G16B10/00

DEEP LEARNING-BASED USE OF PROTEIN CONTACT MAPS FOR VARIANT PATHOGENICITY PREDICTION

The technology disclosed relates to a variant pathogenicity classifier. The variant pathogenicity classifier comprises memory and runtime logic. The memory stores (i) a reference amino acid sequence of a protein, (ii) an alternative amino acid sequence of the protein that contains a variant amino acid caused by a variant nucleotide, and (iii) a protein contact map of the protein. The runtime logic has access to the memory, and is configured to provide (i) the reference amino acid sequence, (ii) the alternative amino acid sequence, and (iii) the protein contact map as input to a first neural network, and to cause the first neural network to generate a pathogenicity indication of the variant amino acid as output in response to processing (i) the reference amino acid sequence, (ii) the alternative amino acid sequence, and (iii) the protein contact map.

DEEP LEARNING-BASED USE OF PROTEIN CONTACT MAPS FOR VARIANT PATHOGENICITY PREDICTION

The technology disclosed relates to a variant pathogenicity classifier. The variant pathogenicity classifier comprises memory and runtime logic. The memory stores (i) a reference amino acid sequence of a protein, (ii) an alternative amino acid sequence of the protein that contains a variant amino acid caused by a variant nucleotide, and (iii) a protein contact map of the protein. The runtime logic has access to the memory, and is configured to provide (i) the reference amino acid sequence, (ii) the alternative amino acid sequence, and (iii) the protein contact map as input to a first neural network, and to cause the first neural network to generate a pathogenicity indication of the variant amino acid as output in response to processing (i) the reference amino acid sequence, (ii) the alternative amino acid sequence, and (iii) the protein contact map.

Methods for amplification of cell-free DNA using ligated adaptors and universal and inner target-specific primers for multiplexed nested PCR

Methods for non-invasive prenatal paternity testing are disclosed herein. The method uses genetic measurements made on plasma taken from a pregnant mother, along with genetic measurements of the alleged father, and genetic measurements of the mother, to determine whether or not the alleged father is the biological father of the fetus. This is accomplished by way of an informatics based method that can compare the genetic fingerprint of the fetal DNA found in maternal plasma to the genetic fingerprint of the alleged father.

Methods for amplification of cell-free DNA using ligated adaptors and universal and inner target-specific primers for multiplexed nested PCR

Methods for non-invasive prenatal paternity testing are disclosed herein. The method uses genetic measurements made on plasma taken from a pregnant mother, along with genetic measurements of the alleged father, and genetic measurements of the mother, to determine whether or not the alleged father is the biological father of the fetus. This is accomplished by way of an informatics based method that can compare the genetic fingerprint of the fetal DNA found in maternal plasma to the genetic fingerprint of the alleged father.

SYSTEMS, METHODS, AND APPARATUSES FOR SEQUENCE ALIGNMENT
20180004892 · 2018-01-04 · ·

Systems, methods, and apparatuses are disclosed for reducing the computational time of assigning a species to an infection isolate. A method for dividing a search index into one or more sub-indices based on a phylogenetic tree of reference sequences is disclosed. A method for dividing reads into test sets and aligning to sub-indices for assigning a species to an infection isolate is disclosed. A system for aligning sequence reads to a database of reference sequences using sub-indices is disclosed.

Finding Relatives in a Database

Determining relative relationships of people who share a common ancestor within at least a threshold number of generations includes: receiving recombinable deoxyribonucleic acid (DNA) sequence information of a first user and recombinable DNA sequence information of a plurality of users; processing, using one or more computer processors, the recombinable DNA sequence information of the plurality of users in parallel; determining, based at least in part on a result of processing the recombinable DNA information of the plurality of users in parallel, a predicted degree of relationship between the first user and a user among the plurality of users, the predicted degree of relative relationship corresponding to a number of generations within which the first user and the second user share a common ancestor.

Finding Relatives in a Database

Determining relative relationships of people who share a common ancestor within at least a threshold number of generations includes: receiving recombinable deoxyribonucleic acid (DNA) sequence information of a first user and recombinable DNA sequence information of a plurality of users; processing, using one or more computer processors, the recombinable DNA sequence information of the plurality of users in parallel; determining, based at least in part on a result of processing the recombinable DNA information of the plurality of users in parallel, a predicted degree of relationship between the first user and a user among the plurality of users, the predicted degree of relative relationship corresponding to a number of generations within which the first user and the second user share a common ancestor.

ALIGNMENT FREE FILTERING FOR IDENTIFYING FUSIONS

Cell free nucleic acids from a test sample obtained from an individual are analyzed to identify possible fusion events. Cell free nucleic acids are sequenced and processed to generate fragments. Fragments are decomposed into kmers and the kmers are either analyzed de novo or compared to targeted nucleic acid sequences that are known to be associated with fusion gene pairs of interest. Thus, kmers that may have originated from a fusion event can be identified. These kmers are consolidated to generate gene ranges from various genes that match sequences in the fragment. A candidate fusion event can be called given the spanning of one or more gene ranges across the fragment.

ALIGNMENT FREE FILTERING FOR IDENTIFYING FUSIONS

Cell free nucleic acids from a test sample obtained from an individual are analyzed to identify possible fusion events. Cell free nucleic acids are sequenced and processed to generate fragments. Fragments are decomposed into kmers and the kmers are either analyzed de novo or compared to targeted nucleic acid sequences that are known to be associated with fusion gene pairs of interest. Thus, kmers that may have originated from a fusion event can be identified. These kmers are consolidated to generate gene ranges from various genes that match sequences in the fragment. A candidate fusion event can be called given the spanning of one or more gene ranges across the fragment.

SYSTEM, METHOD, AND APPARATUS FOR PREDICTING GENETIC ANCESTRY

In one embodiment, a method includes accessing a sample of genetic material associated with a first animal, wherein the sample of genetic material comprises raw genotypes, generating phased haplotypes based on the raw genotypes, generating local assignments for genetic populations for the phased haplotypes by machine learning algorithms based on comparisons between the phased haplotypes and a reference panel comprising reference haplotypes associated with reference populations, and sending instructions to a user device for presenting an output associated with the first animal to a user, wherein the output is generated based on the local assignments for the genetic populations.