Abstract: A method (100) for characterizing a relevance of one or more genes or pathways to a disease of an individual, comprising: (i) obtaining (110) a phenotype profile for the individual, comprising phenotypic characteristics, and differential gene and protein expression information; (ii) identifying (120) one or more database of stored phenotype profiles similar to the individual phenotype profile; (iii) determining (130) a relevance of a genetic pathway to the individual phenotype profile, based at least in part on a similarity between the genetic pathway's known disease/phenotype associations and a phenotype profile of the individual; (iv) determining (140) a relevance of a gene to the individual phenotype profile, based at least in part on a similarity between the gene's known disease/phenotype associations and a phenotype profile of the individual; and (v) reporting (150) one or more genetic pathways and/or one or more genes most relevant to the individual phenotype profile.

Abstract: In patient cohort identification, clustering (30) of patients is performed using a patient comparison metric dependent on a set of features (24). Information is displayed on sample patients who are similar or dissimilar to a query patient according to the clustering. User inputted comparison values are received comparing the sample patients with the query patient. The set of features and/or feature weights are adjusted to generate an adjusted patient comparison metric having improved agreement with the user inputted comparison values. The clustering is repeated using the adjusted patient comparison metric. A patient cohort is identified from a cluster (34) containing the query patient produced by the last clustering repetition. The information on the sample patients may be shown by simultaneously displaying two or more graphical modality representations (70, 72, 74) each plotting the sample patients and the query patient against two or more features of the modality.

Abstract: Cancer care is increasingly more complicated due to increasing therapeutic options and is often difficult to access information critical to clinical decisions as a result of the frequency of new studies and decentralization of complex clinical evidence. Patient genomic and other clinical information is critical for making timely and accurate oncology and health care decisions is often in narrative text format scattered across multiple reports and IT systems. It is critical for treatment to encode clinical knowledge pertinent to clinical decision making in an easily accessible form. Discretized information in a digital patient file can assist in creating and selecting relevant therapies based on the body of medical and genomic testing history for a given patient. Discretized information is linked to a pathway execution engine and dynamically updated clinical trial matches. An authoring tool assists in creating pathways for the pathways execution engine to drive care through clinical decision trees.

Abstract: Methods, systems and apparatus for detecting patterns in constituents of at least one biological organism are disclosed. In accordance with one method, clusters of the constituents are determined by selecting different subsets of at least one of genes or proteins and identifying the clusters from biological data corresponding to the selected subsets. Here, membership values for the constituents, indicating membership within the clusters, are calculated for use as a basis of an additional cluster determination process to obtain final clusters of constituents. By underpinning the preliminary clustering on different subsets of biological data and formulating the higher-level clustering on the basis of the membership values, the embodiments can enable an evaluation of a large variety of biological data in a practical, accurate and highly efficient manner.

Abstract: A method (100) for determining a copy number variation (CNV) profile, comprising: (i) receiving (110) sparse genome sequencing data; (ii) determining (120) an unadjusted CNV profile; (iii) normalizing (130) the unadjusted CNV profile; (iv) receiving (140) a range for possible ploidy and for a possible contamination rate; (v) determining (150) adjusted segmentation values for the CNV profile; (vi) determining (160) a plurality of adjustment scores comprising a distance between an adjusted segmentation value and a closest whole integer for a CNV call; (vii) comparing (170) the determined plurality of adjustment scores to one or more predetermined factors for selecting a CNV profile best fit; (viii) selecting (180) one of the plurality of adjustment scores as a best fit for the copy number variation profile of the tumor cells of the tumor; (ix) generating (190) an adjusted CNV profile report; and (x) reporting (192) the generated adjusted CNV profile report.

Abstract: A method (100) for characterizing a functional impact of a plurality of variants, comprising: obtaining (110) information comprising at least a plurality of variants, gene expression information, copy number variation, and epigenetic effects; determining (120) a splice status for the variant; determining (130) a variant-based expression regulation status, comprising whether the variant has an effect on gene expression; determining (140) a gene-based expression regulation status, comprising an indication of whether the variant has a functional impact on a target gene; determining (150) a gene-based copy number variant (CNV) and epigenetic impact status, comprising whether one or both has an impact on expression of a gene; adjusting (160), based on the CNV and epigenetic impact status, the variant-based and/or the gene-based expression regulation status; and reporting (170) at least the adjusted variant-based and/or the adjusted gene-based expression regulation status for each of a plurality of variants and/or

Abstract: A method (100) for characterizing variant expression status for variants identified from a genomic sample, comprising: (i) obtaining (110) DNA sequencing data for the genomic sample; (ii) obtaining (110) RNA sequencing data for the genomic sample, wherein the obtained RNA sequencing data further comprises expression data for each variant; (iii) merging (130) the aligned DNA and RNA sequencing data into a merged alignment; (iv) identifying (140) a plurality of variants relative to the reference genome to generate a set of variants; (v) characterizing (150) an RNA-editing and/or expression status for each of at least a plurality of variants, wherein the expression status comprises one of a plurality of allele-specific expression categorizations comprising expression information for an alternative allele of the variant and expression information for a reference allele of the variant if there is one; and (vi) generating (160) a report comprising the characterized expression status for the variants.

Abstract: In a clinical decision support method, outputs of computer-implemented analytical modules are computed for a patient. Information is displayed for the patient pertaining to a clinical question comprising outputs computed for the patient of analytical modules associated with the clinical question. The analytical modules may include modules configured to perform in silico genetic/genomic tests using genetic/genome sequencing (whole genome, whole exome, whole transcriptome, targeted gene panels, etc) or microarray data. A clinical question-module matrix (CQ-M matrix) may be generated for the patient associating clinical questions with analytical modules, and the method may further include populating the clinical questions with outputs computed for the patient of the analytical modules associated with the clinical questions by the CQ-M matrix.

Abstract: When generating visual representations of gene activity pathways for clinical decision support, a validated pathway database that stores a plurality of validated pathways is accessed, wherein each pathway describes at least one interaction between a plurality of genes. A processor (18) is configured to execute computer-executable instructions stored in a memory (16), the instructions comprising visually representing gene activity level (28) for at least one gene across a plurality of populations, retrieving a pathway (32) from the validated pathway database, wherein the pathway includes the at least one gene, and visually representing gene activity levels for all genes in the pathway.

Abstract: When generating visual representations of gene activity pathways for clinical decision support, a validated pathway database that stores a plurality of validated pathways is accessed, wherein each pathway describes at least one interaction between a plurality of genes. A processor (18) is configured to execute computer-executable instructions stored in a memory (16), the instructions comprising visually representing gene activity level (28) for at least one gene across a plurality of populations, retrieving a pathway (32) from the validated pathway database, wherein the pathway includes the at least one gene, and visually representing gene activity levels for all genes in the pathway.

Abstract: A method (100, 200, 400) for predicting a response of a tumor to immunotherapy, comprising: analyzing (120) a tumor sample; analyzing (130) a non-tumor sample obtained from the patient; identifying (140) one or more tumor-specific mutations; analyzing (150) the genetic information from the tumor sample to determine a variant allele frequency for the identified tumor-specific mutations; analyzing (160) genetic information to determine a tumor purity of the patients tumor; determining (210) a pathogenicity for the identified tumor-specific mutations; calculating (220), from: (i) the determined variant allele frequency and/or a determined allele-specific expression, exon expression, or gene expression of the one or more tumor-specific mutations; (ii) the determined tumor purity; and (iii) the determined pathogenicity, a tumor functional mutation load score; predicting (410), based on the score, a response of the patients tumor to an immunotherapy treatment; and determining (420), based on said prediction, a trea

Abstract: A method (100) for generating a graph-based reference genome, comprising: (i) receiving (120) one or more older versions of a current reference genome, each comprising a plurality of nodes identifying the version of the reference genome and a location within that version for the respective node; (ii) aligning (130) each older version of the reference genome to the current reference genome to generate a graph-based reference genome, wherein the alignment is based on the location information; (iii) extracting (140), from a corpus of references, an allele and contextual information associated with the allele, wherein the respective reference identifies the version of the reference genome and a location of the allele within the version; and (iv) mapping (150) the allele and associated contextual information onto a node of the graph-based reference genome, based on the identified version of the reference genome and the location of the extracted allele within that version.

Abstract: A method (100) comprising: (i) providing (104, 106) a reference data set for a first gene expression platform and a training data set for a second platform; (iii) computing (108) a boundary expression level that distinguishes between the subtypes; (iv) generating (1 10) a confusion matrix; (v) determining (112) an effectiveness of the gene markers to discriminate between the subtypes; (vi) filtering (114) any gene marker with an expression level below a threshold or with determined effectiveness below a threshold; (v) calculating (118) a mean and/or median expression level for each subtype, and comparing them to generate an expression level change; (vi) comparing (118) the expression level change to a reference expression level change; and (vii) selecting (120) the gene marker if the generated expression level change and the reference expression level change are changed in the same direction; and (viii) providing (124) the selected gene markers via a user interface.

Abstract: The present disclosure pertains to a system, a method of using such a system, and a non-transitory computer-readable medium containing instructions to such a system for generating annotated gene fusion data from processing both a patient's DNA and RNA sequence information thereby filtering out weak candidate gene fusions. Thus the annotated gene fusion data contains clinically relevant information and accurate gene fusion detections (low false-positives) for use in clinical and/or R&D settings. The system, method and computer-readable medium allows a user to generate gene fusion data by detecting breakpoints from a patient's DNA-SEQ and RNA-SEQ, creating candidate breakpoint data by combining matching breakpoints from the DNA-SEQ and RNA-SEQ breakpoint data, determining confidence levels of the candidate breakpoint, identifying corresponding gene fusions, and annotating clinically relevant information about the gene fusions.

Abstract: The amount of genomic data as well the sensitivity of the information carried necessitates the need to develop smart and efficient ways to transmit genomic data in a secure way. While encryption schemes exist, there is also the need to first reduce the amount of massive information and then apply an encoding and encryption method that will be effective both in the economic sense as well as for security of genomic data. In this invention, we discuss novel techniques to encode processed variant information and send it across to a remote site ensuring covert transmission. The protocols not only encode and encrypts the information; it condenses the information that needs to be transferred.

Abstract: Methods, systems and apparatus for detecting patterns in constituents of at least one biological organism are disclosed. In accordance with one method, clusters of the constituents are determined by selecting different subsets of at least one of genes or proteins and identifying the clusters from biological data corresponding to the selected subsets. Here, membership values for the constituents, indicating membership within the clusters, are calculated for use as a basis of an additional cluster determination process to obtain final clusters of constituents. By underpinning the preliminary clustering on different subsets of biological data and formulating the higher-level clustering on the basis of the membership values, the embodiments can enable an evaluation of a large variety of biological data in a practical, accurate and highly efficient manner.

Abstract: The present invention relates to effective diagnosis of patients and assisting clinicians in treatment planning. In particular, invention provides a medical analysis system that enables refinement of molecular classification. The system provides a molecular profiling solution that will allow improved diagnosis, prognosis, response prediction to provide the right chemotherapy, and follow-up to monitor for cancer recurrence.

Abstract: A system and method for providing sequencing of biomolecules, which can be used for differential analysis of a test sample from a normal sample.