ArticleBMC genomics2019
Evaluating the quality of the 1000 genomes project data.
Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
36 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Genetic Insights into Peripheral Artery Disease: A Narrative Review.Biomedicines · 2025Review
- Bioinformatic and genomic analysis identifies C allele of APOE rs7412 as the most prominent variant limiting extreme human longevity.Scientific reports · 2025Article
- Characterizing genetic pathways unique to autism spectrum disorder at multiple levels of biological analysis.Molecular autism · 2024Article
- Somatic mutation phasing and haplotype extension using linked-reads in multiple myeloma.bioRxiv : the preprint server for biology · 2024Article
- Genomic Reference Resource for African Cattle: Genome Sequences and High-Density Array Variants.Scientific data · 2024Article
- Investigation of missense mutation-related type 1 diabetes mellitus through integrating genomic databases and bioinformatic approach.Genomics & informatics · 2024Article
- Characterizing Genetic Pathways Unique to Autism Spectrum Disorder at Multiple Levels of Biological Analysis.medRxiv : the preprint server for health sciences · 2024Article
- HATCHet2: clone- and haplotype-specific copy number inference from bulk tumor sequencing data.Genome biology · 2024Article
- Low-coverage whole genome sequencing for a highly selective cohort of severe COVID-19 patients.GigaByte (Hong Kong, China) · 2024Article
- Tumor sequencing of African ancestry reveals differences in clinically relevant alterations across common cancers.Cancer cell · 2023Article
- HATCHet2: clone- and haplotype-specific copy number inference from bulk tumor sequencing data.bioRxiv : the preprint server for biology · 2023Article
- Genomic Landscape of Normal and Breast Cancer Tissues in a Hungarian Pilot Cohort.International journal of molecular sciences · 2023Article
- Localizing Post-Admixture Adaptive Variants with Object Detection on Ancestry-Painted Chromosomes.Molecular biology and evolution · 2023Article
- Enhancing genomic mutation data storage optimization based on the compression of asymmetry of sparsity.Frontiers in genetics · 2023Article
- Article
- Quality control of large genome datasets.HGG advances · 2022Article
- Strengthening Causal Inference in Exposomics Research: Application of Genetic Data and Methods.Environmental health perspectives · 2022Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
backgroundData from the 1000 Genomes project is quite often used as a reference for human genomic analysis. However, its accuracy needs to be assessed to understand the quality of predictions made using this reference. We present here an assessment of the genotyping, phasing, and imputation accuracy data in the 1000 Genomes project. We compare the phased haplotype calls from the 1000 Genomes project to experimentally phased haplotypes for 28 of the same individuals sequenced using the 10X Genomics platform.
resultsWe observe that phasing and imputation for rare variants are unreliable, which likely reflects the limited sample size of the 1000 Genomes project data. Further, it appears that using a population specific reference panel does not improve the accuracy of imputation over using the entire 1000 Genomes data set as a reference panel. We also note that the error rates and trends depend on the choice of definition of error, and hence any error reporting needs to take these definitions into account.
conclusionsThe quality of the 1000 Genomes data needs to be considered while using this database for further studies. This work presents an analysis that can be used for these assessments.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.