Cited by 438Genomics and Phylogenetic StudiesGenetic Associations and EpidemiologyGenetic diversity and population structure

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SNP Calling, Genotype Calling, and Sample Allele Frequency Estimation from New-Generation Sequencing Data

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Nielsen, Rasmus, Korneliussen, Thorfinn, Albrechtsen, Anders, Li, Yingrui, Wang, Jun·2012·PLoS ONE

DOI 10.1371/journal.pone.0037558PMC PMC3404070

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Abstract

We present a statistical framework for estimation and application of sample allele frequency spectra from New-Generation Sequencing (NGS) data. In this method, we first estimate the allele frequency spectrum using maximum likelihood. In contrast to previous methods, the likelihood function is calculated using a dynamic programming algorithm and numerically optimized using analytical derivatives. We then use a bayesian method for estimating the sample allele frequency in a single site, and show how the method can be used for genotype calling and SNP calling. We also show how the method can be extended to various other cases including cases with deviations from Hardy-Weinberg equilibrium. We evaluate the statistical properties of the methods using simulations and by application to a real data set.

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ESTIMATING F -STATISTICS FOR THE ANALYSIS OF POPULATION STRUCTURE
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BackgroundMethodInfluential
A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data
Li, H. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr509 · Cited by 6,454

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“…with < 10% missing data to the B EAGLE PL format with VCF TOOLS version 0.1.14, computed the site allele frequency spectrum in ANGSD version 0.9.15 (Nielsen et al. 2012; Fuma-galli et al. 2013; Korneliussen et al. 2014), the sample covariance matrix using NGS C OVAR (Fumagalli et al. 2013), and…”
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“Genome-Wide Heterozygosity and Genomic Inbreeding Coefficients (FROH) The population scaled mutation rate theta (θ = 4 Neμ [74]) was estimated using mlrho [75], an approximate measure of expected heterozygosity per site under the infinite sites model, where Ne denotes the effective population size and μ denotes mutati…”
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“2009) and compared it with the true SFS using maximum-likelihood numerical optimization based on simulations of 50,000,000 sites drawn from the WGS data using the realSFS option implemented in ANGSD v 0.933 (Nielsen et al .”
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“This finding could thus explain why studies often find no association between in silico and realised allele frequencies [36–38].”
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“Methods also exist that take read depth into account when estimating allele frequencies and probabilities that genotype calls are correct [9] and for estimating relatedness coefficients [10].”
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“…environmental clines (Larsen et al. 2007; Johannesson et al. 2011; Teacher et al. 2013; Wang et al. 2013; Andre et al. 2016; Brennan et al. 2016) and gene-associated SNPs have been used as high resolution tools for population genomic studies and population traceability (Nielsen et al. 2012).”
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Self-citation
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“The direct estimation approach infers the maximum likelihood estimate (MLE) of the SFS by an EM algorithm (Li, 2011) or a Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm (Nielsen et al. , 2012), assuming independence across all individuals and sites.”
Method
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“This SNP calling scheme performs worse than those Bayesian methods (such as, Li 2011; Nielsen et al. 2012), but is computationally inexpensive and works for large sample data in our case.”
Method
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“FST measures were calculated for each of the gen - omic regions under selection for every possible pair of islands using realSFS in ANGSD with a minimum of 4 individuals for each SNP for each island (Nielsen et al. 2012).”
Method
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Background
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“1 (Liu & Fu, 2020 ) from the folded SFS, both keeping or discarding single-tons.”
Method
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Background
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Method
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Method
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Hofmeister, N. R., Stuart, K. C., Warren, W. C., Werner, S. J., Melissa Bateson, B., Ball, G. F., Buchanan, K. L., Burt, D. W., Cardilini, A. P. A., Cassey, P., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.05.19.442026 · Cited by 9
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“To do this, the folded site allele frequency likelihood for each species and each sampling timepoint separately ( N = 5–13; see Table S2) was calculated in angsd (0.925) (Korneliussen et al., 2014 ; Nielsen et al., 2012).”
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Method
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McCarthy, M. L., Refoyo-Martínez, A., Ferguson, S. H., Rosing‐Asvid, A., Dietz, R., Cahsan, B. D., Schreiber, L., Lorenzen, E. D., Hansen, R. G., Stimmelmayr, R., et al. (2025) · Molecular Ecology · doi:10.1111/mec.17643 · Cited by 8
“In addition, we estimated pair-wise F ST values to quantify the genomic differentiation between population pairings using the population pairwise 2D-SFS calculated with realSFS (Nielsen et al. 2012) and implemented in ANGSD for sites retained in the Global dataset.”
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“Bias in our estimation of rare alleles, which can occur using pool- seq data (Nielsen et al., 2012), may also have contributed to low estimates of Tajima's D. Tajima's D were significantly lower in outlier regions in A. f. lacustris, A. f. killarnensis, and A. macedonica, but not in A. alosa except…”
Background
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“…of, for example, reduced representation sequencing (Davey et al. 2011) or low-depth whole genome sequencing data, along with substantial improvements in the methods available to analyze them (Nielsen et al. 2012; Korneliussen et al. 2013; Fumagalli et al. 2014), this is now becoming feasible.”
Self-citation
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Fontsere, C., Frandsen, P., Hernández-Rodríguez, J., Niemann, J., Scharff‐Olsen, C. H., Vallet, D., Gouar, P. L., Ménard, N., Navarro, A., SIEGISMUND, H. R., et al. (2021) · BMC Genomics · doi:10.1186/s12864-021-08025-y · Cited by 8
“To assess global levels of heterozygosity, the unfolded SFS was calculated for each 405 sample separately, including thirteen gorilla whole-genomes representative of all gorilla 406 subspecies [29, 30], using ANGSD [31] and realSFS [72] only in the target space with the 407”
Method
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“With this exponential growth of sequence data, rich biological data analytics applications, such as sequence alignment (including short read alignment), genome assembly, single nucleotide polymorphism (SNP) detection, and genome-wide association study (GWAS) are developed and studied.”
BackgroundInfluential
Can demographic histories explain long‐term isolation and recent pulses of asymmetric gene flow between highly divergent grey fox lineages?
Preckler‐Quisquater, S., Kierepka, E. M., Reding, D. M., Piaggio, A. J., & Sacks, B. N. (2023) · Molecular Ecology · doi:10.1111/mec.17105 · Cited by 7
“We used ANGSD to generate a full SNP dataset, removing bad reads (- remove_bads 1) and those that aligned to multiple regions in the genome (- uniqueOnly 1).”
MethodInfluential
Balancing selection contributed to domestication of autopolyploid sugarcane (Saccharum officinarum L.)
Arro, J., Park, J., Wai, C. M., VanBuren, R., Pan, Y., Nagai, C., da Silva, J. A., & Ming, R. (2016) · Euphytica · doi:10.1007/s10681-016-1672-8 · Cited by 8
“To further assess the nature of selection based on the relative proportion of rare and common alleles relative to neutrality, patterns of the site frequency spectrum (SFS) (Ronen et al. 2013) were evaluated for each species using ANGSD (Nielsen et al. 2012).”
Method
Finding Hybrid Incompatibilities Using Genome Sequences from Hybrid Populations
Blanckaert, A., & Payseur, B. A. (2021) · Molecular Biology and Evolution · doi:10.1093/molbev/msab168 · Cited by 8
“We recommend incorporating uncertainty in variant calling when building the SFS from sequencing reads (Nielsen et al. 2012) before applying our approach.”
Method
Genomic variation in captive deer mouse (Peromyscus maniculatus) populations
Lucius, M. D., Ji, H., Altomare, D., Doran, R., Torkian, B., Havighorst, A., Kaza, V., Zhang, Y., Gasparian, A. V., Magagnoli, J., et al. (2021) · BMC Genomics · doi:10.1186/s12864-021-07956-w · Cited by 7
“The methods used to calculate the thetas were done according to ANGSD’s website page on Thetas, Tajima, and Neutrality tests (http://www.popgen.dk/angsd/index.php/Thetas,Tajima,Neutrality_tests) (36 , 37).”
Population genetic analysis of bi-allelic structural variants from low-coverage sequence data with an expectation-maximization algorithm
Lucas‐Lledó, J. I., Vicente-Salvador, D., Aguado, C., & Cáceres, M. (2014) · BMC Bioinformatics · doi:10.1186/1471-2105-15-163 · Cited by 7
“…be used to obtain unbiased estimates of allele frequencies or site-frequency spectra, and likelihood-ratio tests can be used to address population-level hypotheses, such as Hardy-Weinberg equilibrium, population differentiation, linkage disequilibrium, genotype-phenotype association, etc [24,25].”
Demographic changes in Pleistocene sea turtles were driven by past sea level fluctuations affecting feeding habitat availability
van der Zee, J. P., Christianen, M. J. A., Bérubé, M., Nava, M. I., van der Wal, S., Berkel, J., Bervoets, T., zu Schlochtern, M. P. M., Becking, L. E., & Palsbøll, P. J. (2021) · Molecular Ecology · doi:10.1111/mec.16302 · Cited by 6
“The folded site frequency spectrum (SFS) was estimated from genotype likelihoods (Nielsen et al., 2012) using angsd version 0.925 (Korneliussen et al., 2014).”
MethodInfluential
Identification and analysis of snps in population of Vietnamese catfish (pangasianodon hypophthalmus), using next generation sequencing and snp validation
Vo, T. T. B. (2018) · MOJ Current Research & Reviews · doi:10.15406/mojcrr.2018.01.00003 · Cited by 7
Fast and accurate estimation of multidimensional site frequency spectra from low-coverage high-throughput sequencing data
Mas-Sandoval, À., Pope, N. S., Nielsen, K. N., Altinkaya, I., Fumagalli, M., & Korneliussen, T. S. (2022) · GigaScience · doi:10.1093/gigascience/giac032 · Cited by 7
“To solve this issue, statistical methods that compute a probability measure for each of the possible genotypes (the genotype likelihoods) and integrate over these probabilities in the downstream analyses have been proposed [5].”
Self-citation
Post-glacial expansion dynamics, not refugial isolation, shaped the genetic structure of a migratory bird, the yellow warblerPreprint
Miller, E. F., Leonardi, M., Xue, Z., Beyer, R. M., Krapp, M., Somveille, M., Somma, G. L., Delser, P. M., & Manica, A. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.05.10.443405 · Cited by 7
“These ANGSD genotype likelihood values were then used as input for NGSadmix to calculate population admixture, setting a K (presumed cluster number) value of 2 and keeping minimum informative individuals at 100.”
MethodInfluential
Modeling Biases from Low-Pass Genome Sequencing to Enable Accurate Population Genetic Inferences
da Fonseca, E. M., Tran, L. N., Mendoza, H., & Gutenkunst, R. N. (2025) · Molecular Biology and Evolution · doi:10.1093/molbev/msaf002 · Cited by 6
distAngsd: Fast and Accurate Inference of Genetic Distances for Next-Generation Sequencing Data
Zhao, L., Nielsen, R., & Korneliussen, T. S. (2022) · Molecular Biology and Evolution · doi:10.1093/molbev/msac119 · Cited by 6
“S4 for N) is essentially the same as equation (1) in Korneliussen et al. (2014), which is the two dimensional equivalent of the likelihood function presented in Keightley and Halligan (2011), Li (2011), and Nielsen et al. (2012).”
BackgroundSelf-citation
A genotype likelihood function for DNA mixtures
Crysup, B., & Woerner, A. E. (2022) · Forensic Science International Genetics · doi:10.1016/j.fsigen.2022.102776 · Cited by 6
Species-specific erosion of genetic diversity in grassland butterflies depends on landscape land cover
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The genomic origin of early maize in eastern North America
Ramos‐Madrigal, J., Fritz, G. J., Schroeder, B. A., Smith, B. D., Sánchez-Barreiro, F., Carøe, C., Runge, A. K. W., Boer, S., McGrath, K. M., Vieira, F. G., et al. (2024) · Cell · doi:10.1016/j.cell.2024.11.003 · Cited by 6
Genomic divergence between two sister Ostrya species through linked selection and recombination
Zhang, J., Zhang, S., Zheng, Z., Lu, Z., & Yang, Y. P. (2022) · Ecology and Evolution · doi:10.1002/ece3.9611 · Cited by 6
“We also estimated a folded joint site frequency spectrum for the two species with ANGSD v 0.933 (Nielsen et al., 2012), and then used fastsimcoal2 software (Excoffier et al., 2013) to investigate the history of population separation between O. japonica and O. chinensis.”
MethodInfluential
loco-pipe: an automated pipeline for population genomics with low-coverage whole-genome sequencing
Zhou, Z. T., Owens, G. L., Larson, W. A., Lou, R. N., & Sudmant, P. H. (2024) · Bioinformatics Advances · doi:10.1093/bioadv/vbae098 · Cited by 5
“Because individual genotypes cannot be confidently assigned from low sequencing depth, lcWGS relies on a suite of specialized software programs that account for genotype uncertainty using a probabilistic framework (Nielsen et al. 2012, 2011; Korneliussen et al. 2014).”
Ecological and biogeographic features shaped the complex evolutionary history of an iconic apex predator (Galeocerdo cuvier)
Lesturgie, P., Laine, H., Suwalski, A., Chifflet‐Belle, P., Delser, P. M., Clua, É., Jaquemet, S., Magalon, H., & Mona, S. (2022) · BMC Ecology and Evolution · doi:10.1186/s12862-022-02100-y · Cited by 9
“We generated pairwise site allele frequency likelihood files and then computed FST with the realSFS program in angsd [57] using SNPs with a minor allele frequency ≥ 0.”
Whole mitochondrial DNA sequencing improves resolution of population structure for Pacific green turtles (Chelonia mydas)
Frey, A., LaCasella, E. L., Jensen, M. P., & Dutton, P. H. (2025) · Frontiers in Marine Science · doi:10.3389/fmars.2025.1581306 · Cited by 5
Genomics of Population Differentiation in Humpback Dolphins,Sousaspp. in the Indo-Pacific Ocean
Amaral, A. R., Chanfana, C., Smith, B. D., Mansur, R. M., Collins, T., Baldwin, R., Minton, G., Parra, G. J., Krützen, M., Jefferson, T. A., et al. (2020) · Journal of Heredity · doi:10.1093/jhered/esaa055 · Cited by 5
A dense linkage map for a large repetitive genome: discovery of the sex-determining region in hybridizing fire-bellied toads ( Bombina bombina and Bombina variegata )
Nürnberger, B., Baird, S. J. E., Čížková, D., Bryjová, A., Mudd, A. B., Blaxter, M., & Szymura, J. M. (2021) · G3 Genes Genomes Genetics · doi:10.1093/g3journal/jkab286 · Cited by 6
A 14,000-year-old genome sheds light on the evolution and extinction of a Pleistocene vulture
Ericson, P. G. P., Irestedt, M., Zuccon, D., Larsson, P., Tison, J.-L., Emslie, S. D., Götherström, A., HUME, J. P., Werdelin, L., & Qu, Y. (2022) · Communications Biology · doi:10.1038/s42003-022-03811-0 · Cited by 5
Transcriptome-derived SNP markers for population assignment of sandfish, Holothuria (Metriatyla) scabra
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Concurrent invasions of European starlings in Australia and North America reveal population‐specific differentiation in shared genomic regions
Hofmeister, N. R., Stuart, K. C., Warren, W. C., Werner, S. J., Melissa Bateson, B., Ball, G. F., Buchanan, K. L., Burt, D. W., Cardilini, A. P. A., Cassey, P., et al. (2023) · Molecular Ecology · doi:10.1111/mec.17195 · Cited by 15
Flow modification associated with reduced genetic health of a river-breeding frog, Rana boyliiPreprint
Peek, R. A., O’Rourke, S. M., & Miller, M. R. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/316604 · Cited by 5
“Genome-wide F ST between population pairs was estimated by first calculating a site frequency spectrum (SFS) for each population (doSaf) (78) with ANGSD.”
Method
Signatures of selective sweeps in urban and rural white clover populations
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Fantastic beasts and how to sequence them: genomic approaches for obscure model organismsPreprint
Matz, M. V. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/165928 · Cited by 4
Entering the era of conservation genomics: Cost-effective assembly of the African wild dog genome using linked long readsPreprint
Armstrong, E. E., Taylor, R. W., Prost, S., Blinston, P., van der Meer, E., Madzikanda, H., Mufute, O., Mandisodza‐Chikerema, R. L., Stuelpnagel, J., Sillero‐Zubiri, C., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/195180 · Cited by 4
“First, a genome coverage of 20x is on the lower side of what is needed to reliably call genotypes (Nielsen et al. 2012).”
Background
Single Nucleotide Polymorphism Typing
Srinivasan, S., & Batra, J. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-809633-8.20127-1 · Cited by 4
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Sgarlata, G. M., Rasolondraibe, E., Salmona, J., Pors, B. L., Ralantoharijaona, T., Rakotonanahary, A. N., Jan, F., Manzi, S., Iribar, A., Zaonarivelo, J. R., et al. (2023) · Molecular Phylogenetics and Evolution · doi:10.1016/j.ympev.2023.107997 · Cited by 5
Linked Selection and Gene Density Shape Genome‐Wide Patterns of Diversification in Peatmosses
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“Using the expectation maximization (EM) algorithm, we optimized and polarized the SAF to obtain an ML estimate of the SFS for each species (Nielsen et al. 2012) and an ML estimate of the pairwise (2D) SFS for each species pair.”
Self-citation
Identification of the sex determination region and the development of a marker to distinguish males and females in megai abalone (Haliotis gigantea)
Kina, T., Hara, M., Hirase, S., & Kikuchi, K. (2024) · Aquaculture Reports · doi:10.1016/j.aqrep.2024.102592 · Cited by 3
Gene Expression and Gene Ontology Enrichment Analysis for H3K4me3 and H3K4me1 in Mouse Liver and Mouse Embryonic Stem Cell Using ChIP-Seq and RNA-Seq
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BATCAVE: calling somatic mutations with a tumor- and site-specific prior
Mannakee, B. K., & Gutenkunst, R. N. (2020) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqaa004 · Cited by 2
“Note however, that if the goal were not to best identify individual variants, but rather to best estimate the distribution of variant allele frequencies within the tumor, then a nonuniform frequency prior would be appropriate (58).”
Background
Evaluating probabilistic genotyping for low-pass DNA sequencing
Mandape, S. N., Kapema, K. B., Duque, T. M., Smuts, A., King, J. L., Crysup, B., Ge, J., Budowle, B., & Woerner, A. E. (2022) · Forensic science international. Genetics supplement series · doi:10.1016/j.fsigss.2022.10.001 · Cited by 3
Next-Generation Sequencing Data-Based Association Testing of a Group of Genetic Markers for Complex Responses Using a Generalized Linear Model Framework
Xu, Z. Q., Yan, S., Wu, C., Duan, Q., Chen, S., & Li, Y. (2023) · Mathematics · doi:10.3390/math11112560 · Cited by 2
Self-citation
Loss of genetic diversity and isolation by distance and by environment in populations of a keystone ungulate species
Maciel, F. D. G., O’Rourke, S., Jones, M. L., Hemstrom, W., Miller, M. R., Schmaedecke, G., Tambosi, L. R., Baptista, M. S. P., Keuroghlian, A., Nava, A. F. D., et al. (2024) · Conservation Genetics · doi:10.1007/s10592-024-01614-w · Cited by 3
“…pairs of sequences (Tajima 1983 ), and Watterson’s theta (θ w ), which is based on the number of segregating sites (Watterson 1975), in ANGSD for each chromosome (Korneliussen et al. 2013), using a site frequency spectrum (SFS; Nielsen et al. 2012) estimated in realSFS (Kornelius-sen et al. 2014).”
Optimized variant calling for estimating kinship.
Woerner, A., Mandape, S. N., Kapema, K. B., Duque, T., Smuts, A., King, J., Crysup, B., Wang, X.-W., Huang, M., Ge, J.-Y., et al. (2022) · Forensic Science International: Genetics · doi:10.1016/j.fsigen.2022.102785 · Cited by 5
Variation in linked selection and recombination drive genomic divergence during allopatric speciation of European and American aspensPreprint
Wang, J., Street, N. R., Scofield, D. G., & Ingvarsson, P. K. (2015) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/029561 · Cited by 3
Self-citation
Testing the ‘caves as islands’ model in two cave-obligate invertebrates with a genomic approachPreprint
Balogh, A., Ngo, L., Zigler, K. S., & Dixon, G. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.04.08.032789 · Cited by 3
“6 because they can fail to capture statistical uncertainty inherent to individual genotypes from NewGeneration Sequencing (NGS) data (Nielsen et al. 2012).”
BackgroundMethodInfluential
Population genomics of the island thrush elucidates one of earth’s great archipelagic radiationsPreprint
Reeve, A. H., Gower, G., Pujolar, J. M., Smith, B. T., Petersen, B., Olsson, U., Haryoko, T., Koane, B., Maiah, G., Blom, M. P. K., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.04.21.488757 · Cited by 3
“Pairwise F ST was calculated from genotype likelihoods using the folded joint (2D) allele frequency spectrum (Nielsen et al. 2012), as implemented in ANGSD (Korneliussen et al. 2014), configured to use the default Reynolds et al. (1983) F ST estimator.”
Method
The genomic landscape of adaptation to a new host plantPreprint
Steward, R., Nilsson, K. J., Ortega, J., Nolen, Z. J., Yan, C. Y., Huang, Y., Ayala-Lopez, J. A., & Runemark, A. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.04.17.537225 · Cited by 3
“We produced unfolded 1D and 2D site frequency spectra (SFS) for each population and population pair using the SAF files in realSFS (Nielsen et al. 2012).”
Method
High standing diversity masks extreme genetic erosion in a declining snakePreprint
Pozzi, A. V., Owens, J. B., Üveges, B., Major, T., Morris, E., Graham, S., Togridou, A., Papadopulos, A., Wüster, W., & Barlow, A. (2023) · bioRxiv · doi:10.1101/2023.09.19.557540 · Cited by 4
Inferring drift, genetic differentiation, and admixture graphs from low-depth sequencing dataPreprint
Rasmussen, M. S., Wiuf, C., & Albrechtsen, A. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.01.29.577762 · Cited by 3
Self-citation
Distinct intraspecific diversification dynamics in Neotropical montane versus lowland canopy birds (Thraupidae: Tangara ) revealed by whole-genome comparative phylogeography
Wacker, K. S., & Winger, B. M. (2025) · Evolution · doi:10.1093/evolut/qpaf247 · Cited by 2
Rare jackpot individuals drive rapid adaptation in Threespine Stickleback
Kwakye, A., Reid, K., Wund, M. A., Heins, D. C., Bell, M. A., & Veeramah, K. R. (2026) · Nature Communications · doi:10.1038/s41467-026-71236-y · Cited by 4
“Then, we used the -sites option from ANGSD to estimate the SFS for the 0-fold and 4-fold sites.”
Influential

Authors: Nielsen, R., Korneliussen, T., Albrechtsen, A., Li, Y., & Wang, J.
Affiliations: BGI Group (China) (CN)
University of Copenhagen (DK)
Corresponding author: Nielsen, Rasmus
Wang, Jun
ORCID: Nielsen, Rasmus
Korneliussen, Thorfinn
Albrechtsen, Anders
Li, Yingrui
Wang, Jun
Venue: PLoS ONE
Publisher: Public Library of Science (PLoS)
Published: 2012-07-24
Volume: 7
Issue: 7
Pages: e37558
ISSN: 1932-6203 (ISSN-L)
DOI: 10.1371/journal.pone.0037558
PMC: PMC3404070
OpenAlex: W2005287518
Cited by: 424
References: 39
Citations by year: 2026: 24 · 2025: 18 · 2024: 43 · 2023: 33 · 2022: 38 · 2021: 40 · 2020: 25 · 2019: 19 · 2018: 37 · 2017: 30 · 2016: 39 · 2015: 30 · 2014: 25 · 2013: 19 · 2012: 1
FWCI: 9.58
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0/ (unspecified)
Locations: PLoS ONE (publishedVersion, cc-by)
Europe PMC (PubMed Central) (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by)
RePEc: Research Papers in Economics (submittedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
eScholarship (California Digital Library) (submittedVersion)
eScholarship (California Digital Library) (submittedVersion, cc-by)
Figshare (submittedVersion, cc-by)
Funders: Villum Fonden (00007171)
National Institutes of Health
National Human Genome Research Institute (R01HG003229)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
Keywords: allele frequency estimation, allele frequency spectrum, SNP calling, genotype calling, next-generation sequencing, maximum likelihood estimation, Hardy-Weinberg equilibrium, genetic variation
MeSH terms: Algorithms, Bayes Theorem, Computer Simulation, Denmark, Gene Frequency, Genotype, Humans, ROC Curve, Software, Likelihood Functions, Computational Biology, Internet, Polymorphism, Single Nucleotide, White People, High-Throughput Nucleotide Sequencing, Exome

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SNP Calling, Genotype Calling, and Sample Allele Frequency Estimation from New-Generation Sequencing Data

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