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.

The technology disclosed generates a reference array of variant data for locations that are shared between read results which are to be compared, and generates hashes over a selected pattern length of positions in the reference array to independently produce non-unique window hashes for base patterns in the read results. It then selects for comparison window hashes that occur less than a ceiling number of times and compares the selected window hashes to identify common window hashes between the read results. It then determines a similarity measure for the read results based on the common window hashes.

The technology disclosed generates a reference array of variant data for locations that are shared between read results which are to be compared, and generates hashes over a selected pattern length of positions in the reference array to independently produce non-unique window hashes for base patterns in the read results. It then selects for comparison window hashes that occur less than a ceiling number of times and compares the selected window hashes to identify common window hashes between the read results. It then determines a similarity measure for the read results based on the common window hashes.

Methods for identifying biosynthetic gene clusters that include genes for producing compounds that interact with specific target proteins are disclosed. Some methods relate to bioinformatics methods for identifying and/or prioritizing biosynthetic gene clusters. Related systems, components, and tools for the identification and expression of such gene clusters are also disclosed.

Methods for identifying biosynthetic gene clusters that include genes for producing compounds that interact with specific target proteins are disclosed. Some methods relate to bioinformatics methods for identifying and/or prioritizing biosynthetic gene clusters. Related systems, components, and tools for the identification and expression of such gene clusters are also disclosed.

The technology disclosed generates a reference array of variant data for locations that are shared between read results which are to be compared, and generates hashes over a selected pattern length of positions in the reference array to independently produce non-unique window hashes for base patterns in the read results. It then selects for comparison window hashes that occur less than a ceiling number of times and compares the selected window hashes to identify common window hashes between the read results. It then determines a similarity measure for the read results based on the common window hashes.

The technology disclosed generates a reference array of variant data for locations that are shared between read results which are to be compared, and generates hashes over a selected pattern length of positions in the reference array to independently produce non-unique window hashes for base patterns in the read results. It then selects for comparison window hashes that occur less than a ceiling number of times and compares the selected window hashes to identify common window hashes between the read results. It then determines a similarity measure for the read results based on the common window hashes.

Described are techniques for determining population structure from identity-by-descent (IBD) of individuals. The techniques may be used to predict that an individual belongs to zero, one or more of a number of communities identified within an IBD network. Additional data may be used to annotate the communities with birth location, surname, and ethnicity information. In turn, these data may be used to provide to an individual a prediction of membership to zero, one or more communities, accompanied by a summary of the information annotated to those communities.

Described are techniques for determining population structure from identity-by-descent (IBD) of individuals. The techniques may be used to predict that an individual belongs to zero, one or more of a number of communities identified within an IBD network. Additional data may be used to annotate the communities with birth location, surname, and ethnicity information. In turn, these data may be used to provide to an individual a prediction of membership to zero, one or more communities, accompanied by a summary of the information annotated to those communities.

The present invention comprises the capture and display of arthropod, human and arthropod-based metadata, which is capable of tracking and displaying the metadata, which is time and location-based, in order to show migration paths of arthropods and/or the diseases they have the potential to carry. This real-time view can help predict future arthropod and disease based on various scenarios such as, but not limited to: increased exposure based on the following: a user's geo-location, date and/or time of year, carrier type, etc. These variables can then assist with the education, awareness and potential prevention of disease.