scholarly journals Application of Graph Theory to the elaboration of personal genomic data for genealogical research

2015 ◽  
Vol 1 ◽  
pp. e27 ◽  
Author(s):  
Vincenzo Palleschi ◽  
Luca Pagani ◽  
Stefano Pagnotta ◽  
Giuseppe Amato ◽  
Sergio Tofanelli
Keyword(s):  
Graph Theory ◽  
Genetic Relationships ◽  
Genomic Data ◽  
Real Data ◽  
Personal Genomic ◽  
Explicit Consent ◽  
Genome Sharing ◽  
Genealogical Information

In this communication a representation of the links between DNA-relatives based on Graph Theory is applied to the analysis of personal genomic data to obtain genealogical information. The method is tested on both simulated and real data and its applicability to the field of genealogical research is discussed. We envisage the proposed approach as a valid tool for a streamlined application to the publicly available data generated by many online personal genomic companies. In this way, anonymized matrices of pairwise genome sharing counts can help to improve the retrieval of genetic relationships between customers who provide explicit consent to the treatment of their data.

scholarly journals Application of Graph Theory to the elaboration of personal genomic data for genealogical research

2015 ◽  
Author(s):  
Vincenzo Palleschi ◽  
Luca Pagani ◽  
Stefano Pagnotta ◽  
Giuseppe Amato ◽  
Sergio Tofanelli
Keyword(s):  
Graph Theory ◽  
Genetic Relationship ◽  
Genomic Data ◽  
Real Data ◽  
Personal Genomic ◽  
Explicit Consent ◽  
Genome Sharing ◽  
Genealogical Information

In this communication a representation of the links between DNA-relatives based on Graph Theory is applied to the analysis of personal genomic data to obtain genealogical information. The method is tested on real data and discussed its applicability to the field of genealogical research. We envisage the proposed approach as a valid tool for a streamlined application to the publicly available data generated by many online personal genomic companies. By this way, anonymized matrices of pairwise genome sharing counts will enable to improve the retrieval of genetic relationship between customers who provided explicit consent to the treatment of their data.

scholarly journals Application of Graph Theory to the elaboration of personal genomic data for genealogical research

2015 ◽  
Author(s):  
Vincenzo Palleschi ◽  
Luca Pagani ◽  
Stefano Pagnotta ◽  
Giuseppe Amato ◽  
Sergio Tofanelli
Keyword(s):  
Graph Theory ◽  
Genetic Relationship ◽  
Genomic Data ◽  
Real Data ◽  
Personal Genomic ◽  
Explicit Consent ◽  
Genome Sharing ◽  
Genealogical Information

In this communication a representation of the links between DNA-relatives based on Graph Theory is applied to the analysis of personal genomic data to obtain genealogical information. The method is tested on real data and discussed its applicability to the field of genealogical research. We envisage the proposed approach as a valid tool for a streamlined application to the publicly available data generated by many online personal genomic companies. By this way, anonymized matrices of pairwise genome sharing counts will enable to improve the retrieval of genetic relationship between customers who provided explicit consent to the treatment of their data.

Genetic Data, Genome Understanding, and Socially Relevant Information

2021 ◽  
pp. 7-18
Author(s):  
Dara Hallinan
Keyword(s):  
Genetic Analysis ◽  
Genetic Relationships ◽  
Genomic Data ◽  
Genetic Data ◽  
Relevant Information ◽  
Significant Information ◽  
Multiple Factors ◽  
Phenotype Data ◽  
Wide Range ◽  
Socially Relevant

This chapter discusses the range of types of data which might be subject to genetic analysis to produce socially relevant information. These genetic data include raw genomic data as well as other types of data, such as phenotype data and inheritance data. Genetic analysis of these types of data is currently capable of producing a wide range of socially relevant information, including information concerning identity, genetic relationships, phenotype, health, and social and behavioural traits. It is not the case, however, that each type of genetic data can be subject to only one type of genetic analysis to produce only one type of socially relevant information. Rather, each type of genetic data, particularly genomic data, can be subject to multiple types of genetic analysis. Nor is it necessarily the case that genetic analyses produce socially relevant information which is completely accurate. Rather, the degree of accuracy of information will usually depend on multiple factors. The chapter then looks at the range of parties about whom socially significant information may be produced.

scholarly journals 333 Animal –GRIN a platform for animal genetic information

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 49-49
Author(s):  
Harvey D Blackburn ◽  
Ted Manahan ◽  
Carrie S Wilson ◽  
Wenkai Fu ◽  
Eduardo Cajueiro ◽  
...  
Keyword(s):  
Genetic Relationships ◽  
Genomic Data ◽  
Gene Bank ◽  
Genomic Information ◽  
Landscape Genomics ◽  
Bank Managers ◽  
On Line ◽  
The U.S ◽  
Ruby On Rails

Abstract An information system, Animal-GRIN, has been constructed as part of the U.S., Brazilian, and Canadian livestock genetic resource programs. It is designed to provide information to gene bank managers, the research community, and livestock producers about livestock breeds and subpopulations acquired in gene bank collections. The system was developed using a range of free software tools, including: MySQL, Ruby on Rails, Java Script, etc. The system is dynamic and publically accessible (https://nrrc.ars.usda.gov/A-GRIN). Exemplary information in Animal-GRIN consists of: animal identifiers, number and type of samples in the collection, pedigrees, coefficients of genetic relationships between animals within a breed, breeding values, phenotypes, and geographic source. To meet the national need for the long term archiving of genomic information developed with public funds, Animal-GRIN was expanded to store and make publically available genomic information (SNP) from any SNP chip, including custom products. Researchers are encouraged to submit their data upon completion of their publically funded projects. With the drill down concept, users can search the database for genomic information, physical samples associated with the genomic information, and phenotypic information on specific animals. Once animals of interest are found, on-line tools enable users to request either germplasm samples or genomic data. Progress in meeting genetic security for a breed’s collection can also be viewed. To date the U.S. collection has 52,639 animals with almost a million samples representing 36 species, 167 breeds, and 331 subpopulations and these have been entered into Animal-GRIN. Genomic data has been acquired on 1,899 animals representing 36 breeds. The next phase of Animal-GRIN development will be development of landscape genomics components. Acquisition of germplasm samples and associated genomic information are a continuing effort.

scholarly journals DNA Compass: a secure, client-side site for navigating personal genetic information

2016 ◽  
Author(s):  
Charles Curnin ◽  
Assaf Gordon ◽  
Yaniv Erlich
Keyword(s):  
Large Scale ◽  
Genomic Data ◽  
Personal Genomic ◽  
The Public ◽  
Direct To Consumer ◽  
The Status ◽  
And Performance ◽  
Precision Medicine Initiative ◽  
Client Side ◽  
Number Of Individuals

AbstractMotivationMillions of individuals have access to raw genomic data using direct-to-consumer companies. The advent of large-scale sequencing projects, such as the Precision Medicine Initiative, will further increase the number of individuals with access to their own genomic information. However, querying genomic data requires a computer terminal – an impediment for the general public.ResultsDNA Compass is a website designed to empower the public by enabling simple navigation of personal genomic data. Users can query the status of their genomic variants for over 400 conditions or tens of millions of documented SNPs. DNA Compass presents the relevant genotypes of the user side-by-side with explanatory scientific resources. The genotypes data never leaves the user’s computer, a feature that provides improved security and performance. Nearly 2500 unique users have used our tool, mainly from the general genetic genealogy community, demonstrating its utility.AvailabilityDNA Compass is freely available on https://[email protected]

Sign in / Sign up

Export Citation Format

Share Document