Abstract: Techniques for automated determination or correction of count bias are based on nucleic acid base content on a finer grained scale than a bin of interest in a target sequence. The techniques include obtaining a target sequence with bins where relative abundances indicate a condition and raw counts Hj of reads, from a subject, which start at each locus j. A partition indicates a fine-grained window at a position relative to a current locus and multiple strata indicating different base contents. Each locus is attributed to one stratum k(j). An expected count of each stratum, E(k), is determined based on Hj for j belonging to the stratum and a number of loci in the target belonging to the stratum. A copy number of a bin is based on a sum of E(k(j)) in the bin. Output data indicates condition of the subject based at least partly on the copy number.

Abstract: Developmental, stem cell and cancer biologists are interested in the molecular definition of cellular differentiation. Although single-cell RNA sequencing represents a transformational advance for global gene analyses, novel obstacles have emerged, including the computational management of dropout events, the reconstruction of biological pathways and the isolation of target cell populations. Provided herein is an algorithm named dpath that applies the concept of metagene entropy and allows the ranking of cells based on their differentiation potential. Also provided herein are self-organizing map (SOM) and random walk with restart (RWR) algorithms to separate the progenitors from the differentiated cells and reconstruct the lineage hierarchies in an unbiased manner. These algorithms were tested using single cells from Etv2-EYFP transgenic mouse embryos and reveal specific molecular pathways that direct differentiation programs involving the haemato-endothelial lineages.

Abstract: The present disclosure provides methods and systems for accurate and efficient context-aware base calling of sequences. In an aspect, disclosed herein is a method for sequencing a nucleic acid molecule, comprising: (a) sequencing the nucleic acid molecule to generate a plurality of sequence signals; and (b) determining base calls of the nucleic acid molecule based at least in part on (i) the plurality of sequence signals and (ii) quantified context dependency for at least a portion of the plurality of sequence signals.

Abstract: A method, including a computer-implemented method, is provided for in vivo detection of epidermal growth factor receptor (EGFR) mutation status within peritumoral edematous tissue of a patient. The method includes performing quantitative pattern analysis of magnetic resonance imaging (MRI) data corresponding to MRI of in vivo peritumoral edematous tissue to determine a level of spatial heterogeneity or similarity within the in vivo peritumoral edematous tissue. EGFR mutation status is assigned as one of negative or positive based on the level of spatial heterogeneity or similarity determined. A non-transitory computer-readable storage medium and a system are also provided.

Abstract: In various embodiments, amplification-free DNA information methods, apparatus and systems are disclosed. A method of amplification-free information storage and retrieval comprises encoding digital data such as binary into nucleotide sequence motifs using an encoding scheme, and synthesizing replicate DNA molecules using an amplification-free DNA writing process. The amplification-free process of decoding the information stored in the DNA comprises exposing at least one of the replicate DNA molecules to a molecular electronics sensor that generates distinguishable signals in a measured electrical parameter of the sensor, wherein the distinguishable signals correspond to the sequence motifs, providing decoding back to the digital data.

Abstract: Systems and methods to enable representation of sequence as well as structural information of an RNA molecule in the form of a single encoded string are described. The encoding steps are based on identifying one or more contiguous stretches of ribonucleotide bases having similar structural attributes and base-pairing patterns. In the encoded string, each of the identified contiguous structure stretches is represented by a single character that indicates the corresponding structural attribute. Appending these structural characters to the corresponding contiguous ribonucleotide character stretches, and subsequently eliminating redundant ribonucleotide characters based on standard base-pairing rules results in generating the final encoded string. Such concomitant representation of sequence and structural information of a given RNA molecule in a single encoded string enables efficient storage and easy dissemination of RNA data.

Abstract: Disclosed herein are polynucleotide adaptors and methods of use thereof for identifying and analyzing nucleic acids, including cell-free nucleic acids from a patient sample. Also disclosed herein are methods of using the adaptors to detect, diagnose, or determine prognosis of cancers.

Abstract: 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 deriving a fragment size parameter, such as a size-weighted coverage or a fraction of fragments in a size range. In some embodiments, the fragment size parameter is adjusted to remove 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.

Abstract: A novel method for prediction of the degree of heterotic phenotypes in plants is disclosed. Structural variation analyses of the genome are used to predict the degree of a heterotic phenotype in plants. In some examples, copy number variation is used to predict the degree of heterotic phenotype. In some methods copy number variation is detected using competitive genomic hybridization arrays. Further, methods for optimizing the arrays are disclosed, together with kits for producing such arrays, as well as hybrid plants selected for development based on the predicted results.

Abstract: Methods, libraries, and kits for nucleotide sequencing are provided. For example, methods can comprise providing a plurality of partitions, the partitions comprising a set of two or more different primers and a target nucleic acid, wherein different partitions contain different sets of primers with a majority of primers in the sets being common with a different primer set but wherein any two different partitions having a common primer contain no more than one common primer; and hybridizing the target nucleic acid to the primers in the reaction partitions under conditions in which fully complementary primers hybridize to the target sequence and primers that are not fully complementary do not hybridize to the target nucleic acid.

Abstract: Methods and apparatus for providing data processing and control for use in a medical communication system are provided.

Abstract: Systems and methods are provided for performing quality control analysis. The method obtains, in electronic form, a batch dataset comprising, for each respective sample in a batch of samples, a corresponding plurality of sequence reads derived from the respective sample by targeted or whole transcriptome RNA sequencing and corresponding metadata for the respective sample. The method determines for the batch dataset a cohort-matched reference batch, where the cohort-matched reference batch is balanced for tissue site, tumor purity, cancer type, sequencer identity, or date sequenced. The method performs one or more global batch quality control tests on the batch dataset using at least the cohort-matched reference batch. The method removes respective samples from the batch dataset that fail any one of the one or more global batch quality control tests or flagging for manual inspection respective samples that fail any one of the one or more global batch quality control tests.

Abstract: The present invention provides algorithm-based molecular assays that involve measurement of expression levels of genes, or their co-expressed genes, from a biological sample obtained from a prostate cancer patient. The genes may be grouped into functional gene subsets for calculating a quantitative score useful to predict a likelihood of a clinical outcome for a prostate cancer patient.

Abstract: Technology provided herein relates in part to methods, processes and apparatuses for non-invasive assessment of genetic variations.

Abstract: Provided in part herein are methods and processes that can be used for non-invasive assessment of a genetic variation which can lead to diagnosis of a particular medical condition or conditions. Such methods and processes can, for example, identify dissimilarities or similarities for one or more features between a subject data set and a reference data set, generate a multidimensional matrix, reduce the matrix into a representation and classify the representation into one or more groups. Methods and processes described herein are applicable to data in biotechnology and other fields.

Abstract: Systems, methods, and apparatus are provided for analyte level estimation to improve accuracy thereof. Systems include sensor electronics operatively coupled to an analyte sensor configured for contact with a user's biofluid. A user interface device is configured for communication with the sensor electronics and configured to determine a predicted state estimate using exogenous measurement data and a past state estimate and, thereafter, determine a corrected state estimate, including an estimated analyte level, using the predicted state estimate and current analyte sensor measurement data.

Abstract: Systems, methods, and devices for generating synthetic genomic datasets and validating bioinformatic pipelines for genomic analysis are disclosed. In preferred embodiments, synthetic maternal and paternal datasets with known variants are used with matched normal synthetic datasets to validate various bioinformatic pipelines. Bioinformatic pipelines are evaluated using the synthetic datasets to assess design changes and improvements. Accuracy, PPV, specificity, sensitivity, reproducibility, and limit of detection of the pipelines in calling variants in synthetic datasets is reported.

Abstract: The present disclosure provides machine learning techniques for computationally predicting the phenotypic performance of combinations of genetic variations and for designing new improved host cells. The machine learning models and methods described herein are host agnostic and therefore can be implemented across taxa. Furthermore, the disclosed platform can be implemented to modulate or improve any host cell parameter of interest.

Abstract: This invention relates to an in vitro method for prognosis of the response to a chemotherapy of an individual suffering from chronic myeloid leukemia, comprising a. a step of measuring the expression level of at least one subgroup of genes chosen from a group of genes, b. a comparing step, and c. a step of determining a score S such that—if S is less than 1, said individual will have more than a 40% chance of responding to the chemotherapy, and—if S is greater than or equal to 1, said individual will have less than a 40% chance of responding to the chemotherapy.

Abstract: A method, apparatus and system for detecting structural variations is provided.