Applications of the 1000 Genomes Project resources

Zheng-Bradley, Xiangqun; Flicek, Paul

doi:10.1093/bfgp/elw027

Cited by 39 publications

(31 citation statements)

References 83 publications

(92 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…All 1000 Genomes data were generated from samples with broad consent for open, public release of de-identified genetic data (2). The open nature of the data has led to its widespread use for various applications, ranging from reference panels for genotype imputation to prioritizing variants for further study to serving as a test bed for methods development (3). In order to ensure the continued usability of this valuable data collection for these and other purposes, we established the International Genome Sample Resource (IGSR) in 2015 to sustain, improve and expand the resources generated by the 1000 Genomes Project.…”

Section: Introductionmentioning

confidence: 99%

The international Genome sample resource (IGSR): A worldwide collection of genome variation incorporating the 1000 Genomes Project data

et al. 2016

Self Cite

View full text Add to dashboard Cite

The International Genome Sample Resource (IGSR; http://www.internationalgenome.org) expands in data type and population diversity the resources from the 1000 Genomes Project. IGSR represents the largest open collection of human variation data and provides easy access to these resources. IGSR was established in 2015 to maintain and extend the 1000 Genomes Project data, which has been widely used as a reference set of human variation and by researchers developing analysis methods. IGSR has mapped all of the 1000 Genomes sequence to the newest human reference (GRCh38), and will release updated variant calls to ensure maximal usefulness of the existing data. IGSR is collecting new structural variation data on the 1000 Genomes samples from long read sequencing and other technologies, and will collect relevant functional data into a single comprehensive resource. IGSR is extending coverage with new populations sequenced by collaborating groups. Here, we present the new data and analysis that IGSR has made available. We have also introduced a new data portal that increases discoverability of our data—previously only browseable through our FTP site—by focusing on particular samples, populations or data sets of interest.

show abstract

Section: Introductionmentioning

confidence: 99%

The international Genome sample resource (IGSR): A worldwide collection of genome variation incorporating the 1000 Genomes Project data

et al. 2016

Self Cite

View full text Add to dashboard Cite

show abstract

“…The 1000 Genomes Project will soon become "The International Genome Sample Resource" with all sequenced reads being re-mapped to the GRCh38 map producing new variants calls specific to this assembly. It will also expand the global catalogue of freely available sequence information by incorporating Russian samples, new African populations and whole genome sequences from the Simons Genome Diversity Project [60]. Data from the CAAPA project is also available at the database of Genotypes and Phenotypes (dbGaP) and can be used to explore the option of "custom reference panels" for imputation in African Americans and other admixed populations from Latin America and the Caribbean.…”

Section: Discussionmentioning

confidence: 99%

Genotype Imputation Performance of Three Reference Panels Using African Ancestry Individuals

Vergara

Parker

Franco

et al. 2018

Preprint

View full text Add to dashboard Cite

Genotype imputation is used to estimate unobserved genotypes from genome-wide maker data, to increase genome coverage and power for genome-wide association studies. Imputation has been most successful for European ancestry populations in which very large reference panels are available. Smaller subsets of African descent populations are available in 1000 Genomes (1000G), the Consortium on Asthma among African-Ancestry Populations in the Americas (CAAPA) and the Haplotype Reference Consortium (HRC). We aimed to compare the performance of these reference panels when imputing variation in 3,747 African Americans (AA) from 2 cohorts (HCV and COPDGene) genotyped using the Illumina Omni family of microarrays. The haplotypes of 2,504 individuals (from 1000G), 883 (from CAAPA) and 32,611 (from HRC) were used as reference. We compared the performance of these panels based on number of variants, imputation quality, imputation accuracy and coverage. In both cohorts, 1000G imputed 1.5-1.6x more variants compared to CAAPA and 1.2x more variants than HRC. Similar findings were observed for variants with higher imputation quality (R 2 >0.5) and for rare, low frequency, and common variants. When merging the results of the three panels the total number of imputed variants was 62M-63M with 20M overlapping variants imputed by all three panels, and a range of 5 to 15M unique variants imputed exclusively with one of the three panels. For overlapping variants, imputation quality was highest for HRC, followed by 1000G, then CAAPA, and improved as the minor allele frequency increased. The 1000G, HRC and CAAPA participants of African ancestry provided high performance and accuracy for imputation of African American admixed individuals, increasing the total number of variants with high quality available for subsequent analyses. These three panels are complementary and would benefit from the development of an integrated African reference panel, including data from multiple sources and populations.

show abstract

“…WGS of tumors [19] is an unbiased approach that provides extensive genomic information about a tumor at the single nucleotide level as well as structural variations such as large insertions, genomic rearrangements, gross deletions, and duplications. Using low-coverage WGS of many individuals from diverse human populations, the 1000 Genomes Project [20] has characterized common variations and a considerable proportion of rare variations present in human genomes. With falling costs, it is now possible to sequence genomes of many individuals for association studies and other genomic analyses [21].…”

Section: Genomicsmentioning

confidence: 99%

“…DaaS enables dynamic data access and provides up-to-date data that are accessible by a wide range of devices that are connected over the web. AWS provides a centralized repository of public data sets, including GenBank [35], 1000 Genomes [20], encyclopedia of DNA elements [36], etc., and all public datasets are delivered as services in AWS and thus can be seamlessly integrated into cloud-based applications.…”

Section: Epigenomics and Protein-dna Interactionsmentioning

confidence: 99%

See 1 more Smart Citation

Cloud Computing for Next-Generation Sequencing Data Analysis

Zhao¹,

Watrous²,

Zhang³

et al. 2017

Cloud Computing - Architecture and Applications

View full text Add to dashboard Cite

High-throughput next-generation sequencing (NGS) technologies have evolved rapidly and are reshaping the scope of genomics research. The substantial decrease in the cost of NGS techniques in the past decade has led to its rapid adoption in biological research and drug development. Genomics studies of large populations are producing a huge amount of data, giving rise to computational issues around the storage, transfer, and analysis of the data. Fortunately, cloud computing has recently emerged as a viable option to quickly and easily acquire the computational resources for large-scale NGS data analyses. Some cloud-based applications and resources have been developed specifically to address the computational challenges of working with very large volumes of data generated by NGS technology. In this chapter, we will review some cloud-based systems and solutions for NGS data analysis, discuss the practical hurdles and limitations in cloud computing, including data transfer and security, and share the lessons we learned from the implementation of Rainbow, a cloud-based tool for large-scale genome sequencing data analysis.

show abstract

Applications of the 1000 Genomes Project resources

Cited by 39 publications

References 83 publications

The international Genome sample resource (IGSR): A worldwide collection of genome variation incorporating the 1000 Genomes Project data

The international Genome sample resource (IGSR): A worldwide collection of genome variation incorporating the 1000 Genomes Project data

Genotype Imputation Performance of Three Reference Panels Using African Ancestry Individuals

Cloud Computing for Next-Generation Sequencing Data Analysis

Contact Info

Product

Resources

About