Abstract: A method includes searching a single file, which includes a plurality of device log files for one or more devices, based on a template file that at least indicates a sub-set of log data of interest, generating reference data for each of the log data of interest that is located in the single file, and storing the reference data in a data structure. A computing system (102) includes a memory (114) that stores one or more instructions (120) including a log file processing module (126), and a processor (116) that executes the one or more instructions, which causes the processor to: filter log data based on a template file that indicates streams of data of interest; dynamically change the amount of data of interest based on the debug level; store the streams of data of interest; and display, in response to an input signal, a sub-set of the stored virtual stream of data of interest.

Abstract: Reference feature vectors are constructed representing refer-ence genetic data sets of a reference population. The reference feature vec-tors are transformed using a linear transformation to generate reduced di-mensionality vector representations of the reference genetic data sets of the reference population. A tree-based spatial data structure is constructed to index the reference genetic data sets as data points defined by at least some dimensions of the reduced dimensionality vector representations of the ref-erence genetic data sets of the reference population. The linear transform may be generated by performing feature reduction on the reference feature vectors. A feature vector representing a proband genetic data set is trans-formed using the linear transformation to generate a reduced-dimensional-ity vector representation that is located in the tree-based spatial data struc-ture to perform population assignment for the proband genetic data set.

Abstract: A non-transitory storage medium stores an assembled genetic sequence comprising aligned sequencing reads. An electronic processing device is configured to perform operations including: identifying a possible variant in the assembled genetic sequence; computing value of at least one read property for reads of the assembled genetic sequence; and calling the possible variant conditional upon the computed values of the at least one read property for sequencing reads of the assembled genetic sequence that include the possible variant satisfying an acceptance criterion. The electronic processing device may be further configured to select at least one region of the assembled genetic sequence for validation based on a non random selection criterion.

Abstract: A cancer test includes: processing a suspect tissue sample (10) acquired from a subject (6) to generate a suspect whole genome sequence (WGS) (20); processing a normal tissue sample (12) acquired from the subject to generate a normal WGS (22); computing a WGS comparison metric comparing the suspect WGS with the normal WGS; and identifying whether the suspect tissue sample comprises cancer tissue based on the computed WGS comparison metric. A tumor delineation method comprises: acquiring a plurality of probative tissue samples (104) from a subject (6) in or near a tumor (100); recording the sampling locations of the probative tissue samples; classifying each probative tissue sample respective to cancer based on genetic testing of the probative tissue sample; and delineating a boundary (110) of the tumor based on the classifications of the probative tissue samples and the recorded sampling locations.

Abstract: Genomic or proteomic data are encoded as a genomic or proteomic character string comprising characters of a bioinformatics character set (20). Each base or peptide of the genomic or proteomic data is represented by a single character of the bioinformatics character set, and each character of the bioinformatics character set encodes (I) a base or peptide and (II) at least one annotated datum value associated with the base or peptide. The genomic or proteomic data are displayed by displaying the genomic or proteomic character string using a bioinformatics font (40) mapped to the bioinformatics character set. At least one string function may be performed on the genomic or proteomic character string to generate an updated genomic or proteomic character string in which at least one base or peptide is represented by a single character encoding at least one additional or modified annotated datum generated by the performed string manipulation.