Abstract: Genomic data is written to disk in a compact format by dividing the data into segments and encoding each segment with the smallest number of bits per character necessary for whatever alphabet of characters appears in that segment. A computer system dynamically chooses the segment boundaries for maximum space savings. A first one of the segments may use a different number of bits per character than a second one of the segments. In one embodiment, dividing the data into segments comprises scanning the data and keeping track of a number of unique characters, noting positions in the sequence where the number increases to a power of two, calculating a compression that would be obtained by dividing the genomic data into one of the plurality of segments at ones of the noted positions, and dividing the genomic data into the plurality of segments at the positions that yield the best compression.

Abstract: Embodiments of the invention utilize a graph-based approach for simulating genomic datasets from large scale populations. Genomic data may be represented as a directed acyclic graph (DAG) that incorporates individual sample data including variant type, position, and zygosity. A simulator may operate on the DAG to generate variant datasets based on probabilistic traversal of the DAG. This probabilistic traversal reflects genomic variant types associated with the subpopulation used to build the DAG, and as a result, the generated variant datasets maintain statistical fidelity to the original sample data.

Abstract: A method for stream-processing biomedical data includes receiving, by a file system on a computing device, a first request for access to at least a first portion of a file stored on a remotely located storage device. The method includes receiving, by the file system, a second request for access to at least a second portion of the file. The method includes determining, by a pre-fetching component executing on the computing device, whether the first request and the second request are associated with a sequential read operation. The method includes automatically retrieving, by the pre-fetching component, a third portion of the requested file, before receiving a third request for access to least the third portion of the file, based on a determination that the first request and the second request are associated with the sequential read operation.

Abstract: Various approaches for data storage and retrieval for a computer memory include processing a computational workflow having multiple data-processing steps, generating and storing a first hash value associated with a first step of the data-processing steps based on an input to the first step, generating and storing a second hash value associated with a second step of the data-processing steps based on the generated first hash value, and reconstructing a computational state of the workflow based on the second hash value, and thereby avoid re-execution of a portion of the workflow corresponding to the second hash value.

Abstract: Some embodiments relate to systems for processing one or more computational workflows. In one embodiment, a description of a computational comprises a plurality of applications, in which applications are represented as nodes and edges connect the nodes indicate the flow of data elements between applications. A task execution module is configured to create and execute tasks. An application programming interface (API) is in communication with the task execution module and comprises a plurality of function calls for controlling at least one function of the task execution module. An API script includes instructions to the API to create and execute a plurality of tasks corresponding to the execution of the computational workflow for a plurality of samples. A graphical user interface (GUI) is in communication with the task execution module and configured to receive input from an end user to initiate execution of the API script.

Abstract: In one aspect, a method for scheduling jobs in a computational workflow includes identifying, from a computational workflow by a workflow execution engine executing on a processor, a plurality of jobs ready for execution. The method includes sorting, based on computational resource requirements associated with each identified job, the identified jobs into a prioritized queue. The method includes provisioning one or more computational instances based on the computational resource requirements of the identified jobs in the prioritized queue, wherein at least one computational instance is provisioned based on a highest priority job in the queue. The method includes submitting the prioritized jobs for execution to the one or more computational instances.

Abstract: In one embodiment, a method of processing a computational workflow comprises receiving a description of a computational workflow. The description comprises a plurality of steps, in which each step has at least one input and at least one output, and further wherein an input from a second step depends on an output from a first step. The description is translated into a static workflow graph stored in a memory, the static workflow graph comprising a plurality of nodes having input ports and output ports, wherein dependencies between inputs and outputs are specified as edges between input ports and output ports. Information about a first set of nodes is then extracted from the static workflow graph and placed into a dynamic graph. A first actionable job is identified from the dynamic graph and executed.

Abstract: Genomic data is written to disk in a compact format by dividing the data into segments and encoding each segment with the smallest number of bits per character necessary for whatever alphabet of characters appears in that segment. A computer system dynamically chooses the segment boundaries for maximum space savings. A first one of the segments may use a different number of bits per character than a second one of the segments. In one embodiment, dividing the data into segments comprises scanning the data and keeping track of a number of unique characters, noting positions in the sequence where the number increases to a power of two, calculating a compression that would be obtained by dividing the genomic data into one of the plurality of segments at ones of the noted positions, and dividing the genomic data into the plurality of segments at the positions that yield the best compression.

Abstract: Some embodiments relate to systems for processing one or more computational workflows. In one embodiment, a description of a computational comprises a plurality of applications, in which applications are represented as nodes and edges connect the nodes indicate the flow of data elements between applications. A task execution module is configured to create and execute tasks. An application programming interface (API) is in communication with the task execution module and comprises a plurality of function calls for controlling at least one function of the task execution module. An API script includes instructions to the API to create and execute a plurality of tasks corresponding to the execution of the computational workflow for a plurality of samples. A graphical user interface (GUI) is in communication with the task execution module and configured to receive input from an end user to initiate execution of the API script.

Abstract: In one embodiment, a method of processing a computational workflow comprises receiving a description of a computational workflow. The description comprises a plurality of steps, in which each step has at least one input and at least one output, and further wherein an input from a second step depends on an output from a first step. The description is translated into a static workflow graph stored in a memory, the static workflow graph comprising a plurality of nodes having input ports and output ports, wherein dependencies between inputs and outputs are specified as edges between input ports and output ports. Information about a first set of nodes is then extracted from the static workflow graph and placed into a dynamic graph. A first actionable job is identified from the dynamic graph and executed.

Abstract: Embodiments of the invention utilize a graph-based approach for simulating genomic datasets from large scale populations. Genomic data may be represented as a directed acyclic graph (DAG) that incorporates individual sample data including variant type, position, and zygosity. A simulator may operate on the DAG to generate variant datasets based on probabilistic traversal of the DAG. This probabilistic traversal reflects genomic variant types associated with the subpopulation used to build the DAG, and as a result, the generated variant datasets maintain statistical fidelity to the original sample data.

Abstract: A method for generating a query of a genomic data store includes receiving, by a query generator executing on a computing device, from a graphical user interface, an identification of a first entity of a first entity class for inclusion in a resource description framework (RDF) query. The method includes receiving from the graphical user interface, an identification of a second entity of the first entity class, the second entity having a bi-directional relationship with the first entity. The method includes automatically generating an RDF query based upon the received identification of the first entity and the received identification of the second entity. The method includes executing the RDF query to select, from a plurality of genomic data sets, at least one genomic data set for at least one patient cohort. The method includes providing a listing of genomic data sets resulting from executing the RDF query.

Abstract: Systems and methods for data storage and retrieval for a computer memory include processing a computational workflow having multiple data-processing steps, generating and storing a first hash value associated with a first step of the data-processing steps based on an input to the first step, generating and storing a second hash value associated with a second step of the data-processing steps based on the generated first hash value, and reconstructing a computational state of the workflow based on the second hash value, and thereby avoid re-execution of a portion of the workflow corresponding to the second hash value.

Abstract: In one embodiment, a method of encoding variation data for a population comprises receiving, by a variant encoding engine executing on a processor, information describing genetic variation of a population of individuals. The information comprises a plurality of variable sites within the reference genome of the population and the genotypes of a plurality of individuals in the population with respect to those variable sites. The method further comprises selecting an encoding strategy for the information based on the characteristics of the genetic variation across the population, and encoding the information according to the selected encoding strategy. In certain embodiments, selecting an encoding strategy may comprise determining the variability of a variable site within the population, and encoding information associated with the variable site based on the variability.

Abstract: The invention relates to methods for determining a haplotype for an organism by using a system for transforming SNP alleles found in sequence fragments into vertices in a graph with edges connecting vertices for alleles that appear together in a sequence fragment. A community detection operation can be used to infer the haplotype from the graph. The system may produce a report that includes the haplotype of the SNPs found in the genome of that organism.

Abstract: The invention includes methods for aligning reads (e.g., nucleic acid reads, amino acid reads) to a reference sequence construct, methods for building the reference sequence construct, and systems that use the alignment methods and constructs to produce sequences. The method is scalable, and can be used to align millions of reads to a construct thousands of bases or amino acids long. The invention additionally includes methods for identifying a disease or a genotype based upon alignment of nucleic acid reads to a location in the construct.

Abstract: Methods of analyzing a transcriptome that involves obtaining at least one pair of paired-end reads from a transcriptome from an organism, finding an alignment with an optimal score between a first read of the pair and a node in a directed acyclic data structure (the data structure has nodes representing RNA sequences such as exons or transcripts and edges connecting pairs of nodes), identifying candidate paths that include the node connected to a downstream node by a path having a length substantially similar to an insert length of the pair of paired-end reads, and aligning the paired-end rends to the candidate paths to determine an optimal-scoring alignment.

Abstract: The invention generally provides systems and methods for analysis of RNA-Seq reads in which an annotated reference is represented as a directed acyclic graph (DAG) or similar data structure. Features such as exons and introns from the reference provide nodes in the DAG and those features are linked as pairs in their canonical genomic order by edges. The DAG can scale to any size and can in fact be populated in the first instance by import from an extrinsic annotated reference.

Abstract: The invention includes methods for aligning reads (e.g., nucleic acid reads, amino acid reads) to a reference sequence construct, methods for building the reference sequence construct, and systems that use the alignment methods and constructs to produce sequences. The method is scalable, and can be used to align millions of reads to a construct thousands of bases or amino acids long. The invention additionally includes methods for identifying a disease or a genotype based upon alignment of nucleic acid reads to a location in the construct.

Abstract: The invention provides methods for identifying rare variants near a structural variation in a genetic sequence, for example, in a nucleic acid sample taken from a subject. The invention additionally includes methods for aligning reads (e.g., nucleic acid reads) to a reference sequence construct accounting for the structural variation, methods for building a reference sequence construct accounting for the structural variation or the structural variation and the rare variant, and systems that use the alignment methods to identify rare variants. The method is scalable, and can be used to align millions of reads to a construct thousands of bases long, or longer.