Abstract: 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.

Abstract: 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.

Abstract: Provided herein are computer implemented methods, systems and processes for determining a transmission metric or transmission path for related pathogens. Also provided herein is a non-transitory computer-readable storage medium with an executable program stored thereon, which program is configured to instruct a microprocessor to generate a transmission path for related pathogens.

Abstract: The present invention relates to a method for compressing genomic data, whereby the genomic data are stored in at least one data file containing at least a plurality of reads built by a genome sequencing method, whereby each read includes a mapping position, a CIGAR string and an actual sequenced nucleotide sequence as a local part of the donor genome, comprising the steps: —unwind a nucleotide sequence of a current read of one of said data files by using the mapping position and the CIGAR string of said current read, whereby said current read has at least one previous read, —compute a difference between the unwound nucleotide sequence of said current read and an unwound nucleotide sequence of at least one of said previous reads, whereby said difference contains the differences of the mapping positions and the nucleotide sequences, —pass said computed difference to an entropy coder to compress said difference, —encode said current read by the compressed difference, and —repeat the forgoing steps with said cur

Abstract: The technology disclosed presents a deep learning-based framework, which identifies sequence patterns that cause sequence-specific errors (SSEs). Systems and methods train a variant filter on large-scale variant data to learn causal dependencies between sequence patterns and false variant calls. The variant filter has a hierarchical structure built on deep neural networks such as convolutional neural networks and fully-connected neural networks. Systems and methods implement a simulation that uses the variant filter to test known sequence patterns for their effect on variant filtering. The premise of the simulation is as follows: when a pair of a repeat pattern under test and a called variant is fed to the variant filter as part of a simulated input sequence and the variant filter classifies the called variant as a false variant call, then the repeat pattern is considered to have caused the false variant call and identified as SSE-causing.

Abstract: Methods, compositions, and systems are provided for detecting one or more a bacterial vaginosis issues by characterizing the microbiome of an individual, monitoring such effects, and/or determining, displaying, or promoting a therapy for the bacterial vaginosis issue. Methods, compositions, and systems are also provided for generating and comparing microbiome composition and/or functional diversity datasets. Methods, compositions, and systems are also provided for generating a characterization model and/or therapy model for bacterial vaginosis.

Abstract: Systems and techniques for extracting information-containing payloads from DNA or other polynucleotides are provided. Decoding the sequence of payload regions from multiple polynucleotides to obtain encoded information includes sequencing the molecules with a polynucleotide sequencer. Reads generated by the polynucleotide sequencer can include information from multiple different sources mixed together. Primer sequences present in the reads identify which reads contain information from the same source. A computationally efficient technique for finding primer sequences in the reads includes comparing hashes of the reads and hashes of primer sequences to find an approximate location then computing edit distances between the primer sequences and the reads to find an exact location. Reads that include the same primer sequences may be clustered together. Sequences of the payload regions are extracted based on the locations of the primer sequences.

Abstract: In one embodiment, a method for identifying candidate sequences for genotyping a genomic sample comprises obtaining a plurality of sequence reads mapping to a genomic region of interest. The plurality of sequence reads are assembled into a directed acyclic graph (DAG) comprising a plurality of branch sites representing variation present in the set of sequence reads, each branch site comprising two or more branches. A path through the DAG comprises a set of successive branches over two or more branch sites and represents a possible candidate sequence of the genomic sample. One or more paths through the DAG are ranked by calculating scores for one or more branch sites, wherein the calculated score comprises a number of sequence reads that span multiple branch sites in a given path. At least one path is selected as a candidate sequence based at least in part on its rank.

Abstract: Presented herein are techniques for identifying and/or validating sequence variants in genomic sequence data. The techniques include generating an error rate reflective of sequence errors present in the genomic sequence data. The error rate may be used to validate potential sequence variants. The error rate may be based on errors identified during consensus sequence confirmation for sequence reads associated with individual unique molecular identifiers.

Abstract: An analytics system creates a data structure counting strings of methylation vectors from a healthy control group. The analytics system enumerates possibilities of methylation state vectors given a sample fragment from a subject, and calculates probabilities for all possibilities with a Markov chain probability. The analytics system generates a p-value score for the subject's test methylation state vector by summing the calculated probabilities that are less than or equal to the calculated probability of the possibility matching the test methylation state vector. The analytics system determines the test methylation state vector to be anomalously methylated compared to the healthy control group if the p-value score is below a threshold score. With a number of such sample fragments, the analytics system can filter the sample fragments based on each p-value score. The analytics system can run a classification model on the filtered set to predict whether the subject has cancer.

Abstract: A technique for clustering DNA reads from polynucleotide sequencing is described. DNA reads with a level of difference that is likely caused by errors in sequencing are grouped together in the same cluster. DNA reads that represent reads of different DNA molecules are placed in different clusters. The clusters are based on edit distance, which is the number of changes necessary to convert a given DNA read into another. The process of forming clusters may be performed iteratively and may use other types of distance that serve as an approximation for edit distance. Well clustered DNA reads provide a starting point for further analysis.

Abstract: Exemplary systems and methods for selecting from population of candidate edits and predicting an aggregate effect of the candidate edits are disclosed. One exemplary method includes identifying a population of candidate edits to a genomic sequence of said organism and ranking each of the candidate edits based on a predicted ability of each candidate edit to affect a trait of interest in said organism. The exemplary method further includes selecting one or more of the candidate edits based on the ranking and predicting, by the computing device, an aggregate effect of the selected one or more of the candidate edits for the trait of interest when expressed by a specimen of the organism having a genomic sequence and edited according to the selected one or more of the candidate edits, as compared to an unedited specimen of the organism.

Abstract: A genomic data analyzer may be configured to detect and characterize, with a variant calling module, genomic variant scenarios in sequencing reads from an enriched patient genomic sample comprising a combination of a first repeat pattern and a second repeat pattern, such as repeats of homopolymer (single nucleotide) and/or heteropolymer (multiple nucleotide) basic motifs. The variant calling module may estimate the probability distribution of the length of the first repeat pattern and the probability distribution of the length of the second repeat pattern by comparing the distribution of the repeat pattern length measurements in patient data to the distribution of the repeat pattern length measurements in control data, in order to remove biases possibly induced by the next generation sequencing laboratory setup both in control and patient data.

Abstract: An identification apparatus acquires a protein file in which a plurality of proteins including a plurality of amino acids are arranged. The identification apparatus identifies a plurality of primary structure candidates with any position included in the protein file as a starting position. The identification apparatus identifies one primary structure among the primary structure candidates based on a combination of a primary structure and each amino acid and a primary structure table, where the each amino acid is positioned at an end of the primary structure and the primary structure table associates a primary structure and a cooccurrence rate of a certain amino acid combination positioned at an end of the primary structure.

Abstract: Embodiments predict response to neoadjuvant chemotherapy (NAC) in breast cancer (BCa) from pre-treatment dynamic contrast enhanced magnetic resonance imaging (DCE-MRI).

Abstract: Systems, devices and methods for predicting binding on an array such as a peptide array. Certain methods utilize a peptide array having a plurality of peptides with one or more defined parameters and contacting the peptide array with a training sample containing one or more molecules of interest. Interactions between the plurality of peptides and the one or more molecules of interest are processed according to a data fitting model, which model is then is applied to interactions between the plurality of peptides and a test sample to predict binding associated with the one or more molecules of interest.

Abstract: A machine learning system and method for somatic mutation discovery are provided that provides improved identification of tumor-specific mutations. The improved identification of tumor-specific mutations may affect discovery of alterations and therapeutic management of cancer patients.

Abstract: A method and a system for calculating tumor neoantigen burden (TNB) are provided. The method includes: step S1: processing a normal sample and a tumor sample, sequencing a specific region and detecting somatic mutations in the sample; step S2: annotating and filtering the somatic mutations, and translating to obtain mutant peptide sequences of a patient; step S3: filtering the mutant peptide sequences to obtain neopeptide sequences based on a proteome of the normal sample; step S4, performing a human leukocyte antigen (HLA) typing analysis based on alignment data of the normal sample to obtain HLA genotypes of the sample; step S5, predicting binding affinities between the neopeptide sequences and the HLA genotypes to obtain specific neoantigens of the sample, and performing a weighted scoring on each of the specific neoantigens and calculating the TNB of the sample.

Abstract: A method for detecting a tandem duplication in an FLT3 gene of a sample, includes mapping reads corresponding to targeted regions of exons of the FLT3 gene to a reference sequence. A partially mapped read includes a mapped portion, a soft-clipped portion and a breakpoint. Analyzing the partially mapped reads intersecting a column of the pileup includes detecting a duplication in the soft-clipped portion by comparing the soft-clipped portion to the mapped portion adjacent to the breakpoint; determining an insert size of the duplication in the soft-clipped portion; and assigning the partially mapped read to a category based on the insert size. Categories correspond to insert sizes. The categories are filtered and converted into features corresponding to the column. The features corresponding to one or more columns representing a same insert are merged to determine a location and size of a tandem duplication.

Abstract: The present invention provides a method of detecting mutational signatures in a DNA sample. The invention relates to method of detecting signatures arising from rearrangements in the DNA in the sample and determining the contributions of known rearrangement signatures to said rearrangements. In particular embodiments, the contributions are determined by computing the cosine similarity between the rearrangement mutations in said catalogue and the rearrangement mutational signatures. The rearrangement signatures are classified based on whether they are clustered or not, whether they are tandem duplications, deletions, inversions or translocations and on the basis of their size.