Abstract: The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein are methods of designing, making, and using the cancer assay panel for the diagnosis of cancer.

Abstract: An analytics system marks duplicate fragments from an initial set of fragments from a subject. The analytics system generates a sample state vector for each fragment. Each sample state vector comprises a sample genomic location within a reference genome and a plurality of methylation states for a plurality of CpG sites in the fragment, the methylation states determined to be one of methylated, unmethylated, variant, and ambiguous. The analytics system identifies two fragments with methylation state vectors as being derived from a matching reference location, e.g., sharing a common plurality of CpG sites. The analytics system calculates a modified Hamming distance based on methylation states in the first sample state vector and methylation states in the second sample state vector. Based on the modified Hamming distance, the analytics system marks the first fragment and the second fragment as either duplicate fragments or non-duplicate fragments.

Abstract: Methods and systems for detecting contaminated fragments in a biological sample for cancer classification are disclosed. The system identifies CpG-SNP contamination markers. The CpG-SNP contamination markers include at least one SNP that affects a CpG site. The CpG-SNP contamination markers may include additive CpG-SNP sites and/or subtractive CpG-SNP sites. Additive CpG-SNP sites include an SNP that creates a new CpG site. Subtractive CpG-SNP sites include an SNP that removes a preexisting CpG site. Hybrid sites may include additional sites. A multiple CpG-SNP contamination marker comprises two or more CpG-SNP sites. A CpG-SNP & indel contamination marker comprises at least one CpG-SNP site and an indel site. For a given sample, the system identifies contamination markers for which the sample is homozygous. The system determines fragments having a haplotype that is different from the homozygous haplotype of the sample to be contamination fragments.

Abstract: Techniques for determining whether a public encryption key is vulnerable as the result of deficiencies in pseudorandom number generation algorithms are provided. In some embodiments, a system may compile a database of cryptographic information received from a plurality of sources, including databases, and network traffic monitoring tools. RSA public keys extracted from the cryptographic information may be stored in an organized database in association with corresponding metadata. The system may construct a product tree from all unique collected RSA keys, and may then construct a remainder tree from the product tree, wherein each output remainder may be determined to be a greatest common divisor of one of the RSA keys against all other unique RSA keys in the database. The system may then use the greatest common divisors to factor one or more of the RSA keys and to determine that the factored keys are vulnerable to being compromised.

Abstract: The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein are methods of designing, making, and using the cancer assay panel for the diagnosis of cancer.

Abstract: An analytics system marks duplicate fragments from an initial set of fragments from a subject. The analytics system generates a sample state vector for each fragment. Each sample state vector comprises a sample genomic location within a reference genome and a plurality of methylation states for a plurality of CpG sites in the fragment, the methylation states determined to be one of methylated, unmethylated, variant, and ambiguous. The analytics system identifies two fragments with methylation state vectors as being derived from a matching reference location, e.g., sharing a common plurality of CpG sites. The analytics system calculates a modified Hamming distance based on methylation states in the first sample state vector and methylation states in the second sample state vector. Based on the modified Hamming distance, the analytics system marks the first fragment and the second fragment as either duplicate fragments or non-duplicate fragments.

Abstract: Methods and systems for detecting contaminated fragments in a biological sample for cancer classification are disclosed. The system identifies multiple SNP site contamination markers and indel site contamination markers. The multiple SNP site contamination markers include at least two SNP sites within a threshold distance, having population haplotype frequency within a range of threshold frequencies, excluding guanine-adenine polymorphisms and/or cytosine-thymine polymorphisms, ensuring Hardy-Weinberg equilibrium, or any combination of the parameters above. The indel site contamination markers include indel sequences that are within a threshold length, having high complexity, having population haplotype frequency within a range of threshold frequencies, ensuring Hardy-Weinberg equilibrium, or any combination of the parameters above. The system identifies contamination markers for which the sample is homozygous.

Abstract: The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein are methods of designing, making, and using the cancer assay panel for the diagnosis of cancer.

Abstract: The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein are methods of designing, making, and using the cancer assay panel for the diagnosis of cancer.

Abstract: Technical solutions for classifying patients with respect to multiple cancer classes are provided. The classification can be done using cell-free whole genome sequencing information from subjects. A reference set of subjects is used to train classifiers to recognize genomic markers that distinguish such cancer classes. The classifier training includes dividing the reference genome into a set of non-overlapping bins, applying a dimensionality reduction method to obtain a feature set, and using the feature set to train classifiers. For subjects with unknown cancer class, the trained classifiers provide probabilities or likelihoods that the subject has a respective cancer class for each cancer in a set of cancer classes. The present disclosure thus describes methods to improve the screening and detection of cancer class from among several cancer classes. This serves to facilitate early and appropriate treatment for subjects afflicted with cancer.

Abstract: The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein are methods of designing, making, and using the cancer assay panel for the diagnosis of cancer.

Abstract: Techniques for determining whether a public encryption key is vulnerable as the result of deficiencies in pseudorandom number generation algorithms are provided. In some embodiments, a system may compile a database of cryptographic information received from a plurality of sources, including databases, and network traffic monitoring tools. RSA public keys extracted from the cryptographic information may be stored in an organized database in association with corresponding metadata. The system may construct a product tree from all unique collected RSA keys, and may then construct a remainder tree from the product tree, wherein each output remainder may be determined to be a greatest common divisor of one of the RSA keys against all other unique RSA keys in the database. The system may then use the greatest common divisors to factor one or more of the RSA keys and to determine that the factored keys are vulnerable to being compromised.

Abstract: Technical solutions for classifying patients with respect to multiple cancer classes are provided. The classification can be done using cell-free whole genome sequencing information from subjects. A reference set of subjects is used to train classifiers to recognize genomic markers that distinguish such cancer classes. The classifier training includes dividing the reference genome into a set of non-overlapping bins, applying a dimensionality reduction method to obtain a feature set, and using the feature set to train classifiers. For subjects with unknown cancer class, the trained classifiers provide probabilities or likelihoods that the subject has a respective cancer class for each cancer in a set of cancer classes. The present disclosure thus describes methods to improve the screening and detection of cancer class from among several cancer classes. This serves to facilitate early and appropriate treatment for subjects afflicted with cancer.

Abstract: The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein are methods of designing, making, and using the cancer assay panel for the diagnosis of cancer.

Abstract: Techniques for determining whether a public encryption key is vulnerable as the result of deficiencies in pseudorandom number generation algorithms are provided. In some embodiments, a system may compile a database of cryptographic information received from a plurality of sources, including databases, and network traffic monitoring tools. RSA public keys extracted from the cryptographic information may be stored in an organized database in association with corresponding metadata. The system may construct a product tree from all unique collected RSA keys, and may then construct a remainder tree from the product tree, wherein each output remainder may be determined to be a greatest common divisor of one of the RSA keys against all other unique RSA keys in the database. The system may then use the greatest common divisors to factor one or more of the RSA keys and to determine that the factored keys are vulnerable to being compromised.

Abstract: Disclosed herein are systems and methods for localization of a disease state (e.g., tissue of origin of cancer) using nucleic acid samples. In an embodiment, a method comprises receiving a plurality of cancer signals of a sample, each cancer signal indicating a probability that the sample is associated with a different disease state of a plurality of disease states. The method determines a first cancer signal having a greatest probability among the plurality of cancer signals. In accordance with a determination that the first cancer signal satisfies a criterion, the method associates the sample with a first disease state. In accordance with a determination that the first cancer signal does not satisfy the criterion, the method determines a second cancer signal having a second greatest probability among the plurality of cancer signals, and associates the sample with the first disease state and a second disease state.

Abstract: The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein are methods of designing, making, and using the cancer assay panel for the diagnosis of cancer.

Abstract: The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein includes methods of designing, making, and using the cancer assay panel to detect cancer and particular types of cancer.

Abstract: The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein includes methods of designing, making, and using the cancer assay panel for detection of cancer tissue of origin (e.g., types of cancer).

Abstract: The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein includes methods of designing, making, and using the cancer assay panel to detect cancer and particular types of cancer.