A system and method for accurate determination of sequence variants from noisy sequencing data, including single nucleotide variants and structural variants of the internal tandem duplication type. This system expands the utility of inexpensive sequencing instruments which stream relatively high-error output sequences in real time, such that they may be used in high-stakes contexts, such as clinical cancer care. An example application is Acute Myeloid Leukemia (AML), where healthcare providers may need to make decisions in hours, is provided.

Provided are a method of detecting chromosomal aneuploidy of a targeted fetal chromosome, and a computer-readable medium having recorded thereon a program to be applied to performing the method. According to the present disclosure, fetal chromosomal aneuploidy may be non-invasively and prenatally diagnosed with excellent sensitivity and specificity.

Provided are a method of detecting chromosomal aneuploidy of a targeted fetal chromosome, and a computer-readable medium having recorded thereon a program to be applied to performing the method. According to the present disclosure, fetal chromosomal aneuploidy may be non-invasively and prenatally diagnosed with excellent sensitivity and specificity.

This disclosure describes methods, non-transitory computer readable media, and systems that can utilize a machine learning model to recalibrate nucleotide-base calls (e.g., variant calls) of a call-generation model. For instance, the disclosed systems can train and utilize a call-recalibration-machine-learning model to generate a set of predicted variant-call classifications based on sequencing metrics associated with a sample nucleotide sequence. Leveraging the set of variant-call classifications, the disclosed systems can further update or modify nucleotide-base calls (e.g., variant calls) corresponding to genomic coordinates. Indeed, the disclosed systems can generate an initial nucleotide-base call based on sequencing metrics for nucleotide reads of a sample sequence utilizing a call-generation model and further utilize a call-recalibration-machine-learning model to generate classification predictions for updating or recalibrating the initial nucleotide-base call from a subset of the same sequencing metrics or other sequencing metrics.

This disclosure describes methods, non-transitory computer readable media, and systems that can utilize a machine learning model to recalibrate nucleotide-base calls (e.g., variant calls) of a call-generation model. For instance, the disclosed systems can train and utilize a call-recalibration-machine-learning model to generate a set of predicted variant-call classifications based on sequencing metrics associated with a sample nucleotide sequence. Leveraging the set of variant-call classifications, the disclosed systems can further update or modify nucleotide-base calls (e.g., variant calls) corresponding to genomic coordinates. Indeed, the disclosed systems can generate an initial nucleotide-base call based on sequencing metrics for nucleotide reads of a sample sequence utilizing a call-generation model and further utilize a call-recalibration-machine-learning model to generate classification predictions for updating or recalibrating the initial nucleotide-base call from a subset of the same sequencing metrics or other sequencing metrics.

A storytelling interface comprising a map panel and a genealogy panel, and methods for using the same, are described. The storytelling interface facilitates dynamic and automatic scaling and relocation of the map panel based on a user's location within the genealogy panel, which facilitates a continuous scrolling operation to navigate between different sections of the genealogy panel. The storytelling interface facilitates a user receiving, viewing, and interacting with DNA and ethnic communities results determined from DNA testing, and allows a user to navigate through pertinent communities in both time and/or space.

The disclosure provides gene fusions, gene variants, and novel associations with disease states, as well as kits, probes, and methods of using the same.

The disclosure provides gene fusions, gene variants, and novel associations with disease states, as well as kits, probes, and methods of using the same.

Provided herein are methods, processes and apparatuses for non-invasive assessment of genetic variations.

Provided herein are methods, processes and apparatuses for non-invasive assessment of genetic variations.