scholarly journals Matching phenotypes to whole genomes: Lessons learned from four iterations of the personal genome project community challenges

2017 ◽  
Vol 38 (9) ◽  
pp. 1266-1276 ◽  
Author(s):  
Binghuang Cai ◽  
Biao Li ◽  
Nikki Kiga ◽  
Janita Thusberg ◽  
Timothy Bergquist ◽  
...  
Keyword(s):  
Genome Project ◽  
Lessons Learned ◽  
Personal Genome ◽  
Personal Genome Project ◽  
Whole Genomes

scholarly journals The Personal Genome Project-UK: an open access resource of human multi-omics data

2019 ◽  
Author(s):  
Olga Chervova ◽  
Lucia Conde ◽  
José Afonso Guerra-Assunção ◽  
Ismail Moghul ◽  
Amy P. Webster ◽  
...  
Keyword(s):  
Open Access ◽  
Genome Project ◽  
Reference Panel ◽  
Integrated Analysis ◽  
Personal Genome ◽  
Omics Data ◽  
Personal Genome Project ◽  
Medical Genomics ◽  
Open Access Resource ◽  
Access Resource

AbstractIntegrative analysis of multi-omics data is a powerful approach for gaining functional insights into biological and medical processes. Conducting these multifaceted analyses on human samples is often complicated by the fact that the raw sequencing output is rarely available under open access. The Personal Genome Project UK (PGP-UK) is one of few resources that recruits its participants under open consent and makes the resulting multi-omics data freely and openly available. As part of this resource, we describe the PGP-UK multi-omics reference panel consisting of ten genomic, methylomic and transcriptomic data. Specifically, we outline the data processing, quality control and validation procedures which were implemented to ensure data integrity and exclude sample mix-ups. In addition, we provide a REST API to facilitate the download of the entire PGP-UK dataset. The data are also available from two cloud-based environments, providing platforms for free integrated analysis. In conclusion, the genotype-validated PGP-UK multi-omics human reference panel described here provides a valuable new open access resource for integrated analyses in support of personal and medical genomics.

scholarly journals Harvard Personal Genome Project: lessons from participatory public research

10.1186/gm527 ◽  
2014 ◽  
Vol 6 (2) ◽  
pp. 10 ◽  
Author(s):  
Madeleine P Ball ◽  
Jason R Bobe ◽  
Michael F Chou ◽  
Tom Clegg ◽  
Preston W Estep ◽  
...  
Keyword(s):  
Genome Project ◽  
Personal Genome ◽  
Public Research ◽  
Personal Genome Project

scholarly journals The Personal Genome Project-UK, an open access resource of human multi-omics data

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Olga Chervova ◽  
Lucia Conde ◽  
José Afonso Guerra-Assunção ◽  
Ismail Moghul ◽  
Amy P. Webster ◽  
...  
Keyword(s):  
Open Access ◽  
Genome Project ◽  
Reference Panel ◽  
Integrated Analysis ◽  
Personal Genome ◽  
Omics Data ◽  
Personal Genome Project ◽  
Medical Genomics ◽  
Open Access Resource ◽  
Access Resource

Abstract Integrative analysis of multi-omics data is a powerful approach for gaining functional insights into biological and medical processes. Conducting these multifaceted analyses on human samples is often complicated by the fact that the raw sequencing output is rarely available under open access. The Personal Genome Project UK (PGP-UK) is one of few resources that recruits its participants under open consent and makes the resulting multi-omics data freely and openly available. As part of this resource, we describe the PGP-UK multi-omics reference panel consisting of ten genomic, methylomic and transcriptomic data. Specifically, we outline the data processing, quality control and validation procedures which were implemented to ensure data integrity and exclude sample mix-ups. In addition, we provide a REST API to facilitate the download of the entire PGP-UK dataset. The data are also available from two cloud-based environments, providing platforms for free integrated analysis. In conclusion, the genotype-validated PGP-UK multi-omics human reference panel described here provides a valuable new open access resource for integrated analyses in support of personal and medical genomics.

scholarly journals The Sri Lankan Personal Genome Project: an overview

2011 ◽  
Vol 2 (1) ◽  
pp. 4 ◽  
Author(s):  
Vajira H.W. Dissanayake ◽  
Pubudu S. Samarakoon ◽  
Vinod Scaria ◽  
Ashok Patowary ◽  
Sridar Sivasubbu ◽  
...  
Keyword(s):  
Genome Project ◽  
Personal Genome ◽  
Sri Lankan ◽  
Personal Genome Project

scholarly journals GenomeChronicler: The Personal Genome Project UK Genomic Report Generator Pipeline

2020 ◽  
Vol 11 ◽  
Author(s):  
José Afonso Guerra-Assunção ◽  
Lucia Conde ◽  
Ismail Moghul ◽  
Amy P. Webster ◽  
Simone Ecker ◽  
...  
Keyword(s):  
Genome Project ◽  
Personal Genome ◽  
Personal Genome Project

scholarly journals Personal genome project

2012 ◽  
Vol 13 (9) ◽  
pp. 599-599 ◽  
Author(s):  
Bryony Jones
Keyword(s):  
Genome Project ◽  
Personal Genome ◽  
Personal Genome Project

scholarly journals GenomeChronicler: The Personal Genome Project UK Genomic Report Generator Pipeline

2020 ◽  
Author(s):  
José Afonso Guerra-Assunção ◽  
Lucia Conde ◽  
Ismail Moghul ◽  
Amy P. Webster ◽  
Simone Ecker ◽  
...  
Keyword(s):  
Service Providers ◽  
Genome Project ◽  
Phenotypic Traits ◽  
Personal Genome ◽  
Whole Genome ◽  
Sequencing Data ◽  
Potential Health ◽  
Personal Genome Project ◽  
Link Type ◽  
A Genome

AbstractIn recent years, there has been a significant increase in whole genome sequencing data of individual genomes produced by research projects as well as direct to consumer service providers. While many of these sources provide their users with an interpretation of the data, there is a lack of free, open tools for generating reports exploring the data in an easy to understand manner.GenomeChronicler was developed as part of the Personal Genome Project UK (PGP-UK) to address this need. PGP-UK provides genomic, transcriptomic, epigenomic and self-reported phenotypic data under an open-access model with full ethical approval. As a result, the reports generated by GenomeChronicler are intended for research purposes only and include information relating to potentially beneficial and potentially harmful variants, but without clinical curation.GenomeChronicler can be used with data from whole genome or whole exome sequencing, producing a genome report containing information on variant statistics, ancestry and known associated phenotypic traits. Example reports are available from the PGP-UK data page (personalgenomes.org.uk/data).The objective of this method is to leverage existing resources to find known phenotypes associated with the genotypes detected in each sample. The provided trait data is based primarily upon information available in SNPedia, but also collates data from ClinVar, GETevidence and gnomAD to provide additional details on potential health implications, presence of genotype in other PGP participants and population frequency of each genotype.The analysis can be run in a self-contained environment without requiring internet access, making it a good choice for cases where privacy is essential or desired: any third party project can embed GenomeChronicler within their off-line safe-haven environments. GenomeChronicler can be run for one sample at a time, or in parallel making use of the Nextflow workflow manager.The source code is available from GitHub (https://github.com/PGP-UK/GenomeChronicler), container recipes are available for Docker and Singularity, as well as a pre-built container from SingularityHub (https://singularity-hub.org/collections/3664) enabling easy deployment in a variety of settings. Users without access to computational resources to run GenomeChronicler can access the software from the Lifebit CloudOS platform (https://lifebit.ai/cloudos) enabling the production of reports and variant calls from raw sequencing data in a scalable fashion.

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