The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
SNP Calling, Genotype Calling, and Sample Allele Frequency Estimation from New-Generation Sequencing Data
Open accessAbstract
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“due to the error rate of sequencing, the mixture of nonparenchymal cells and polyploidy of hepatocytes, this approach could not detect low-frequency single-nucleotide polymorphisms in hepatocytes11.”
From Genome editing with Cas9 in adult mice corrects a disease mutation and phenotype (2014) · cites this paper as [11]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
ESTIMATING F -STATISTICS FOR THE ANALYSIS OF POPULATION STRUCTURE
Weir, B. S., & Cockerham, C. C. (1984) · Evolution · doi:10.1111/j.1558-5646.1984.tb05657.x · Cited by 18,909 · cited 1×
“, [21]) also proceed from estimates of the SFS.”
BackgroundProceedings of the National Academy of Sciences of the United States of America
Dowling, J. E., & Wald, G. (2009) · Nutrition Reviews · doi:10.1111/j.1753-4887.1981.tb06752.x · Cited by 17,937
Numerical recipes in C: the art of scientific computing
(1993) · Choice Reviews Online · doi:10.5860/choice.30-5638 · Cited by 17,933
Numerical Recipes in C: The Art of Scientific Computing
Seiler, M. C., & Seiler, F. A. (1989) · Risk Analysis · doi:10.1111/j.1539-6924.1989.tb01007.x · Cited by 15,446
Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P. (1994) · Cited by 15,411
Statistical method for testing the neutral mutation hypothesis by DNA polymorphism.
Tajima, F. (1989) · Genetics · doi:10.1093/genetics/123.3.585 · Cited by 14,056
RNA-Seq: a revolutionary tool for transcriptomics
Wang, Z., Gerstein, M., & Snyder, M. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2484 · Cited by 13,174 · cited 1×
“, [5]), in population genetic studies (e.”
Estimating F-Statistics for the Analysis of Population Structure
Weir, B. S., & Cockerham, C. C. (1984) · Evolution · doi:10.2307/2408641 · Cited by 11,023
A map of human genome variation from population-scale sequencing.
The 1000 Genomes Project Consortium (2010) · Nature · doi:10.1038/nature09534 · Cited by 7,877 · cited 4×
“In fact, imputation based genotype calling will lead to a substantial increase in accuracy over other methods [7].”
BackgroundMethodInfluentialLi, H. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr509 · Cited by 6,454
Flagged first, then by citations
Cited by
Sorted by citations
Items 101–200 of 438
Pečnerová, P., Garcia‐Erill, G., Liu, X., Nursyifa, C., Waples, R. K., Santander, C. G., Quinn, L. J. E., Frandsen, P., Meisner, J., Stæger, F. F., et al. (2021) · Current Biology · doi:10.1016/j.cub.2021.01.064 · Cited by 68
“A genome-wide estimate of F ST (Table 1) for each pair of populations was computed directly from the 2d-SFS, estimated with realSFS, 28 using the Reich estimator.”
MethodSelf-citationA genome-wide scan for signatures of directional selection in domesticated pigs
Moon, S., Kim, T. H., Lee, K., Kwak, W., Lee, T., Lee, S.-W., Kim, M.-J., Cho, K., Kim, N., Chung, W.-H., et al. (2015) · BMC Genomics · doi:10.1186/s12864-015-1330-x · Cited by 71
“More details on the algorithm for estimating the posterior probability can be found in [48].”
BackgroundSelf-citationBrunet, M. A., Levesque, S. A., Hunting, D. J., Cohen, A. A., & Roucou, X. (2018) · Genome Research · doi:10.1101/gr.230938.117 · Cited by 75
“So far, the response to this dilemma has been to use more stringent criteria for linking SNPs to pathologies, and synonymous mutations are often discarded and regarded as silent mutations under a uni-coding dogma (Nielsen et al. 2011, 2012; Olson et al. 2015).”
Gene regulatory effects of a large chromosomal inversion in highland maize
Crow, T. M., Ta, J., Nojoomi, S., Aguilar-Rangel, M. R., Torres‐Rodríguez, J. V., Gates, D. J., Rellán‐Álvarez, R., Sawers, R. J. H., & Runcie, D. E. (2020) · PLoS Genetics · doi:10.1371/journal.pgen.1009213 · Cited by 69
Genomic signatures of selection in bats surviving white‐nose syndrome
Gignoux‐Wolfsohn, S., Pinsky, M. L., Kerwin, K., Herzog, C., Hall, M., Bennett, A. B., Fefferman, N. H., & Maslo, B. (2021) · Molecular Ecology · doi:10.1111/mec.15813 · Cited by 74
“This depth of coverage allowed us to identify single nucleotide polymorphisms (SNPs) and calculate population-level allele frequencies using established methods that take genotype uncertainty into account (Korneliussen et al., 2014; Nielsen et al., 2012).”
MethodDivergence in gene expression within and between two closely related flycatcher species
Uebbing, S., Künstner, A., Mäkinen, H., Backström, N., Bolívar, P., Burri, R., Dutoit, L., Mugal, C. F., Nater, A., Aken, B. L., et al. (2016) · Molecular Ecology · doi:10.1111/mec.13596 · Cited by 70
“FST between collared flycatcher and pied flycatcher in 2-kb genomic regions upstream of the translation start site of each gene was estimated based on genotype likelihoods using ANGSD (Nielsen et al. 2012) and NGSTOOLS (Fumagalli et al. 2014).”
MethodVeeramah, K. R., Gutenkunst, R. N., Woerner, A. E., Watkins, J. C., & Hammer, M. F. (2014) · Molecular Biology and Evolution · doi:10.1093/molbev/msu166 · Cited by 64
“High coverage wholegenome sequencing of many individuals from single populations is likely to make this feasible very soon, although an alternative would be to utilize methods that can accurately infer AFS from low coverage data (Nielsen et al. 2012).”
BackgroundRippe, J. P., Dixon, G., Fuller, Z. L., Liao, Y., & Matz, M. V. (2021) · Molecular Ecology · doi:10.1111/mec.15931 · Cited by 67
“All genotyping and identification of single nucleotide polymorphisms was performed using the ANGSD program suite (Kim et al., 2011; Nielsen et al., 2012; Korneliussen et al., 2014), which is well suited for low-coverage genetic data as it operates on genotype likelihoods, rather than hard genotype calls, in most downs…”
MethodFountain, E. D., Pauli, J. N., Reid, B. N., Palsbøll, P. J., & Peery, M. Z. (2016) · Molecular Ecology Resources · doi:10.1111/1755-0998.12519 · Cited by 66
“…have investigated methods for incorporating sequencing error rates in data subject to low coverage (Bansal 2010; Malhis & Jones 2010; Le & Durbin 2011; Nielsen et al. 2012; Mastretta-Yanes et al. 2015), but the effects of sequencing error and coverage on genotyping error rates are uncertain.”
MethodComputing Platforms for Big Biological Data Analytics: Perspectives and Challenges
Yin, Z., Lan, H., Tan, G., Lu, M., Vasilakos, A. V., & Liu, W. (2017) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2017.07.004 · Cited by 72
“Other applications such as SNP detection [17] and GWAS [18] may also take days or even months to finish processing one dataset.”
BackgroundMethodLou, R. N., & Therkildsen, N. O. (2021) · Molecular Ecology Resources · doi:10.1111/1755-0998.13559 · Cited by 72
Accounting for uncertainty in DNA sequencing data
O'Rawe, J., Ferson, S. A., & Lyon, G. J. (2015) · Trends in Genetics · doi:10.1016/j.tig.2014.12.002 · Cited by 63
Uncovering the genomic basis of an extraordinary plant invasion
Bieker, V. C., Battlay, P., Petersen, B., Sun, X., Wilson, J., Brealey, J. C., Bretagnolle, F., Nurkowski, K. A., Lee, C., Sánchez-Barreiro, F., et al. (2022) · Science Advances · doi:10.1126/sciadv.abo5115 · Cited by 64
“The SFS was polarized using the ancestral state (see ancestral state estimation section). realSFS from angsd ( 103 , 113 ) was used to generate the two-dimensional SFS between population pairs and generate F ST in sliding windows.”
Martin, M. D., Vieira, F. G., Ho, S. Y. W., Wales, N., Schubert, M., Seguin‐Orlando, A., Ristaino, J. B., & Gilbert, M. T. P. (2015) · Molecular Biology and Evolution · doi:10.1093/molbev/msv241 · Cited by 60
“588 (Nielsen et al. 2012; Korneliussen et al. 2013) was used to estimate genotype likelihoods for each sample at sites likely to contain SNP variants (command-line options - GL 1 -doGlf 2 -SNP_pval 1e-6), resulting in 1,371,306 SNP sites where genotypes passed the confidence filter in at least 14…”
MethodOut of Southern East Asia of the Brown Rat Revealed by Large-Scale Genome Sequencing
Zeng, L., Chen, M., Li, Y., Su, L., Su, Y., Otecko, N. O., Dalecky, A., Donnellan, S. C., Aplin, K. P., Liu, X., et al. (2017) · Molecular Biology and Evolution · doi:10.1093/molbev/msx276 · Cited by 64
“…to point out that one caveat of our analyses is attributable to the relatively low coverage of genome sequencing, which would affect the SFS that the demographic inferences were based on (Nielsen et al. 2011, 2012; Han et al. 2015), although we have used high-quality genotypes for analyses.”
MethodSelf-citationShafer, A. B. A., Gattepaille, L. M., Stewart, R. E., & Wolf, J. B. W. (2014) · Molecular Ecology · doi:10.1111/mec.13034 · Cited by 60
“2011), or Bayesian and likelihood approaches that take into account genotype uncertainty in the population-level estimates (Buerkle & Gompert 2011; Nielsen et al. 2012).”
BackgroundDeagle, B. E., Faux, C. E., Kawaguchi, S., Meyer, B., & Jarman, S. (2015) · Molecular Ecology · doi:10.1111/mec.13370 · Cited by 58
“Similarly, much of the work involving development of algorithms for data analysis also makes use of model systems to evaluate the methodology (e.g. Nielsen et al. 2012; Arnold et al. 2013).”
MethodSchweizer, R. M., Robinson, J. A., Harrigan, R. J., Silva, P., Galverni, M., Musiani, M., Green, R. E., Novembre, J., & Wayne, R. K. (2015) · Molecular Ecology · doi:10.1111/mec.13467 · Cited by 58
“Using ANGSD (Nielsen et al. 2012), we also generated unfolded SFS to verify patterns of allele frequency variation of the top 5% of genes from SWEED relative to neutral and genic regions (Supporting information).”
MethodThe evolution of white-tailed jackrabbit camouflage in response to past and future seasonal climates
Ferreira, M. S., Thurman, T. J., Jones, M. R., Farelo, L., Kumar, A. V., Mortimer, S. M. E., Demboski, J. R., Mills, L. S., Alves, P. C., Melo‐Ferreira, J., et al. (2023) · Science · doi:10.1126/science.ade3984 · Cited by 57
Genomic Evidence of Local Adaptation to Climate and Diet in Indigenous Siberians
Hallmark, B., Karafet, T. M., Hsieh, P., Osipova, L. P., Watkins, J. C., & Hammer, M. F. (2018) · Molecular Biology and Evolution · doi:10.1093/molbev/msy211 · Cited by 58
Thermal vasodilation as a treatment of congestive heart failure: a novel approach.
Tei, C., & Tanaka, N. (1996) · PubMed · Cited by 54
Selection on ancestral genetic variation fuels repeated ecotype formation in bottlenose dolphins
Louis, M., Galimberti, M., Archer, F. I., Berrow, S., Brownlow, A. C., Fallon, R., Nykänen, M., O’Brien, J. M., Robertson, K. M., Rosel, P. E., et al. (2021) · Science Advances · doi:10.1126/sciadv.abg1245 · Cited by 63
Nevado, B., Ramos-Onsins, S. E., & Miguel Pérez-enciso, A. (2014) · Molecular Ecology · doi:10.1111/mec.12693 · Cited by 59
“The third method used in this study does not perform genotype calls, but rather bases inferences on genotype likelihoods, thus directly dealing with missing data and the sequencing and mapping errors inherent in NGS data (Nielsen et al. 2012).”
MethodElleouet, J. S., & Aitken, S. N. (2018) · Molecular Ecology Resources · doi:10.1111/1755-0998.12758 · Cited by 50
Population dynamics and genetic connectivity in recent chimpanzee history
Fontsere, C., Kuhlwilm, M., Morcillo-Suárez, C., Álvarez-Estapé, M., Lester, J. D., Gratton, P., Schmidt, J. M., Dieguez, P., Aebischer, T., Álvarez-Varona, P., et al. (2022) · Cell Genomics · doi:10.1016/j.xgen.2022.100133 · Cited by 47
fastNGSadmix: admixture proportions and principal component analysis of a single NGS sample
Jørsboe, E., Hanghøj, K., & Albrechtsen, A. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx474 · Cited by 48
Self-citationFounder effects shape linkage disequilibrium and genomic diversity of a partially clonal invader
Flanagan, B. A., Krueger‐Hadfield, S. A., Murren, C. J., Nice, C. C., Strand, A. E., & Sotka, E. E. (2021) · Molecular Ecology · doi:10.1111/mec.15854 · Cited by 48
“With few exceptions, we used genotype likelihoods in order to incorporate the uncertainty that arises from errors in sequencing and sampling (Nielsen et al., 2012).”
MethodRašić, G., Schama, R., Powell, R., Maciel‐de‐Freitas, R., Endersby‐Harshman, N. M., Filipović, I., Sylvestre, G., Maspero, R., & Hoffmann, A. A. (2015) · Evolutionary Applications · doi:10.1111/eva.12301 · Cited by 47
“We then simulated genotype likelihoods with an 89 read depth (as in the empirical dataset, see Results) and an error rate of 0.5%, from which we then calculated the folded SFS as in Nielsen et al. (2012).”
BackgroundMethodInfluentialInferring Heterozygosity from Ancient and Low Coverage Genomes
Kousathanas, A., Leuenberger, C., Link, V., Sell, C., Bürger, J., & Wegmann, D. (2016) · Genetics · doi:10.1534/genetics.116.189985 · Cited by 50
Landscape drivers of genomic diversity and divergence in woodland Eucalyptus
Murray, K., Janes, J. K., Jones, A., Bothwell, H. M., Andrew, R. L., & Borevitz, J. (2019) · Molecular Ecology · doi:10.1111/mec.15287 · Cited by 48
“sideroxylon was calculated with realSFS (Nielsen et al., 2012), then estimated genome-wide FST between E.”
MethodGenomic signatures of inbreeding and mutation load in a threatened rattlesnake
Ochoa, A., & Gibbs, H. L. (2021) · Molecular Ecology · doi:10.1111/mec.16147 · Cited by 49
Evaluating the effect of reference genome divergence on the analysis of empirical RADseq datasets
Bohling, J. H. (2020) · Ecology and Evolution · doi:10.1002/ece3.6483 · Cited by 46
Genomic selection in salmonids: new discoveries and future perspectives
D’Agaro, E., Favaro, A., Matiussi, S., Gibertoni, P. P., & Esposito, S. (2021) · Aquaculture International · doi:10.1007/s10499-021-00747-w · Cited by 46
The practice and promise of temporal genomics for measuring evolutionary responses to global change
Clark, R. D., Catalano, K. A., Fitz, K. S., Garcia, E., Jaynes, K. E., Reid, B. N., Sawkins, A. S., Snead, A. A., Whalen, J. C., & Pinsky, M. L. (2023) · Molecular Ecology Resources · doi:10.1111/1755-0998.13789 · Cited by 45
“Given that low-frequency alleles are often the first to be lost during genetic bottlenecks, programs that account for such issues should be used when possible (e.g., upstream base quality recalibration: Ni & Stoneking, 2016; downstream SFS estimation: Nielsen et al., 2012).”
Fu, Y. (2014) · G3 Genes Genomes Genetics · doi:10.1534/g3.114.010942 · Cited by 45
“…protocol with de novo sequencing to assemble a reference for generating reference-based GBS data for which map-dependent imputation can be applied; or (4) develop more accurate population genetic inferences from highly incomplete GBS data (Lynch 2008; Nielsen et al. 2012; Fumagalli et al. 2013).”
MethodWang, X., Bernhardsson, C., & Ingvarsson, P. K. (2020) · Genome Biology and Evolution · doi:10.1093/gbe/evaa005 · Cited by 43
Estimating IBD tracts from low coverage NGS data
Vieira, F. G., Albrechtsen, A., & Nielsen, R. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw212 · Cited by 44
“Many recent methods rely on probabilistic frameworks to account for these errors and accurately call SNPs and genotypes, even at low coverage (Martin et al., 2010; Li, 2011; Nielsen et al., 2012).”
MethodSelf-citationMeisner, J., & Albrechtsen, A. (2019) · Molecular Ecology Resources · doi:10.1111/1755-0998.13019 · Cited by 44
Self-citationQi, X., An, H., Hall, T. E., Di, C., Blischak, P. D., McKibben, M. T. W., Hao, Y., Conant, G. C., Pires, J. C., & Barker, M. S. (2021) · New Phytologist · doi:10.1111/nph.17194 · Cited by 43
The Muskox Lost a Substantial Part of Its Genetic Diversity on Its Long Road to Greenland
Hansen, C. C. R., Hvilsom, C., Schmidt, N. M., Aastrup, P., Van Coeverden de Groot, P. J., Siegismund, H. R., & Heller, R. (2018) · Current Biology · doi:10.1016/j.cub.2018.10.054 · Cited by 42
Verdu, C., Guichoux, E., Quevauvillers, S., Thier, O. D., Laizet, Y., Delcamp, A., Gévaudant, F., Monty, A., Porté, A. J., Lejeune, P., et al. (2016) · Ecology and Evolution · doi:10.1002/ece3.2466 · Cited by 41
Poelstra, J. W., Salmona, J., Tiley, G. P., Schüßler, D., Blanco, M. B., Andriambeloson, J., Bouchez, O., Campbell, C. R., Etter, P. D., Hohenlohe, P. A., et al. (2020) · Systematic Biology · doi:10.1093/sysbio/syaa053 · Cited by 63
Genome-Wide Analysis of Colonization History and Concomitant Selection in Arabidopsis lyrata
Mattila, T. M., Tyrmi, J. S., Pyhäjärvi, T., & Savolainen, O. (2017) · Molecular Biology and Evolution · doi:10.1093/molbev/msx193 · Cited by 36
“The statistic hWat, p and Tajima’s D were calculated within population and Fst between each population pair in nonoverlapping widows using the genotype call free method implemented in ANGSD version 0.913 (Nielsen et al. 2012; Fumagalli et al. 2013; Korneliussen et al. 2014).”
MethodInfluentialPhenotypic sexual dimorphism is associated with genomic signatures of resolved sexual conflict
Wright, A. E., Rogers, T. F., Fumagalli, M., Cooney, C. R., & Mank, J. E. (2019) · Molecular Ecology · doi:10.1111/mec.15115 · Cited by 39
Genotype-Frequency Estimation from High-Throughput Sequencing Data
Maruki, T., & Lynch, M. (2015) · Genetics · doi:10.1534/genetics.115.179077 · Cited by 41
“The corresponding SFS by the proposed method was more similar to Nielsen et al. ’ s (2012) SFS with the GATK model than to that with the Samtools model.”
BackgroundMethodInfluentialEvidence for widespread selection in shaping the genomic landscape during speciation of Populus
Wang, J., Street, N. R., Park, E., Liu, J., & Ingvarsson, P. K. (2020) · Molecular Ecology · doi:10.1111/mec.15388 · Cited by 37
Self-citationQian, Y., Meng, M., Zhou, C., Liu, H., Jiang, H., Xu, Y., Chen, W., Ding, Z., Liu, Y., Gong, X., et al. (2023) · Molecular Biology and Evolution · doi:10.1093/molbev/msad129 · Cited by 41
Integrative taxonomy clarifies the evolution of a cryptic primate clade
van Elst, T., Sgarlata, G. M., Schüßler, D., Tiley, G. P., Poelstra, J. W., Scheumann, M., Blanco, M. B., Aleixo-Pais, I. G., Rina Evasoa, M., Ganzhorn, J. U., et al. (2024) · Nature Ecology & Evolution · doi:10.1038/s41559-024-02547-w · Cited by 37
Schilling, M. P., Wolf, P. G., Duffy, A. M., Rai, H. S., Rowe, C. A., Richardson, B. A., & Mock, K. E. (2014) · PLoS ONE · doi:10.1371/journal.pone.0095292 · Cited by 37
“However, the empirical effects of various library preparation and filtering techniques associated with GBS have only been explored in a very limited number of systems [7,14–18].”
BackgroundThe genetic legacy of 50 years of desert bighorn sheep translocations
Jahner, J. P., Matocq, M. D., Malaney, J. L., Cox, M., Wolff, P. L., Gritts, M. A., & Parchman, T. L. (2018) · Evolutionary Applications · doi:10.1111/eva.12708 · Cited by 35
Rasmussen, M. S., Garcia‐Erill, G., Korneliussen, T. S., Wiuf, C., & Albrechtsen, A. (2022) · Genetics · doi:10.1093/genetics/iyac148 · Cited by 35
Self-citationApplying SNP-Derived Molecular Coancestry Estimates to Captive Breeding Programs
Ivy, J. A., Putnam, A. S., Navarro, A. Y., Gurr, J., & Ryder, O. A. (2016) · Journal of Heredity · doi:10.1093/jhered/esw029 · Cited by 36
“A second dataset was created that included only SNPs for which the minor allele was found in 2 or more individuals, thereby reducing the effects of genotyping error on analyses (Nielsen et al. 2012).”
BackgroundGazda, M. A., Andrade, P., Afonso, S., Dilytė, J., Archer, J. P., Lopes, R. J., Faria, R., & Carneiro, M. (2018) · Molecular Biology and Evolution · doi:10.1093/molbev/msy030 · Cited by 35
“To take into account uncertainties in genotype calls caused by the moderate levels of sequencing depth (average¼ 12.4 ), we computed genotype posterior probabilities using ANGSD instead of relying on individual genotype calls (Kim et al. 2011; Li 2011; Korneliussen et al. 2014).”
MethodInfluentialStaton, M. E., Addo‐Quaye, C., Cannon, N., Sun, Y., Zhebentyayeva, T. N., Huff, M. L., Fan, S., Bellis, E., Islam‐Faridi, N., Yu, J., et al. (2020) · Tree Genetics & Genomes · doi:10.1007/s11295-020-01454-y · Cited by 35
“…0.920 was used to calculate the allele frequency spectrum, obtain a maximum likelihood estimate of the unfolded site frequency spectrum (SFS) (Nielsen et al. 2012), estimate pairwise nucleotide diversity, and perform tests for selection based on Tajima’s D coefficient (Tajima 1989), which…”
MethodInfluentialPervasive hybridization with local wild relatives in Western European grapevine varieties
Freitas, S., Gazda, M. A., Rebelo, M. Â., Muñoz‐Pajares, A. J., Vila-Viçosa, C. M., Muñoz‐Mérida, A., Gonçalves, L. M. C., Azevedo-Silva, D., Afonso, S., Castro, I., et al. (2021) · Science Advances · doi:10.1126/sciadv.abi8584 · Cited by 35
Climate-induced range shifts drive adaptive response via spatio-temporal sieving of alleles
Luqman, H., Wegmann, D., Fior, S., & Widmer, A. (2023) · Nature Communications · doi:10.1038/s41467-023-36631-9 · Cited by 40
Lim, H. C., & Braun, M. J. (2016) · Molecular Ecology Resources · doi:10.1111/1755-0998.12568 · Cited by 32
Wang, Z., Wang, J., Peng, J., Du, X., Jiang, M., Li, Y., Han, F., Du, G., Yang, H., Lian, S., et al. (2019) · Molecular Breeding · doi:10.1007/s11032-019-0930-6 · Cited by 32
Self-citationBohling, J. H., Small, M. P., Bargen, J. V., Louden, A., & DeHaan, P. W. (2019) · Conservation Genetics · doi:10.1007/s10592-018-1134-z · Cited by 30
Garcia‐Erill, G., Jørgensen, C. H. F., Muwanika, V. B., Wang, X., Rasmussen, M. S., de Jong, Y. A., Gaubert, P., Olayemi, A., Salmona, J., Butynski, T. M., et al. (2022) · Molecular Biology and Evolution · doi:10.1093/molbev/msac134 · Cited by 33
“For each pairwise population, we then used realSFS (Nielsen et al. 2012) to estimate population pair-wise 2dSFS from saf fi les based on randomly sampled blocks of contiguous non fi ltered sites until reaching 200 Mbp.”
MethodSelf-citationMeisner, J., Albrechtsen, A., & Hanghøj, K. (2021) · BMC Bioinformatics · doi:10.1186/s12859-021-04375-2 · Cited by 30
Self-citationGiraffe lineages are shaped by major ancient admixture events
Bertola, L. D., Quinn, L. J. E., Hanghøj, K., Garcia‐Erill, G., Rasmussen, M. S., Balboa, R. F., Meisner, J., Bøggild, T., Wang, X., Lin, L., et al. (2024) · Current Biology · doi:10.1016/j.cub.2024.02.051 · Cited by 32
“77 From the SFS, we calculated the kinship co-efficient using the KING estimator.”
Self-citation1206 genomes reveal origin and movement of Aedes aegypti driving increased dengue risk
Crawford, J. E., Balcazar, D., Redmond, S. N., Rose, N. H., Youd, H. A., Lucas, E. R., Ali, R. S. M., Al-Nazawi, A. M., Badolo, A., Chen, C., et al. (2025) · Science · doi:10.1126/science.ads3732 · Cited by 37
Strong and lasting impacts of past global warming on baleen whales and their prey
Cabrera, A. A., Schall, E., Bérubé, M., Anderwald, P., Bachmann, L., Berrow, S., Best, P. B., Clapham, P. J., Cunha, H. A., Rosa, L. D., et al. (2022) · Global Change Biology · doi:10.1111/gcb.16085 · Cited by 38
Zerebecki, R. A., Sotka, E. E., Hanley, T. C., Bell, K. L., Gehring, C. A., Nice, C. C., Richards, C. L., & Hughes, A. R. (2021) · The American Naturalist · doi:10.1086/716512 · Cited by 30
“With noted exceptions, all analyses were based on genotype likelihoods to incorporate the uncertainty that arises from errors in sequencing and sampling (Nielsen et al. 2012).”
MethodDoes urbanisation lead to parallel demographic shifts across the world in a cosmopolitan plant?
Caizergues, A. E., Santangelo, J. S., Ness, R. W., Angeoletto, F. H. S., Anstett, D. N., Anstett, J., Baena‐Díaz, F., Carlen, E. J., Chaves, J. A., Comerford, M. S., et al. (2024) · Molecular Ecology · doi:10.1111/mec.17311 · Cited by 29
“Since calling individual genotypes from low coverage data can lead to bias in variant detection (Han et al., 2014; Nielsen et al., 2012), we computed genotype likelihoods with ANGSD v0.”
MethodOutlier SNPs enable food traceability of the southern rock lobster, Jasus edwardsii
Villacorta‐Rath, C., Ilyushkina, I., Strugnell, J. M., Green, B. S., Murphy, N. P., Doyle, S. R., Hall, N. E., Robinson, A. J., & Bell, J. J. (2016) · Marine Biology · doi:10.1007/s00227-016-3000-1 · Cited by 28
European derived Saccharomyces cerevisiae colonisation of New Zealand vineyards aided by humans
Gayevskiy, V., Lee, S., & Goddard, M. R. (2016) · FEMS Yeast Research · doi:10.1093/femsyr/fow091 · Cited by 27
“The number of sites and the number of segregating sites for each population were determined from the mean allele frequency calculations in ANGSD with the minInd parameter set to the number of strains per population and the minMaf alternatively set to 0 and 0.01.”
BackgroundMethodInfluentialde Jager, D., Glanzmann, B., Möller, M., Hoal, E. G., van Helden, P. D., Harper, C. K., & Bloomer, P. (2021) · Scientific Reports · doi:10.1038/s41598-021-83823-8 · Cited by 31
da Fonseca, R. R., Ureña, I., Afonso, S., Pires, A. E., Jørsboe, E., Chikhi, L., & Ginja, C. (2019) · BMC Genomics · doi:10.1186/s12864-019-5685-2 · Cited by 26
A versatile Rapture (RAD‐Capture) platform for genotyping marine turtles
Komoroske, L. M., Miller, M. R., O’Rourke, S., Stewart, K. R., Jensen, M. P., & Dutton, P. H. (2018) · Molecular Ecology Resources · doi:10.1111/1755-0998.12980 · Cited by 26
Crawford, J. E., Riehle, M. M., Markianos, K., Bischoff, E., Guelbeogo, M. W., Gnémé, A., Sagnon, N., Vernick, K. D., Nielsen, R., & Lazzaro, B. P. (2016) · Molecular Ecology · doi:10.1111/mec.13572 · Cited by 24
“We estimated the global SFS from genotype probabilities using –realSFS 2 in ANGSD, which is identical to –realSFS 1 (Nielsen et al. 2012) except that it uses inbreeding coefficients as priors for calculations of posterior probabilities (Vieira et al. 2013).”
MethodSelf-citationCox, K. H., Oliveira, L. M. B., Plummer, L., Corbin, B. A., Gardella, T. J., Balasubramanian, R., & Crowley, W. F. (2017) · Human Molecular Genetics · doi:10.1093/hmg/ddx404 · Cited by 26
Fast diffusion of domesticated maize to temperate zones
Li, X., Jian, Y., Xie, C., Wu, J., Xu, Y., & Zou, C. (2017) · Scientific Reports · doi:10.1038/s41598-017-02125-0 · Cited by 25
Balogh, A., Ngo, L., Zigler, K. S., & Dixon, G. (2020) · Scientific Reports · doi:10.1038/s41598-020-74508-9 · Cited by 24
Speciation of pelagic zooplankton: Invisible boundaries can drive isolation of oceanic ctenophores
Johnson, S. B., Winnikoff, J. R., Schultz, D. T., Christianson, L. M., Patry, W. L., Mills, C. E., & Haddock, S. H. D. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.970314 · Cited by 24
Population assignment from genotype likelihoods for low‐coverage whole‐genome sequencing data
DeSaix, M. G., Rodriguez, M. D., Ruegg, K., & Anderson, E. C. (2024) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.14286 · Cited by 23
“The creation of probabilistic frameworks for allele frequency estimation, genotype calling and single nucleotide polymorphism (SNP) calling have made low-coverage WGS practical for many applications (Kim et al., 2011; Nielsen et al., 2011, 2012).”
Berthouly‐Salazar, C., Mariac, C., Couderc, M., Pouzadoux, J., Floc’h, J.-B., & Vigouroux, Y. (2016) · Frontiers in Plant Science · doi:10.3389/fpls.2016.00777 · Cited by 24
“Nielsen et al. (2011) pointed out that, until now, no satisfactory genotype calling algorithm is available that would lead to an unbiased SFS.”
BackgroundHao, Y., Dietrich, C. H., & Dai, W. (2016) · Scientific Reports · doi:10.1038/srep38151 · Cited by 24
Genomics clarifies taxonomic boundaries in a difficult species complex
Baumsteiger, J., Moyle, P. B., Aguilar, A., O’Rourke, S. M., & Miller, M. R. (2017) · PLoS ONE · doi:10.1371/journal.pone.0189417 · Cited by 23
“Genome-wide FST between population pairs (based on each hierarchical subsampling) was estimated by first estimating a site frequency spectrum (SFS) for each population (doSaf; [77]) using paired-end BAM files.”
Battlay, P., Craig, S., Putra, A. R., Monro, K., Silva, N. P. D., Wilson, J., Bieker, V. C., Kabir, S., Shamaya, N., van Boheemen, L. A., et al. (2025) · Molecular Biology and Evolution · doi:10.1093/molbev/msae270 · Cited by 25
Cost-effective assembly of the African wild dog (Lycaon pictus) genome using linked reads
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. (2018) · GigaScience · doi:10.1093/gigascience/giy124 · Cited by 27
“(indel) regions and duplicate marking was performed using GATK (GATK , RRID:SCR_001876), and finally, we called heterozygous sites using a probabilistic framework implemented in ANGSD [54, 62, 63].”
InfluentialCaballero-Villalobos, L., Silva‐Arias, G. A., Turchetto, C., Giudicelli, G. C., Petzold, E., Bombarely, A., & Freitas, L. B. (2020) · Botanical Journal of the Linnean Society · doi:10.1093/botlinnean/boaa091 · Cited by 21
“Folded site frequency spectrum (SFS).”
MethodInfluentialNøhr, A. K., Hanghøj, K., Garcia‐Erill, G., Li, Z., Moltke, I., & Albrechtsen, A. (2021) · G3 Genes Genomes Genetics · doi:10.1093/g3journal/jkab174 · Cited by 24
“However, next-generation sequencing (NGS) data are becoming more common, and often these data are sequenced at low to medium depth, where genotype calling can come with significant biases (Nielsen et al. 2012).”
BackgroundSelf-citationSandercock, A. M., Westbrook, J. W., Zhang, Q., Johnson, H. A., Saielli, T. M., Scrivani, J. A., Fitzsimmons, S. F., Collins, K., Perkins, M. T., Craddock, J. H., et al. (2022) · Molecular Ecology · doi:10.1111/mec.16629 · Cited by 22
“We used angsd (Analysis of Next Generation Sequencing Data) to estimate these parameters, as its use of genotype likelihoods provides less- biased estimates than those based only on variant calls (Korneliussen et al., 2014; Nielsen et al., 2012).”
MethodFraïssé, C., Roux, C., Gagnaire, P., Romiguier, J., Faivre, N., Welch, J. J., & Bierne, N. (2018) · PeerJ · doi:10.7717/peerj.5198 · Cited by 26
da Fonseca, R. R., Campos, P. F., Rey‐Iglesia, A., Barroso, G. V., Bergeron, L. A., Nande, M., Tuya, F., Abidli, S., Pérez, M., Riveiro, I., et al. (2024) · Genes · doi:10.3390/genes15020170 · Cited by 23
“We used methods based on the site frequency spectrum (SFS) [47,48] to obtain the genome-wide fixation index (F ST ) values in ANGSD [41].”
MethodAssessing the Relationship of Ancient and Modern Populations
Schraiber, J. G. (2017) · Genetics · doi:10.1534/genetics.117.300448 · Cited by 22
angsd ‐wrapper: utilities for analysing next‐generation sequencing data
Durvasula, A., Hoffman, P., Kent, T. V., Liu, C., Kono, T. J. Y., Morrell, P. L., & Ross‐Ibarra, J. (2016) · Molecular Ecology Resources · doi:10.1111/1755-0998.12578 · Cited by 21
Inferring Demographic History Using Genomic Data
Salmona, J., Heller, R., Lascoux, M., & Shafer, A. B. A. (2017) · Population genomics · doi:10.1007/13836_2017_1 · Cited by 24
A reference‐free approach to analyse RADseq data using standard next generation sequencing toolkits
Heller, R., Nursyifa, C., Garcia‐Erill, G., Salmona, J., Chikhi, L., Meisner, J., Korneliussen, T. S., & Albrechtsen, A. (2021) · Molecular Ecology Resources · doi:10.1111/1755-0998.13324 · Cited by 23
“The latter is a serious shortcoming, as genotype calling (GC) may lead to data biases when depth is low or uneven among samples (Han et al., 2013; Nielsen et al., 2011, 2012; Rochette & Catchen, 2017; Skotte et al., 2013).”
BackgroundMethodResultInfluentialSelf-citationPopulation genomics of the muskox' resilience in the near absence of genetic variation
Pečnerová, P., Lord, E., Garcia‐Erill, G., Hanghøj, K., Rasmussen, M. S., Meisner, J., Liu, X., van der Valk, T., Santander, C. G., Quinn, L., et al. (2024) · Molecular Ecology · doi:10.1111/mec.17205 · Cited by 19
“931 (Nielsen et al., 2012) im - plemented in ANGSD (Korneliussen et al., 2014 ).”
BackgroundMethodSelf-citationPleistocene climate fluctuations drove demographic history of African golden wolves (Canis lupaster)
Sarabia, C., vonHoldt, B. M., Larrasoaña, J. C., Uríos, V., & Leonard, J. A. (2020) · Molecular Ecology · doi:10.1111/mec.15784 · Cited by 20
Genomic characterization of animal genetic resources
Boitard, S., Chikhi, L., da Fonseca, R. R., Ginja, C., Kantanen, J., Lenstra, J. A., Orozco‐terWengel, P., & Pausch, H. (2023) · FAO eBooks · doi:10.4060/cc3079en · Cited by 29
Lozier, J. D., Strange, J. P., & Heraghty, S. D. (2023) · Ecology and Evolution · doi:10.1002/ece3.9778 · Cited by 23
“We used the SFS for all samples in each population group for diversity calculations, but for plotting single population SFS, we also performed calculations for nine randomly selected individuals per region so that the SFS would have the same bin sizes.”
MethodInfluentialDeSaix, M. G., Anderson, E. C., Bossu, C. M., Rayne, C., Schweizer, T. M., Bayly, N. J., Narang, D. S., Hagelin, J. C., Gibbs, H. L., Saracco, J. F., et al. (2023) · Molecular Ecology · doi:10.1111/mec.17137 · Cited by 18
“One of these challenges is dealing with low sequencing read depths per individual, which necessitates the use of probabilistic frameworks for genotype calling to account for the uncertainty inherent in the data (Nielsen et al., 2011, 2012).”
BackgroundKeighley, M. V., Heinsohn, R., Langmore, N. E., Murphy, S., & Peñalba, J. V. (2018) · Emu - Austral Ornithology · doi:10.1080/01584197.2018.1483731 · Cited by 20
“Genotype likelihood calculations (suited to low-coverage data) (Nielsen et al. 2011, 2012) and SNP filtering based on coverage, overlap between populations or putative repeats and paralogous regions were conducted with ANGSD (Korneliussen et al. 2014).”
MethodUnexpected population fragmentation in an endangered seabird: the case of the Peruvian diving-petrel
Cristofari, R., Plaza, P., Fernández, C. E., Trucchi, E., Gouin, N., Bohec, C. L., Zavalaga, C. B., Alfaro‐Shigueto, J., & Luna‐Jorquera, G. (2019) · Scientific Reports · doi:10.1038/s41598-019-38682-9 · Cited by 21
Rosenblum, E. B., Parent, C. E., Diepeveen, E. T., Noss, C. F., & Bi, K. (2017) · The American Naturalist · doi:10.1086/692138 · Cited by 18
Cross‐platform compatibility of de novo‐aligned SNP s in a nonmodel butterfly genus
Campbell, E. O., Davis, C. S., Dupuis, J. R., Muirhead, K., & Sperling, F. A. H. (2017) · Molecular Ecology Resources · doi:10.1111/1755-0998.12695 · Cited by 19
Metadata
- 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
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2012-07-24
- Volume
- 7
- Issue
- 7
- Pages
- e37558
- ISSN
- 1932-6203 (ISSN-L)
- 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
- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
