Browse
Submit Data
Databases
API
Help

Dataset Information

27 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Estimating exome genotyping accuracy by comparing to data from large scale sequencing projects.

ABSTRACT: With exome sequencing becoming a tool for mutation detection in routine diagnostics there is an increasing need for platform-independent methods of quality control. We present a genotype-weighted metric that allows comparison of all the variant calls of an exome to a high-quality reference dataset of an ethnically matched population. The exome-wide genotyping accuracy is estimated from the distance to this reference set, and does not require any further knowledge about data generation or the bioinformatics involved. The distances of our metric are visualized by non-metric multidimensional scaling and serve as an intuitive, standardizable score for the quality assessment of exome data.

SUBMITTER: Heinrich V

PROVIDER: S-EPMC3978951 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Estimating exome genotyping accuracy by comparing to data from large scale sequencing projects.

Heinrich Verena V Kamphans Tom T Stange Jens J Parkhomchuk Dmitri D Hecht Jochen J Dickhaus Thorsten T Robinson Peter N PN Krawitz Peter M PM

Genome medicine 20130731 7

With exome sequencing becoming a tool for mutation detection in routine diagnostics there is an increasing need for platform-independent methods of quality control. We present a genotype-weighted metric that allows comparison of all the variant calls of an exome to a high-quality reference dataset of an ethnically matched population. The exome-wide genotyping accuracy is estimated from the distance to this reference set, and does not require any further knowledge about data generation or the bio ...[more]

PMID: 23902830

Similar Datasets

Accuracy of short tandem repeats genotyping tools in whole exome sequencing data.

Project description:Background: Short tandem repeats are an important source of genetic variation. They are highly mutable and repeat expansions are associated dozens of human disorders, such as Huntington's disease and spinocerebellar ataxias. Technical advantages in sequencing technology have made it possible to analyse these repeats at large scale; however, accurate genotyping is still a challenging task. We compared four different short tandem repeats genotyping tools on whole exome sequencing data to determine their genotyping performance and limits, which will aid other researchers in choosing a suitable tool and parameters for analysis. Methods: The analysis was performed on the Simons Simplex Collection dataset, where we used a novel method of evaluation with accuracy determined by the rate of homozygous calls on the X chromosome of male samples. In total we analysed 433 samples and around a million genotypes for evaluating tools on whole exome sequencing data. Results: We determined a relatively good performance of all tools when genotyping repeats of 3-6 bp in length, which could be improved with coverage and quality score filtering. However, genotyping homopolymers was challenging for all tools and a high error rate was present across different thresholds of coverage and quality scores. Interestingly, dinucleotide repeats displayed a high error rate as well, which was found to be mainly caused by the AC/TG repeats. Overall, LobSTR was able to make the most calls and was also the fastest tool, while RepeatSeq and HipSTR exhibited the lowest heterozygous error rate at low coverage. Conclusions: All tools have different strengths and weaknesses and the choice may depend on the application. In this analysis we demonstrated the effect of using different filtering parameters and offered recommendations based on the trade-off between the best accuracy of genotyping and the highest number of calls.

| S-EPMC7327730 | biostudies-literature

Exome sequencing followed by large-scale genotyping fails to identify single rare variants of large effect in idiopathic generalized epilepsy.

Project description:Idiopathic generalized epilepsy (IGE) is a complex disease with high heritability, but little is known about its genetic architecture. Rare copy-number variants have been found to explain nearly 3% of individuals with IGE; however, it remains unclear whether variants with moderate effect size and frequencies below what are reliably detected with genome-wide association studies contribute significantly to disease risk. In this study, we compare the exome sequences of 118 individuals with IGE and 242 controls of European ancestry by using next-generation sequencing. The exome-sequenced epilepsy cases include study subjects with two forms of IGE, including juvenile myoclonic epilepsy (n = 93) and absence epilepsy (n = 25). However, our discovery strategy did not assume common genetic control between the subtypes of IGE considered. In the sequence data, as expected, no variants were significantly associated with the IGE phenotype or more specific IGE diagnoses. We then selected 3,897 candidate epilepsy-susceptibility variants from the sequence data and genotyped them in a larger set of 878 individuals with IGE and 1,830 controls. Again, no variant achieved statistical significance. However, 1,935 variants were observed exclusively in cases either as heterozygous or homozygous genotypes. It is likely that this set of variants includes real risk factors. The lack of significant association evidence of single variants with disease in this two-stage approach emphasizes the high genetic heterogeneity of epilepsy disorders, suggests that the impact of any individual single-nucleotide variant in this disease is small, and indicates that gene-based approaches might be more successful for future sequencing studies of epilepsy predisposition.

| S-EPMC3415540 | biostudies-literature

An estimate of large-scale sequencing accuracy.

Project description:The accuracy of large-scale DNA sequencing is difficult to estimate without redundant effort. We have found that the mobile genetic element IS10, a component of the transposon Tn10, has contaminated a significant number of clones in the public databases, as a result of the use of the transposon in bacterial cloning strain construction. These contaminations need to be annotated as such. More positively, by defining the range of sequence variation in IS10, we have been able to determine that the rate of sequencing errors is very low, most likely surpassing the stated aim of one error or less in ten thousand bases.

| S-EPMC1083690 | biostudies-literature

Estimating the occurrence of primary ubiquinone deficiency by analysis of large-scale sequencing data.

Project description:Primary ubiquinone (UQ) deficiency is an important subset of mitochondrial disease that is caused by mutations in UQ biosynthesis genes. To guide therapeutic efforts we sought to estimate the number of individuals who are born with pathogenic variants likely to cause this disorder. We used the NCBI ClinVar database and literature reviews to identify pathogenic genetic variants that have been shown to cause primary UQ deficiency, and used the gnomAD database of full genome or exome sequences to estimate the frequency of both homozygous and compound heterozygotes within seven genetically-defined populations. We used known population sizes to estimate the number of afflicted individuals in these populations and in the mixed population of the USA. We then performed the same analysis on predicted pathogenic loss-of-function and missense variants that we identified in gnomAD. When including only known pathogenic variants, our analysis predicts 1,665 affected individuals worldwide and 192 in the USA. Adding predicted pathogenic variants, our estimate grows to 123,789 worldwide and 1,462 in the USA. This analysis predicts that there are many undiagnosed cases of primary UQ deficiency, and that a large proportion of these will be in developing regions of the world.

| S-EPMC5735152 | biostudies-literature

Phylogeny-driven target selection for large-scale genome-sequencing (and other) projects.

Project description:Despite the steadily decreasing costs of genome sequencing, prioritizing organisms for sequencing remains important in large-scale projects. Phylogeny-based selection is of interest to identify those organisms whose genomes can be expected to differ most from those that have already been sequenced. Here, we describe a method that infers a phylogenetic scoring independent of which set of organisms has previously been targeted, which is computationally simple and easy to apply in practice. The scoring itself, as well as pre- and post-processing of the data, is illustrated using two real-world examples in which the method has already been applied for selecting targets for genome sequencing. These projects are the JGI CSP Genomic Encyclopedia of Bacteria and Archaea phase I, targeting 1,000 type strains, and, on a smaller-scale, the phylogenomics of the Roseobacter clade. Potential artifacts of the method are discussed and compared to a selection approach based on the taxonomic classification.

| S-EPMC3746418 | biostudies-literature

Estimating the prevalence of allelic variants in the transthyretin gene by analysing large-scale sequencing data.

Project description:Transthyretin amyloidosis (ATTR amyloidosis) is a rare disease characterised by extracellular deposition of amyloid fibrils composed by transthyretin. ATTR amyloidosis can be sub-classified as wild-type ATTR (ATTR-wt) or as hereditary amyloidosis (ATTR-m); the prevalence of both types are likely underestimated. There are tools that can help us to study ATTR-m, as gnomAD database. Our primary aim was to estimate prevalence of variants, especially amyloidogenic variants, in the TTR gene using gnomAD database. We analysed TTR missense variants found in gnomAD. The variables studied were classified according to their clinical significance and according to the different populations. We found 71 missense variants in the TTR gene. Eleven variants were described as affects function variants (prevalence 1:230). The most frequently detected variant were c.424G>A (p.(Val142Ile)) (prevalence 1:332, MAF 0.00151) and c.148G>A (p.(Val50Met)) (prevalence 1:4924, MAF 0.000102), which represented 88% and 5%, respectively, of all affects function variants detected. Seventeen variants were classified as probably affects function, 29 as unknown variants, 4 as probably does not affect function and 10 as does not affect function variants. In terms of different populations, c.424G>A (p.(Val142Ile)) was especially prevalent in African population (MAF 0.01602; prevalence of 1:31) and c.148G>A (p.(Val50Met)) in European population (MAF 0.000179; prevalence of 1:2792). Prevalence of amyloidogenic variants in the general population was higher than prevalence heretofore described. This difference could be explained by incomplete penetrance of the disease, but other factors contributing to this fact, fundamentally the underdiagnosis of the disease.

| S-EPMC6461877 | biostudies-literature

Exome sequencing followed by large-scale genotyping suggests a limited role for moderately rare risk factors of strong effect in schizophrenia.

Project description:Schizophrenia is a severe psychiatric disorder with strong heritability and marked heterogeneity in symptoms, course, and treatment response. There is strong interest in identifying genetic risk factors that can help to elucidate the pathophysiology and that might result in the development of improved treatments. Linkage and genome-wide association studies (GWASs) suggest that the genetic basis of schizophrenia is heterogeneous. However, it remains unclear whether the underlying genetic variants are mostly moderately rare and can be identified by the genotyping of variants observed in sequenced cases in large follow-up cohorts or whether they will typically be much rarer and therefore more effectively identified by gene-based methods that seek to combine candidate variants. Here, we consider 166 persons who have schizophrenia or schizoaffective disorder and who have had either their genomes or their exomes sequenced to high coverage. From these data, we selected 5,155 variants that were further evaluated in an independent cohort of 2,617 cases and 1,800 controls. No single variant showed a study-wide significant association in the initial or follow-up cohorts. However, we identified a number of case-specific variants, some of which might be real risk factors for schizophrenia, and these can be readily interrogated in other data sets. Our results indicate that schizophrenia risk is unlikely to be predominantly influenced by variants just outside the range detectable by GWASs. Rather, multiple rarer genetic variants must contribute substantially to the predisposition to schizophrenia, suggesting that both very large sample sizes and gene-based association tests will be required for securely identifying genetic risk factors.

| S-EPMC3415532 | biostudies-literature

XLID-causing mutations and associated genes challenged in light of data from large-scale human exome sequencing.

Project description:Because of the unbalanced sex ratio (1.3-1.4 to 1) observed in intellectual disability (ID) and the identification of large ID-affected families showing X-linked segregation, much attention has been focused on the genetics of X-linked ID (XLID). Mutations causing monogenic XLID have now been reported in over 100 genes, most of which are commonly included in XLID diagnostic gene panels. Nonetheless, the boundary between true mutations and rare non-disease-causing variants often remains elusive. The sequencing of a large number of control X chromosomes, required for avoiding false-positive results, was not systematically possible in the past. Such information is now available thanks to large-scale sequencing projects such as the National Heart, Lung, and Blood (NHLBI) Exome Sequencing Project, which provides variation information on 10,563 X chromosomes from the general population. We used this NHLBI cohort to systematically reassess the implication of 106 genes proposed to be involved in monogenic forms of XLID. We particularly question the implication in XLID of ten of them (AGTR2, MAGT1, ZNF674, SRPX2, ATP6AP2, ARHGEF6, NXF5, ZCCHC12, ZNF41, and ZNF81), in which truncating variants or previously published mutations are observed at a relatively high frequency within this cohort. We also highlight 15 other genes (CCDC22, CLIC2, CNKSR2, FRMPD4, HCFC1, IGBP1, KIAA2022, KLF8, MAOA, NAA10, NLGN3, RPL10, SHROOM4, ZDHHC15, and ZNF261) for which replication studies are warranted. We propose that similar reassessment of reported mutations (and genes) with the use of data from large-scale human exome sequencing would be relevant for a wide range of other genetic diseases.

| S-EPMC3738825 | biostudies-literature

Quantifying unobserved protein-coding variants in human populations provides a roadmap for large-scale sequencing projects.

Project description:As new proposals aim to sequence ever larger collection of humans, it is critical to have a quantitative framework to evaluate the statistical power of these projects. We developed a new algorithm, UnseenEst, and applied it to the exomes of 60,706 individuals to estimate the frequency distribution of all protein-coding variants, including rare variants that have not been observed yet in the current cohorts. Our results quantified the number of new variants that we expect to identify as sequencing cohorts reach hundreds of thousands of individuals. With 500K individuals, we find that we expect to capture 7.5% of all possible loss-of-function variants and 12% of all possible missense variants. We also estimate that 2,900 genes have loss-of-function frequency of <0.00001 in healthy humans, consistent with very strong intolerance to gene inactivation.

| S-EPMC5095512 | biostudies-literature

Parallel sequencing lives, or what makes large sequencing projects successful.

Project description:T47D_rep2 and b1913e6c1_51720e9cf were 2 Hi-C samples. They were born and processed at the same time, yet their fates were very different. The life of b1913e6c1_51720e9cf was simple and fruitful, while that of T47D_rep2 was full of accidents and sorrow. At the heart of these differences lies the fact that b1913e6c1_51720e9cf was born under a lab culture of Documentation, Automation, Traceability, and Autonomy and compliance with the FAIR Principles. Their lives are a lesson for those who wish to embark on the journey of managing high-throughput sequencing data.

| S-EPMC5714127 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data