA and DNA, single-stranded or double-stranded) and/or extents of modification (e.g., cytosine methylation, association with proteins). These methods accommodate multiple forms and/or modifications of nucleic acid in a sample, such that sequence information can be obtained for multiple forms. The methods also preserve the identity of multiple forms or modified states through processing and analysis, such that analysis of sequence can be combined with epigenetic analysis.

Methods and systems for analyzing nucleic acid molecules

The present disclosure provides a method for enriching for multiple genomic regions using a first bait set that selectively hybridizes to a first set of genomic regions of a nucleic acid sample and a second bait set that selectively hybridizes to a second set of genomic regions of the nucleic acid sample. These bait set panels can selectively enrich for one or more nucleosome-associated regions of a genome, said nucleosome-associated regions comprising genomic regions having one or more genomic base positions with differential nucleosomal occupancy, wherein the differential nucleosomal occupancy is characteristic of a cell or tissue type of origin or disease state.

Methods for multi-resolution analysis of cell-free nucleic acids

Disclosed are methods for determining copy number variation (CNV) known or suspected to be associated with a variety of medical conditions, including syndromes related to CNV of subchromosomal regions. In some embodiments, methods are provided for determining CNV of fetuses using maternal samples comprising maternal and fetal cell free DNA. Some embodiments disclosed herein provide methods to improve the sensitivity and/or specificity of sequence data analysis by removing within-sample GC-content bias. In some embodiments, removal of within-sample GC-content bias is based on sequence data corrected for systematic variation common across unaffected training samples. In some embodiments, syndrome related biases in sample data are also removed to increase signal to noise ratio. Also disclosed are systems for evaluation of CNV of sequences of interest.

Detecting fetal sub-chromosomal aneuploidies

The present disclosure provides methods and systems for various uses of cell-free nucleic acid (cfNA). Functional typing of cfNA fragmentation patterns may be utilized in the non-invasive detection, diagnosis, and monitoring of disease. One embodiment may determine a stage of cancer in a subject, the progression of cancer in a subject, or the responsiveness to treatment of a cancer in a subject. Another embodiment disclosed herein may include sequencing-free diagnostic methods.

Methods for characterizing cell-free nucleic acid fragments

Methods are provided herein to improve automatic detection of copy number variation in nucleic acid samples. These methods provide improved approaches for determining baseline copy number of genetic loci within a sample, reduce variation due to features of genetic loci, sample preparation, and probe exhaustion.

Methods to determine tumor gene copy number by analysis of cell-free DNA

Disclosed are methods for determining copy number variation (CNV) known or suspected to be associated with a variety of medical conditions. In some embodiments, methods are provided for determining copy number variation (CNV) of fetuses using maternal samples comprising maternal and fetal cell free DNA. In some embodiments, methods are provided for determining CNVs known or suspected to be associated with a variety of medical conditions. Some embodiments disclosed herein provide methods to improve the sensitivity and/or specificity of sequence data analysis by removing within-sample GC-content bias. In some embodiments, removal of within-sample GC-content bias is based on sequence data corrected for systematic variation common across unaffected training samples. Also disclosed are systems and computer program products for evaluation of CNV of sequences of interest.

Growing community of inventors

Orinda, CA, United States of America

Diana Abdueva