Abstract: Some embodiments relate to methods, systems, uses, or software for generating a consensus sequence of a particular molecule. A set of sequences of the particular molecule can be accessed, each having been generated independently from other sequences in the set of sequences and each including an ordered set of bases. An alignment process may be performed using the set of sequences to generate an alignment result associating, for each base of the ordered sets of bases of the sets of sequences. The base may have a reference position. For each reference position of a set of reference positions, a feature vector for the reference position may be generated that represents each base from the ordered sets of bases aligned to the reference position. The feature vectors for the set of references positions may be processed using a machine learning model to generate the consensus sequence for the particular molecule.

Abstract: The present disclosure provides systems and methods of classifying and/or identifying a cancer subtype. The present disclosure also provides methods of enhancing the prediction of a tumor mutational burden by using both synonymous and non-synonymous somatic mutations in the computation method. It is believed that by increasing the number of mutations in the computation of the tumor mutational burden, a comparatively more consistent tumor mutational burden may be derived, especially for targeted-panel sequencing. It is believed that the consistent computation of the tumor mutational burden from targeted panels allows for computationally quicker and less costly analysis of sequencing data as compared with a tumor mutational burden computed from whole exome sequencing data.

Abstract: The present disclosure provides systems and methods that utilize neural networks such as convolutional neural networks to analyze genomic sequence data generated by a sequencer and generate accurate prediction data identifying and describing germline and/or somatic variants within the sequence data.

Abstract: Described herein are methods, systems, and apparatuses for detecting significantly mutated genes/pathways in a cancer cohort. A driver gene detection technique taking into account the heterogeneous mutational context in a cancer cohort is disclosed. A statistical model of a gene-specific mutation rate distribution (e.g., using an optimized gene specific mean estimation and/or a gene-specific dispersion estimation) is used to model a sample/gene-specific background mutation rate. The statistical model may then be used to detect gene/pathway enrichment and distinguish tumor suppressors and oncogenes based on the spatial distribution of non-silent mutations, loss-of-function mutations, and/or gain-of-function mutations.

Abstract: The present disclosure provides systems and methods for nucleic acid sequence analysis. A system for processing raw nucleic acid sequence data from a genomic sequencer comprises a data processing server having a housing contained therein one or more processing modules. The one or more processing modules can each comprise an electronic control unit programmed to align nucleic acid sequence data from a genomic sequencing device and perform one or more of variant analysis and structural variant analysis on the nucleic acid sequence data. The system can further comprise a computer server in communication with the processing server. The computer server can be programmed or otherwise configured to process and/or analyze the aligned nucleic acid sequence data.

Abstract: The present disclosure provides systems and methods for nucleic acid sequence analysis. A system for processing raw nucleic acid sequence data from a genomic sequencer comprises a data processing server having a housing contained therein one or more processing modules. The one or more processing modules can each comprise an electronic control unit programmed to align nucleic acid sequence data from a genomic sequencing device and perform one or more of variant analysis and structural variant analysis on the nucleic acid sequence data. The system can further comprise a computer server in communication with the processing server. The computer server can be programmed or otherwise configured to process and/or analyze the aligned nucleic acid sequence data.