340 results about "Genomic data" patented technology

A system and method is disclosed for managing users' genomic data, including providing and offering access to genomic-based services, routing genomic data to providers of genomic-based services, brokering financial transactions related to the management of genomic data, securing for users best prices for genomic-based services, allowing users to earn money for the use of their genomic and other data, and using genomic data for marketing and developing products in particular geographic regions or for particular populations.

Apparatus, systems and methods for pre-processing, analyzing, and storing genomic data through a scalable, distributed analysis system across a network is presented.

A method for assessing and analyzing one or more drugs, adverse effects and associated risks, and patient characteristics resulting from the use of at least drug of interest is disclosed. The method comprises the steps of selecting one or more cases for analysis, said cases describing the behavior between at least one drug of interest and a patient genotype; profiling statistically derived values from multiple cases related to the safety of the at least one drug, wherein at least one filter is employed for deriving said values; at least one data mining engine; and an output device for displaying the analytic results from the data mining engine. A system for performing the method is likewise disclosed.

Phased haplotype features are used to infer an individual's ancestry. Reference genomic data is obtained for individuals of known ancestral origin. Haplotype features are identified based on consecutive SNPs from each individual. Sample genomic data is obtained for an individual of unknown ancestral origin. The data is phased and divided into features analogous to the features in the reference data. An admixture estimator then performs an admixture estimation based on the observed feature values in the sample data and the reference data. The estimation indicates a contribution of each of the known populations to the genome of the sample individual.

Systems, methods and computer program products configured to provide and perform metadata-based workflow management are disclosed. The inventive subject matter includes a computer readable storage medium having computer readable program instructions embodied therewith. The computer readable program instructions are configured to: initiate a workflow configured to process data; associate the data with metadata; and drive at least a portion of the workflow based on at least some of the metadata. The metadata include anchoring metadata; common metadata; and custom metadata. Inventive subject matter also encompasses a method for managing genomic data processing workflows using metadata includes: initiating a workflow; receiving a request to manage the workflow using metadata comprising: anchoring metadata, common metadata, and custom metadata, associating the metadata with the data; and driving at least a portion of the workflow based on the metadata. The workflow involves genomic analyses.

The present invention provides users with cloud-based high throughput computing system for integrative analyses of next generation sequencing genomic data, such that human cancer biomarkers and drug targets can be accurately and quickly identified. Advantageously, the present invention harness a comprehensive systematic analysis pipelines for all types of next generation sequencing genomic data, advanced genomic variants calling algorithms and modeling, variant data correlation and integration, and identification of cancer specific biomarkers and therapeutic targets. Thus, the present invention will aid users so that less of their time and efforts are required in order to obtain precisely the desired information for which they are analyzing.

A computer implemented system for genomic data sorting, comprising alignment and position mapping. The system maps each read to a position on the reference genome with which the read is associated, followed by sorting these reads by their mapped positions.

Processing of genomic data is facilitated by providing a control data set generation system wherein a control generator tool or process creates matched data sets for facilitating informatics analysis. These matched data sets may include genomic loci or genomic sequences, or both. The data is taken from a database of actual genomic data, including sequence and annotation data, as opposed to ad-hoc generation, sequence scrambling or the like. This produces biologically relevant and accurate results which allow for stronger controls. The controls are matched against a user-provided data set via a number of parameters.

Processing of genomic data is facilitated utilizing correlation analysis of mapped data sets, each data set including genomic data mapped and ordered relative to a genomic coordinate system. Correlation analysis identifies at a nucleotide level nucleotide positions wherein at least one nucleotide locus of each data set correlate. The analysis includes for each data set, selecting a nucleotide locus thereof closest to one end of the coordinate system, comparing the selected nucleotide loci for correlation, and if so, outputting results of the comparing, and updating the selected nucleotide loci by identifying the data set having a next nucleotide locus closest to the one end of the coordinate system, and inserting that next locus into the group of selected loci, and repeating the comparing for the newly selected loci. The process is repeated until nucleotide loci of the mapped data sets are compared and results of the comparison are output.

Computationally-efficient techniques facilitate secure crowdsourcing of genomic and phenotypic data, e.g., for large-scale association studies. In one embodiment, a method begins by receiving, via a secret sharing protocol, genomic and phenotypic data of individual study participants. Another data set, comprising results of pre-computation over random number data, e.g., mutually independent and uniformly-distributed random numbers and results of calculations over those random numbers, is also received via secret sharing. A secure computation then is executed against the secretly-shared genomic and phenotypic data, using the secretly-shared results of the pre-computation over random number data, to generate a set of genome-wide association study (GWAS) statistics. For increased computational efficiency, at least a part of the computation is executed over dimensionality-reduced genomic data. The resulting GWAS statistics are then used to identify genetic variants that are statistically-correlated with a phenotype of interest.

An electronic system, method, and service is disclosed for storing subjects' genomic and medical information on portable storage devices to be used for private disease diagnosis and for subject-controlled participation in research queries. Using a computer with network access, subjects conduct private disease diagnosis and disease forecasting by downloading genetic queries and running the queries against private genomic data stored on the portable storage device. When participating in a subject-controlled research program, subjects are provided the capability of joining a peer-to-peer network and the choice to decide whether to participate in queries submitted by researchers over the network to subject network members. When subject network members decide to participate in a submitted query, they download the query, run the query against their private data, and anonymously submit the results back to the network.

A non-stereo fundus image is used to obtain a plurality of glaucoma indicators. Additionally, genome data for the subject is used to obtain genetic marker data relating to one or more genes and/or SNPs associated with glaucoma. The glaucoma indicators indicators and genetic marker data are input into an adaptive model operative to generate an output indicative of a risk of glaucoma in the subject. In combination, the genetic indicators and genome data are more informative about the risk of glaucoma than either of the two in isolation. The adaptive model may be a two-stage model, having a first stage in which individual genetic indicators are combined with respective portions of the genome data by first adaptive model modules to form respective first outputs, and a second stage in which the first outputs are combined by a second adaptive mode. Texture analysis is performed on the fundus images to classify them based on their quality, and only images which are determined to meet a quality criterion are subjected to an analysis to determine if they exhibit glaucoma indicators. Also, the images are put into a standard format. The system may include estimating the position of the optic cup by combining results from multiple optic cup segmentation techniques. The system may include estimating the position of the optic disc by applying edge detection to the funds image, excluding edge points that are unlikely to be optic disc boundary points, and estimating the position of an optic disc by fitting an ellipse to the remaining edge points.