Abstract: Disclosed herein are methods and systems of utilizing sequencing reads for detecting and quantifying the presence of a tissue type or a disease type in cell-free DNA prepared from blood samples.

Abstract: Disclosed herein are methods and systems of utilizing sequencing reads for detecting and quantifying the presence of a tissue type or a disease type in cell-free DNA prepared from blood samples.

Abstract: The present disclosure provides methods and compositions for preparation of a nucleic acid library. In some embodiments, the nucleic acids comprise cell-free DNA, including cfDNA that is in need of analysis, such as by sequencing. The methods may comprise restriction enzyme digestion, adapter ligation, and subsequent amplification, and may provide improved approaches for reducing the number adapter dimers produced during the process. In an aspect, a method for preparing a library of nucleic acids may comprise: digesting DNA molecules with restriction enzymes to produce DNA fragments; ligating adapters to the DNA fragments by incubating with ligase to produce a mixture of adapter-ligated DNA fragments and adapter dimers; amplifying the adapter-ligated DNA fragments to produce amplified adapter-ligated DNA fragments; and reducing the quantity of the adapter dimers by differentiating between the junction between an adapter and a DNA fragment, and the junction between an adapter and another adapter.

Abstract: The present disclosure provides methods and systems for detecting or inferring levels of Copy Number Variants (CNVs) in cell-free nucleic acid samples to detect or assess cancer and prenatal diseases. Cell-free nucleic acid methylation sequencing data may be utilized to distinguish tumor-derived or fetal-derived sequencing reads from normal cfDNA sequencing reads. Each cell-free nucleic acid sequencing read (e.g., containing tumor or fetal methylation markers) may be classified as corresponding to a tumor/fetal-derived or a normal-plasma cell-free nucleic acid, based on the methylation cfDNA sequencing data (e.g., obtained using Bisulfite sequencing or bisulfite-free sequencing methods) and tumor/fetal methylation markers. Next, a profile of the tumor/fetal-derived sequencing read counts may be constructed and then normalized. The CNV status (e.g., gain or loss) of each genomic region may be inferred, and a diagnosis or prognosis can be made based on a subjects inferred CNV profile.

Abstract: The present disclosure provides a probabilistic model for accurate and sensitive somatic single nucleotide variant (SNV) detection in cell-free nucleic acid samples comprising a set of sequence data. A joint genotype may be determined for each locus in the set of sequence data, and germline mutations may be intrinsically removed. A set of filtrations can be applied to eliminate low quality somatic variant calls. Further, a global tumor cell-free deoxyribonucleic acid (cfDNA) fraction and overlapping read mates can be considered, thereby enabling accurate SNV detection and variant allele frequency estimation from samples with low tumor cfDNA fraction. A sensitive early detection of minimal residual disease (MRD) is designed by using the probabilistic model and the machine learning model for distinguishing true variants from sequencing errors.

Abstract: Disclosed herein are methods and systems of utilizing sequencing reads for detecting and quantifying the presence of a tissue type or a disease type in cell-free DNA prepared from blood samples.