Genomes Project Data Research Articles

LDexpress: an online tool for integrating population-specific linkage disequilibrium patterns with tissue-specific expression data

Genome-wide association studies have identified thousands of genetic susceptibility loci associated with cancer as well as other traits and diseases. Mapping germline variation in identified genetic susceptibility regions to alterations in nearby gene expression nominates candidate genes potentially related to disease risk for further functional investigation. We developed LDexpress as an online resource that integrates population-specific linkage disequilibrium data from the 1000 Genomes (1000G) project and tissue-specific expression data from the Genotype-Tissue Expression project to better study regional germline variation impacting gene expression. LDexpress is a publicly available web tool designed to be easy to use, flexible to conduct a wide range of variant queries, and quick to efficiently investigate dozens of query variants across multiple tissue types. We demonstrate the utility of LDexpress using example genomic queries and anticipate this tool will accelerate understanding of disease etiology by uncovering associations of regional germline variation to nearby gene expression.

Role of Sex on the Genetic Susceptibility to Childhood Asthma in Latinos and African Americans.

Asthma is a respiratory disease whose prevalence changes throughout the lifespan and differs by sex, being more prevalent in males during childhood and in females after puberty. In this study, we assessed the influence of sex on the genetic susceptibility to childhood asthma in admixed populations. Sex-interaction and sex-stratified genome-wide association studies (GWAS) were performed in 4291 Latinos and 1730 African Americans separately, and results were meta-analyzed. Genome-wide (p ≤ 9.35 × 10−8) and suggestive (p ≤ 1.87 × 10−6) population-specific significance thresholds were calculated based on 1000 Genomes Project data. Additionally, protein quantitative trait locus (pQTL) information was gathered for the suggestively associated variants, and enrichment analyses of the proteins identified were carried out. Four independent loci showed interaction with sex at a suggestive level. The stratified GWAS highlighted the 17q12-21 asthma locus as a contributor to asthma susceptibility in both sexes but reached genome-wide significance only in females (p-females < 9.2 × 10−8; p-males < 1.25 × 10−2). Conversely, genetic variants upstream of ligand-dependent nuclear receptor corepressor-like gene (LCORL), previously involved in height determination and spermatogenesis, were associated with asthma only in males (minimum p = 5.31 × 10−8 for rs4593128). Enrichment analyses revealed an overrepresentation of processes related to the immune system and highlighted differences between sexes. In conclusion, we identified sex-specific polymorphisms that could contribute to the differences in the prevalence of childhood asthma between males and females.

Significant interpopulation differentiation at candidate loci may underlie ethnic disparities in the prevalence of uterine fibroids

Uterine fibroids (UF) are a significant health problem bearing a substantial economic burden. The prevalence of the disease is disparate in populations of different ethnic ancestry being the highest in Africans. This study analysed worldwide population differentiation at the genomewide association study (GWAS)-significant UF-associated loci to test a hypothesis that population structure at risk loci might underlie the observed interethnic disparities in the prevalence. In total, 28 single-nucleotide polymorphism (SNP) with the GWAS significance for European Caucasians were analysed in female cohorts of the European, admixed American, African, east Asian, and South Asian populations retrieved from the 1000 Genomes Project data. Common population genetic structure estimators, polygenic risk score (unweighted and weighted) were computed. According to the Fisher's exact test, the populations were significantly differentiated (P<< 10-5) at the UF risk loci. The polygenic risk scores did not differ significantly when calculated across all loci. However, they differed when only loci with risk alleles showing the enrichment/depletion patterns correlating with the documented ethnicity-specific risk of the disease were included in the calculation. The population genetic structure at the UF risk loci is apparently a significant factor underlying the observed between-ethnic disparities in the disease prevalence.

Inference of recent admixture using genotype data

The inference of biogeographic ancestry (BGA) has become a focus of forensic genetics. Misinference of BGA can have profound unwanted consequences for investigations and society. We show that recent admixture can lead to misclassification and erroneous inference of ancestry proportions, using state of the art analysis tools with (i) simulations, (ii) 1000 genomes project data, and (iii) two individuals analyzed using the ForenSeq DNA Signature Prep Kit. Subsequently, we extend existing tools for estimation of individual ancestry (IA) by allowing for different IA in both parents, leading to estimates of parental individual ancestry (PIA), and a statistical test for recent admixture. Estimation of PIA outperforms IA in most scenarios of recent admixture. Furthermore, additional information about parental ancestry can be acquired with PIA that may guide casework.

Variant calling across 505 openly consented samples from four Gambian populations on GRCh38

The International Genome Sample Resource (IGSR) repository was established to maximise the utility of human genetic data derived from openly consented samples within the research community. Here we describe variant detection in 505 samples from four populations in The Gambia, using the GRCh38 reference genome, adding to the range of populations for which this has been done and, importantly, making allele frequencies available. A multi-caller site discovery process was applied along with imputation and phasing to produce a phased biallelic single nucleotide variant (SNV) and insertion/deletion (INDEL) call set. Variation had not previously been explored on the GRCh38 human genome assembly for 387 of the samples. Compared to our previous work with the 1000 Genomes Project data on GRCh38, we identified over nine million novel SNVs and over 870 thousand novel INDELs.

Intronic LINE-1 insertion in SLCO1B3 as a highly prevalent cause of rotor syndrome in East Asian population.

Rotor syndrome is caused by digenic loss-of-function variants in SLCO1B1 and SLCO1B3 but only a few studies have reported co-occurring inactivating variants from both genes. A rotor syndrome-causing long interspersed element-1 (LINE-1) insertion in SLCO1B3 had been reported to be highly prevalent in the Japanese population but there has been no additional report. In spite of its known association with various human diseases, LINE-1 is hard to detect with current sequencing technologies. In this study, we aimed to devise a method to screen the LINE-1 insertion variant and investigate the frequency of this variant in various populations. A chimeric sequence, thatwas generated by concatenating the reference sequence at the junction and a part of inserted LINE-1 sequence, was searched from 725 raw sequencing data files. In cases containing the chimeric sequence, confirmatory long-range PCR and gap-PCR were performed. In total, 95 (13.1%) of 725 patients were positive for the chimeric sequence, and all were confirmed to have the SLCO1B3 LINE-1 insertion by PCR-based tests. The same chimeric sequence was searched from the 1000 Genomes Project data repository and the carrier frequency was remarkably high in the East Asian populations (10.1%), especially in Southern Han Chinese (18.5%), but almost absent in other populations. This SLCO1B3 LINE-1 insertion should be screened in a population-specific manner under suspicion of Rotor syndrome and the methods proposed in this study would enable this in a simple way.

CABE-RY: A PAM-flexible dual-mutation base editor for reliable modeling of multi-nucleotide variants

Multi-nucleotide variants (MNVs) represent an important type of genetic variation and have biological and clinical significance. To simulate MNVs, we designed four dual-mutation base editors combining hA3A(Y130F), TadA8e(V106W), and protospacer adjacent motif (PAM)-flexible SpRY and selected cytosine and adenine base editor-SpRY (CABE-RY), which had the best editing performance, for further study. Characterization and comparison showed that CABE-RY had a smaller DNA editing window and lower RNA off-target edits than the corresponding single base editors. Thus, we have established a versatile tool to efficiently simulate MNVs over the genome, which could be very useful for functional studies on MNVs in humans.

Large palindromes on the primate X Chromosome are preserved by natural selection.

Mammalian sex chromosomes carry large palindromes that harbor protein-coding gene families with testis-biased expression. However, there are few known examples of sex-chromosome palindromes conserved between species. We identified 26 palindromes on the human X Chromosome, constituting more than 2% of its sequence, and characterized orthologous palindromes in the chimpanzee and the rhesus macaque using a clone-based sequencing approach that incorporates full-length nanopore reads. Many of these palindromes are missing or misassembled in the current reference assemblies of these species’ genomes. We find that 12 human X palindromes have been conserved for at least 25 million years, with orthologs in both chimpanzee and rhesus macaque. Insertions and deletions between species are significantly depleted within the X palindromes’ protein-coding genes compared to their noncoding sequence, demonstrating that natural selection has preserved these gene families. The spacers that separate the left and right arms of palindromes are a site of localized structural instability, with seven of 12 conserved palindromes showing no spacer orthology between human and rhesus macaque. Analysis of the 1000 Genomes Project data set revealed that human X-palindrome spacers are enriched for deletions relative to arms and flanking sequence, including a common spacer deletion that affects 13% of human X Chromosomes. This work reveals an abundance of conserved palindromes on primate X Chromosomes and suggests that protein-coding gene families in palindromes (most of which remain poorly characterized) promote X-palindrome survival in the face of ongoing structural instability.

Geospatial Paradigm of Nucleotide Substitution within the Gene Family Encoding Plasma Membrane H+-ATPase Pumps in Arabidopsis thaliana

The PM H+-ATPase gene family consists of 12 members in Arabidopsis thaliana denoted to Auto-inhibited H+-ATPase 1-12 (AHA1-AHA12). This gene family performs crucial roles in many aspects of plant growth and development such as ion and metabolite transportation, pollen development, stomatal opening, signalling process, and adaptation to abiotic stresses especially thermal changes. The H+-ATPase action dynamically fluctuates during thermal changes in order to enhance adaptation strategies in plants. Based on the fact that surface temperature on average is typically warmer in lower latitudes and cooler in higher latitudes, the association of PM H+-ATPase genetic variants (SNPs) with latitude intervals was studied using chi-square testing of 1001 Genomes project data. The results indicated a significant association between nucleotide substitution and latitude interval, and therefore a geospatial paradigm of PM H+-ATPase nucleotide substitution was established. A&gt;T and T&gt;A substitutions showed a close positive association with higher latitudes (cold climate) and negative association with lower latitudes (warm climate), and vice versa for A&gt;G. Most of the nucleotide substitutions were associated with extreme cold and warm climates while cold climate had more impact. The most significant signal of PM H+-ATPase genes strategy for adaptation to cold climate was A&gt;T nucleotide substitution. Also, the results showed that the most high-impact SNPs were identified in coding regions and related to premature stop codons.

Shall genomic correlation structure be considered in copy number variants detection?

Copy number variation has been identified as a major source of genomic variation associated with disease susceptibility. With the advent of whole-exome sequencing (WES) technology, massive WES data have been generated, allowing for the identification of copy number variants (CNVs) in the protein-coding regions with direct functional interpretation. We have previously shown evidence of the genomic correlation structure in array data and developed a novel chromosomal breakpoint detection algorithm, LDcnv, which showed significantly improved detection power through integrating the correlation structure in a systematic modeling manner. However, it remains unexplored whether the genomic correlation exists in WES data and how such correlation structure integration can improve the CNV detection accuracy. In this study, we first explored the correlation structure of the WES data using the 1000 Genomes Project data. Both real raw read depth and median-normalized data showed strong evidence of the correlation structure. Motivated by this fact, we proposed a correlation-based method, CORRseq, as a novel release of the LDcnv algorithm in profiling WES data. The performance of CORRseq was evaluated in extensive simulation studies and real data analysis from the 1000 Genomes Project. CORRseq outperformed the existing methods in detecting medium and large CNVs. In conclusion, it would be more advantageous to model genomic correlation structure in detecting relatively long CNVs. This study provides great insights for methodology development of CNV detection with NGS data.

Identification and analysis of the structure, expression and nucleotide polymorphism of the GPAT gene family in rice

Glycerol-3-phosphate acyltransferase ( GPAT ), a family of membrane-bound enzymes, is involved in the initial step of glycerolipid biosynthesis in plant cells. In this study, we performed an in-silico genome-wide analysis of rice ( Oryza sativa ) and identified 26 GPAT genes annotated according to their chromosomal locations. Putative orthologs of the rice genes were identified in five monocot and dicot plant species. The study characterized the rice GPAT gene structures, genome localization, gene duplications, conserved motifs, and cis-elements in their promoter regions. Segmental duplication contributed to the expansion of the GPAT family in rice with purifying selection pressure. We analyzed the phylogeny between six different monocots and dicot GPAT genes and compared them with rice orthologs and their exon-intron structure to understand their evolutionary relationships. Based on RNA-seq data, we found rice GPAT genes have diverse expression patterns. Some genes had high expression in specific tissues, including; OsGPAT 2,13 and 8 in the root; OsGPAT 3 and 10 in the shoot; OsGPAT4 in panicle; OsGPAT 25 in the leaf; OsGPAT 8, 25, and 26 in the anther and OsGPAT 10, and 25 in the seed. Expression analysis under salt, cold, and heat conditions showed that GPAT genes positively respond to abiotic stress conditions. Some genes demonstrated sustained up-regulation in specific stresses including; OsGPAT2, OsGPAT18, OsGPAT19, OsGPAT5, and OsGPAT12 in cold stress; OsGPAT6, 11, 13, 18, 19 and 21 in heat stress; and OsGPAT 5, 14, 18, 19 and 24 during salt stress. Moreover, we used the 3000 rice genomes project (3 K RGP) data to analyze nucleotide polymorphism at each rice GPAT locus among hundred Chinese rice varieties. This study will provide a framework for future studies and further broaden our insights into the evolution and functional elucidation of GPAT genes in rice. • An in silico Genome-wide analysis explored 26 rice GPAT genes. • GPAT s showed low nucleotide diversity using 3000 rice genome data from 100 varieties. • Putative orthologs of the rice genes in 5 species clustered in the same clades of a phylogenetic tree. • Many GPAT genes responded positively to cold, heat, and salt stresses. • Segmental duplication under purifying selection pressure contributed to gene expansion.

PCAmatchR: a flexible R package for optimal case-control matching using weighted principal components.

A concern when conducting genome-wide association studies (GWAS) is the potential for population stratification, i.e. ancestry-based genetic differences between cases and controls, that if not properly accounted for, could lead to biased association results. We developed PCAmatchR as an open source R package for performing optimal case-control matching using principal component analysis (PCA) to aid in selecting controls that are well matched by ancestry to cases. PCAmatchR takes user supplied PCA outputs and selects matching controls for cases by utilizing a weighted Mahalanobis distance metric which weights each principal component by the percentage of genetic variation explained. Results from the 1000 Genomes Project data demonstrate both the functionality and performance of PCAmatchR for selecting matching controls for case populations as well as reducing inflation of association test statistics. PCAmatchR improves genomic similarity between matched cases and controls, which minimizes the effects of population stratification in GWAS analyses. PCAmatchR is freely available for download on GitHub (https://github.com/machiela-lab/PCAmatchR) or through CRAN (https://CRAN.R-project.org/package=PCAmatchR). Supplementary data are available at Bioinformatics online.

Noninvasive prenatal paternity determination using microhaplotypes: a pilot study

BackgroundThe use of noninvasive techniques to determine paternity prenatally is increasing because it reduces the risks associated with invasive procedures. Current methods, based on SNPs, use the analysis of at least 148 markers, on average.MethodsTo reduce the number of regions, we used microhaplotypes, which are chromosomal segments smaller than 200 bp containing two or more SNPs. Our method employs massively parallel sequencing and analysis of microhaplotypes as genetic markers. We tested 20 microhaplotypes and ascertained that 19 obey Hardy–Weinberg equilibrium and are independent, and data from the 1000 Genomes Project were used for population frequency and simulations.ResultsWe performed simulations of true and false paternity, using the 1000 Genomes Project data, to confirm if the microhaplotypes could be used as genetic markers. We observed that at least 13 microhaplotypes should be used to decrease the chances of false positives. Then, we applied the method in 31 trios, and it was able to correctly assign the fatherhood in cases where the alleged father was the real father, excluding the inconclusive results. We also cross evaluated the mother-plasma duos with the alleged fathers for false inclusions within our data, and we observed that the use of at least 15 microhaplotypes in real data also decreases the false inclusions.ConclusionsIn this work, we demonstrated that microhaplotypes can be used to determine prenatal paternity by using only 15 regions and with admixtures of DNA.

Enrichment in conservative amino acid changes among fixed and standing missense variations in slowly evolving proteins.

The process of molecular evolution has many elements that are not yet fully understood. Evolutionary rates are known to vary among protein coding and noncoding DNAs, and most of the observed changes in amino acid or nucleotide sequences are assumed to be non-adaptive by the neutral theory of molecular evolution. However, it remains unclear whether fixed and standing missense changes in slowly evolving proteins are more or less neutral compared to those in fast evolving genes. Here, based on the evolutionary rates as inferred from identity scores between orthologs in human and Rhesus Macaques (Macaca mulatta), we found that the fraction of conservative substitutions between species was significantly higher in their slowly evolving proteins. Similar results were obtained by using four different methods of scoring conservative substitutions, including three that remove the impact of substitution probability, where conservative changes require fewer mutations. We also examined the single nucleotide polymorphisms (SNPs) by using the 1000 Genomes Project data and found that missense SNPs in slowly evolving proteins also had a higher fraction of conservative changes, especially for common SNPs, consistent with more non-conservative substitutions and hence stronger natural selection for SNPs, particularly rare ones, in fast evolving proteins. These results suggest that fixed and standing missense variants in slowly evolving proteins are more likely to be neutral.

Evaluation of the InnoTyper21® system for the applications into trace and degraded DNA in the Korean population.

The InnoTyper 21® Human Identification kit consists of amelogenin and 20 bi-allelic Alus, retrotransposon markers existing abundantly in human genome. The InnoTyper 21® kit produces shorter amplicons (60-125 bp) than conventional short tandem repeat (STR) genotyping kit, then it is effective on the analysis of challengeable forensic samples including insufficient or highly degraded DNAs. Also, as the genotyping with InnoTyper21® kit is compatible with PCR and capillary electrophoresis, it is easy to incorporate into the workflow in forensic laboratories. In the internal validation of InnoTyper21® kit on sensitivity, degradation, and mixture studies for the evaluation in this study, we acquired full profiles on analyzing small concentration DNA (as low as 25 pg) and highly degraded DNA (up to 105 degradation index value). Through the Korean population study, forensic statistical parameters were investigated and a specific variant of T insertion in NBC51 was confirmed in six samples. Comparison of Korean population with five populations or 1000 Genomes Project data show Korean specific substructure. It is expected that the InnoTyper 21® kit will be used into the actual forensic cases, utilizing the population study investigated through this research.

Efficiently Summarizing Relationships in Large Samples: A General Duality Between Statistics of Genealogies and Genomes.

As a genetic mutation is passed down across generations, it distinguishes those genomes that have inherited it from those that have not, providing a glimpse of the genealogical tree relating the genomes to each other at that site. Statistical summaries of genetic variation therefore also describe the underlying genealogies. We use this correspondence to define a general framework that efficiently computes single-site population genetic statistics using the succinct tree sequence encoding of genealogies and genome sequence. The general approach accumulates sample weights within the genealogical tree at each position on the genome, which are then combined using a summary function; different statistics result from different choices of weight and function. Results can be reported in three ways: by site, which corresponds to statistics calculated as usual from genome sequence; by branch, which gives the expected value of the dual site statistic under the infinite sites model of mutation, and by node, which summarizes the contribution of each ancestor to these statistics. We use the framework to implement many currently defined statistics of genome sequence (making the statistics’ relationship to the underlying genealogical trees concrete and explicit), as well as the corresponding branch statistics of tree shape. We evaluate computational performance using simulated data, and show that calculating statistics from tree sequences using this general framework is several orders of magnitude more efficient than optimized matrix-based methods in terms of both run time and memory requirements. We also explore how well the duality between site and branch statistics holds in practice on trees inferred from the 1000 Genomes Project data set, and discuss ways in which deviations may encode interesting biological signals.

WDR34 mutation from anencephaly patients impaired both SHH and PCP signaling pathways

Neural tube defects (NTDs) are debilitating human congenital abnormalities due to failure of neural tube closure. Sonic Hedgehog (SHH) signaling is required for dorsal–ventral patterning of the neural tube. The loss of activation in SHH signaling normally causes holoprosencephaly while the loss of inhibition causes exencephaly due to failure in neural tube closure. WDR34 is a dynein intermedia chain component which is required for SHH activation. However, Wdr34 knockout mouse exhibit exencephaly. Here we screened mutations in WDR34 gene in 100 anencephaly patients of Chinese Han population. Compared to 1000 Genome Project data, two potentially disease causing missense mutations of WDR34 gene (c.1177G>A; p.G393S and c.1310A>G; p.Y437C) were identified in anencephaly patients. These two mutations did not affect the protein expression level of WDR34. Luciferase reporter and endogenous target gene expression level showed that both mutations are lose-of-function mutations in SHH signaling. Surprisingly, WDR34 could promote planar cell polarity (PCP) signaling and the G393S lost this promoting effect on PCP signaling. Morpholino knockdown of wdr34 in zebrafish caused severe convergent extension defects and pericardial abnormalities. The G393S mutant has less rescuing effects than both WT and Y437C WDR34 in zebrafish. Our results suggested that mutation in WDR34 could contribute to human NTDs by affecting both SHH and PCP signaling.

Sex differences in the genetic architecture of depression

The prevalence and clinical characteristics of depressive disorders differ between women and men; however, the genetic contribution to sex differences in depressive disorders has not been elucidated. To evaluate sex-specific differences in the genetic architecture of depression, whole exome sequencing of samples from 1000 patients (70.7% female) with depressive disorder was conducted. Control data from healthy individuals with no psychiatric disorder (n = 72, 26.4% female) and East-Asian subpopulation 1000 Genome Project data (n = 207, 50.7% female) were included. The genetic variation between men and women was directly compared using both qualitative and quantitative research designs. Qualitative analysis identified five genetic markers potentially associated with increased risk of depressive disorder in females, including three variants (rs201432982 within PDE4A, and rs62640397 and rs79442975 within FDX1L) mapping to chromosome 19p13.2 and two novel variants (rs820182 and rs820148) within MYO15B at the chromosome 17p25.1 locus. Depressed patients homozygous for these variants showed more severe depressive symptoms and higher suicidality than those who were not homozygotes (i.e., heterozygotes and homozygotes for the non-associated allele). Quantitative analysis demonstrated that the genetic burden of protein-truncating and deleterious variants was higher in males than females, even after permutation testing. Our study provides novel genetic evidence that the higher prevalence of depressive disorders in women may be attributable to inherited variants.

Accurate prediction of genome-wide RNA secondary structure profile based on extreme gradient boosting.

RNA secondary structure plays a vital role in fundamental cellular processes, and identification of RNA secondary structure is a key step to understand RNA functions. Recently, a few experimental methods were developed to profile genome-wide RNA secondary structure, i.e. the pairing probability of each nucleotide, through high-throughput sequencing techniques. However, these high-throughput methods have low precision and cannot cover all nucleotides due to limited sequencing coverage. Here, we have developed a new method for the prediction of genome-wide RNA secondary structure profile from RNA sequence based on the extreme gradient boosting technique. The method achieves predictions with areas under the receiver operating characteristic curve (AUC) >0.9 on three different datasets, and AUC of 0.888 by another independent test on the recently released Zika virus data. These AUCs are consistently >5% greater than those by the CROSS method recently developed based on a shallow neural network. Further analysis on the 1000 Genome Project data showed that our predicted unpaired probabilities are highly correlated (>0.8) with the minor allele frequencies at synonymous, non-synonymous mutations, and mutations in untranslated regions, which were higher than those generated by RNAplfold. Moreover, the prediction over all human mRNA indicated a consistent result with previous observation that there is a periodic distribution of unpaired probability on codons. The accurate predictions by our method indicate that such model trained on genome-wide experimental data might be an alternative for analytical methods. The GRASP is available for academic use at https://github.com/sysu-yanglab/GRASP. Supplementary data are available online.

Efficient toolkit implementing best practices for principal component analysis of population genetic data

ABSTRACTMotivationPrincipal component analysis (PCA) of genetic data is routinely used to infer ancestry and control for population structure in various genetic analyses. However, conducting PCA analyses can be complicated and has several potential pitfalls. These pitfalls include (i) capturing linkage disequilibrium (LD) structure instead of population structure, (ii) projected PCs that suffer from shrinkage bias, (iii) detecting sample outliers and (iv) uneven population sizes. In this work, we explore these potential issues when using PCA, and present efficient solutions to these. Following applications to the UK Biobank and the 1000 Genomes project datasets, we make recommendations for best practices and provide efficient and user-friendly implementations of the proposed solutions in R packages bigsnpr and bigutilsr.ResultsFor example, we find that PC19–PC40 in the UK Biobank capture complex LD structure rather than population structure. Using our automatic algorithm for removing long-range LD regions, we recover 16 PCs that capture population structure only. Therefore, we recommend using only 16–18 PCs from the UK Biobank to account for population structure confounding. We also show how to use PCA to restrict analyses to individuals of homogeneous ancestry. Finally, when projecting individual genotypes onto the PCA computed from the 1000 Genomes project data, we find a shrinkage bias that becomes large for PC5 and beyond. We then demonstrate how to obtain unbiased projections efficiently using bigsnpr. Overall, we believe this work would be of interest for anyone using PCA in their analyses of genetic data, as well as for other omics data.Availability and implementationR packages bigsnpr and bigutilsr can be installed from either CRAN or GitHub (see https://github.com/privefl/bigsnpr). A tutorial on the steps to perform PCA on 1000G data is available at https://privefl.github.io/bigsnpr/articles/bedpca.html. All code used for this paper is available at https://github.com/privefl/paper4-bedpca/tree/master/code.Supplementary information Supplementary data are available at Bioinformatics online.