We describe a method and apparatus for analysing a sample. The method may comprise extracting a plurality of sequence reads from within the sample. Genomic analysis is then performed on the plurality of sequence reads by comparing the plurality of sequence reads to reference genomes stored in a reference database, wherein each stored reference genome comprises a set of reference sequences. Before performing the genomic analysis, the method further comprises comparing screening sequences with at least one of the set of reference sequences and the plurality of sequence reads from the sample. When it is determined that a screening sequence matches at least one sequence within either the set of reference sequences or the plurality of sequence reads, the at least one matching sequence is masked.

Displaying a comparison of genotypic information between relatives is disclosed, including receiving an indication that a first individual is a grandparent, receiving an indication that a second individual is a grandchild of the first individual, comparing the genotypic information of the first individual and the second individual and calculating a similarity score, and displaying an indication of the similarity score graphically using colors.

Displaying a comparison of genotypic information between relatives is disclosed, including receiving an indication that a first individual is a grandparent, receiving an indication that a second individual is a grandchild of the first individual, comparing the genotypic information of the first individual and the second individual and calculating a similarity score, and displaying an indication of the similarity score graphically using colors.

Determining relative connections between individuals includes: obtaining identification information of a first individual and identification information of a second individual; determining, based at least in part on a relative connections graph, a relative connections path connecting the first individual, the second individual, and at least one additional individual; and outputting information pertaining to the relative connections path.

Determining relative connections between individuals includes: obtaining identification information of a first individual and identification information of a second individual; determining, based at least in part on a relative connections graph, a relative connections path connecting the first individual, the second individual, and at least one additional individual; and outputting information pertaining to the relative connections path.

In one example, a method comprises: receiving an trait indicator; obtaining, based on the trait indicator, a probability distribution of embedding vectors in a latent space, the probability distribution being generated by a distribution generation sub-model of a trained generative machine learning model from an input vector representing a variant segment associated with the trait indicator, the input vector being defined in a variant segment space having a larger number of dimensions than the latent space; obtaining a sample vector by sampling the probability distribution; reconstructing, by a sequence generation sub-model of the trained generative machine learning model and based on the trait indicator, an output vector from the sample vector, the output vector being defined in the variant segment space; and generating a simulated genome sequence based on the output vector.

A bioinformatics method is provided for identifying candidate biological sequences, such as DNA, RNA, and proteins, with high sensitivity and specificity for application in procedures such as PCR and gene and protein sequencing. The method involves categorizing a collection of biological sequences within an out-group and an in-group, identifying the intersection between the in-group and the out-group, the union of the out-group, and a relative complement of sequences that are members of the in-group, but not the out-group. A biological signature for a species of interest with high sensitivity and specificity will be a member of the relative complement that has an out-group frequency of zero.

The present disclosure provides methods and computer-implemented systems for producing, procuring, or identifying a non-human animal or offspring thereof having one or more predetermined traits. Also disclosed herein are a computer implemented graphical user interface and database system containing information associated with one or more predetermined traits for use in generating a probability matrix containing an array of probability values pertaining to the likelihood of producing a non-human animal having one or more predetermined traits.

The present disclosure provides methods and computer-implemented systems for producing, procuring, or identifying a non-human animal or offspring thereof having one or more predetermined traits. Also disclosed herein are a computer implemented graphical user interface and database system containing information associated with one or more predetermined traits for use in generating a probability matrix containing an array of probability values pertaining to the likelihood of producing a non-human animal having one or more predetermined traits.

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.