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Publications

  1. Ochoa, A. and J. D. Storey (2021). “Estimating FST and kinship for arbitrary population structures”. PLoS Genetics 17.1. First published online 2020-11-02, p. e1009241. https://doi.org/10.1371/journal.pgen.1009241.
  2. Graim, K. and et al. (2021). “Modeling molecular development of breast cancer in canine mammary tumors”. Genome Research 31. First published online 2020-12-23, pp. 337-347. https://doi.org/10.1101/gr.256388.119.
  3. Bass, A. J. and J. D. Storey (2021). “The optimal discovery procedure for significance analysis of general gene expression studies”. Bioinformatics 37.3. First published online 2020-08-20, pp. 367-374. https://doi.org/10.1093/bioinformatics/btaa707.
  4. Chen, X., D. G. Robinson, and J. D. Storey (2021). “The functional false discovery rate with applications to genomics”. Biostatistics 22.1. First published online 2019-05-28, pp. 68-81. https://dx.doi.org/10.1093/biostatistics/kxz010.
  5. Bass, A. J., D. G. Robinson, and J. D. Storey (2019). “Determining sufficient sequencing depth in RNA-Seq differential expression studies”. bioRxiv doi:10.1101/635623. https://dx.doi.org/10.1101/635623.
  6. Bass, A. J. and J. D. Storey (2019). “The optimal discovery procedure for significance analysis of general gene expression studies”. bioRxiv doi:10.1101/571992. https://dx.doi.org/10.1101/571992.
  7. Ochoa, A. and J. D. Storey (2019). “New kinship and FST estimates reveal higher levels of differentiation in the global human population”. bioRxiv doi:10.1101/653279. https://dx.doi.org/10.1101/653279.
  8. Ochoa, A. and J. D. Storey (2019). “ FST and kinship for arbitrary population structures II: Method-of-moments estimators”. bioRxiv doi:10.1101/083923. https://dx.doi.org/10.1101/083923.
  9. Ochoa, A. and J. D. Storey (2019). “ FST and kinship for arbitrary population structures I: Generalized definitions”. bioRxiv doi:10.1101/083915. https://dx.doi.org/10.1101/083915.
  10. Cabreros, I. and J. D. Storey (2019). “A likelihood-free estimator of population structure bridging admixture models and principal components analysis”. Genetics 212.4, pp. 1009-1029. https://dx.doi.org/10.1534/genetics.119.302159.
  11. Hao, W. and J. D. Storey (2019). “Extending tests of Hardy-Weinberg equilibrium to structured populations”. Genetics 213.3, pp. 759-770. https://dx.doi.org/10.1534/genetics.119.302370.
  12. Cabreros, I. and J. D. Storey (2019). “Causal models on probability spaces”. arXiv 1907.01672. https://arxiv.org/abs/1907.01672.
  13. Cabreros, I. and J. D. Storey (2019). “A likelihood-free estimator of population structure bridging admixture models and principal components analysis”. bioRxiv doi:10.1101/240812. https://dx.doi.org/10.1101/240812.
  14. Painter, H. J., N. C. Chung, A. Sebastian, I. Albert, J. D. Storey, and M. Llinás (2018). “Genome-wide real-time in vivo transcriptional dynamics during Plasmodium falciparum blood-stage development”. Nature Communications 9.1, p. 2656. http://dx.doi.org/10.1038/s41467-018-04966-3.
  15. Painter, H. J., N. C. Chung, A. Sebastian, I. Albert, J. D. Storey, and M. Llinás (2018). “Genome-wide real-time in vivo transcriptional dynamics during Plasmodium falciparum blood-stage development”. bioRiv doi:10.1101/265975. http://dx.doi.org/10.1101/265975.
  16. Hao, W. and J. D. Storey (2017). “Extending tests of Hardy-Weinberg equilibrium to structured populations”. bioRxiv doi:10.1101/240804. https://dx.doi.org/10.1101/240804.
  17. Cabreros, I. and J. D. Storey (2017). “A nonparametric estimator of population structure unifying admixture models and principal components analysis”. bioRxiv doi:10.1101/240812. https://dx.doi.org/10.1101/240812.
  18. Chen, X., D. G. Robinson, and J. D. Storey (2017). “The functional false discovery rate with applications to genomics”. bioRxiv doi:10.1101/241133. https://dx.doi.org/10.1101/241133.
  19. Hackett, S. R. and J. D. Storey (2017). “Mixed membership martial arts: Data-driven analysis of winning martial arts styles”. MIT Sloan Sports Analytics Conference. http://www.sloansportsconference.com/wp-content/uploads/2017/02/1575.pdf.
  20. Ochoa, A. and J. D. Storey (2016). “ FST and kinship for arbitrary population structures II: Method of moments estimators”. bioRxiv doi:10.1101/083923. https://dx.doi.org/10.1101/083923.
  21. Ochoa, A. and J. D. Storey (2016). “ FST and kinship for arbitrary population structures I: Generalized definitions”. bioRxiv doi:10.1101/083915. https://dx.doi.org/10.1101/083915.
  22. Gopalan, P., W. Hao, D. M. Blei, and J. D. Storey (2016). “Scaling probabilistic models of genetic variation to millions of humans”. Nature Genetics 48.12, pp. 1587-1590. https://dx.doi.org/10.1038/ng.3710.
  23. Hackett, S. R., V. R. T. Zanotelli, W. Xu, J. Goya, J. O. Park, D. H. Perlman, et al. (2016). “Systems-level analysis of mechanisms regulating yeast metabolic flux”. Science 354.6311, pp. aaf2786-aaf2786. https://dx.doi.org/10.1126/science.aaf2786.
  24. Hao, W., M. Song, and J. D. Storey (2015). “Probabilistic models of genetic variation in structured populations applied to global human studies”. Bioinformatics 32.5, pp. 713-721. https://dx.doi.org/10.1093/bioinformatics/btv641.
  25. Song, M., W. Hao, and J. D. Storey (2015). “Testing for genetic associations in arbitrarily structured populations”. Nature Genetics 47.5, pp. 550-554. https://dx.doi.org/10.1038/ng.3244.
  26. Robinson, D. G., J. Y. Wang, and J. D. Storey (2015). “A nested parallel experiment demonstrates differences in intensity-dependence between RNA-seq and microarrays”. Nucleic Acids Research, p. gkv636. https://dx.doi.org/10.1093/nar/gkv636.
  27. Ochoa, A., J. D. Storey, M. Llinás, and M. Singh (2015). “Beyond the E-Value: Stratified statistics for protein domain prediction”. PLOS Computational Biology 11.11, p. e1004509. https://dx.doi.org/10.1371/journal.pcbi.1004509.
  28. Gopalan, P., W. Hao, D. M. Blei, and J. D. Storey (2015). “Scaling probabilistic models of genetic variation to millions of humans”. bioRxiv doi:10.1101/013227. https://dx.doi.org/10.1101/013227.
  29. Chen, X. and J. D. Storey (2015). “Consistent estimation of low-dimensional latent structure in high-dimensional data”. arXiv 1510.03497. https://arxiv.org/abs/1510.03497.
  30. Song, M., W. Hao, and J. D. Storey (2015). “Testing for genetic associations in arbitrarily structured populations”. bioRxiv doi:10.1101/012682. https://dx.doi.org/10.1101/012682.
  31. Robinson, D. G. and J. D. Storey (2014). “subSeq: Determining appropriate sequencing depth through efficient read subsampling”. Bioinformatics 30.23, pp. 3424-3426. https://dx.doi.org/10.1093/bioinformatics/btu552.
  32. Chung, N. C. and J. D. Storey (2014). “Statistical significance of variables driving systematic variation in high-dimensional data”. Bioinformatics 31.4, pp. 545-554. https://dx.doi.org/10.1093/bioinformatics/btu674.
  33. Marstrand, T. T. and J. D. Storey (2014). “Identifying and mapping cell-type-specific chromatin programming of gene expression”. Proceedings of the National Academy of Sciences 111.6, pp. E645-E654. https://dx.doi.org/10.1073/pnas.1312523111.
  34. Kim, J., N. Ghasemzadeh, D. J. Eapen, N. Chung, J. D. Storey, A. A. Quyyumi, et al. (2014). “Gene expression profiles associated with acute myocardial infarction and risk of cardiovascular death”. Genome Medicine 6.5, p. 40. https://dx.doi.org/10.1186/gm560.
  35. Ochoa, A., J. D. Storey, M. Llinás, and M. Singh (2014). “Beyond the E-value: Stratified statistics for protein domain prediction”. arXiv 1409.6384. https://arxiv.org/abs/1409.6384.
  36. Robinson, D. G., J. Wang, and J. D. Storey (2014). “A nested parallel experiment demonstrates differences in intensity-dependence between RNA-seq and microarrays”. bioRxiv doi:10.1101/013342. https://dx.doi.org/10.1101/013342.
  37. Robinson, D. G., W. Chen, J. D. Storey, and D. Gresham (2013). “Design and analysis of bar-seq experiments”. G3: Genes | Genomes | Genetics 4.1, pp. 11-18. https://dx.doi.org/10.1534/g3.113.008565.
  38. Jaffe, A. E., J. D. Storey, H. Ji, and J. T. Leek (2013). “Gene set bagging for estimating the probability a statistically significant result will replicate”. BMC Bioinformatics 14.1, p. 360. https://dx.doi.org/10.1186/1471-2105-14-360.
  39. Jaffe, A. E., J. D. Storey, H. Ji, and J. T. Leek (2013). “Gene set bagging for estimating replicability of gene set analyses”. arXiv 1301.3933. https://arxiv.org/abs/1301.3933.
  40. Hao, W., M. Song, and J. D. Storey (2013). “Probabilistic models of genetic variation in structured populations applied to global human studies”. arXiv 1312.2041. https://arxiv.org/abs/1312.2041.
  41. Chung, N. C. and J. D. Storey (2013). “Statistical significance of variables driving systematic variation”. arXiv 1308.6013. https://arxiv.org/abs/1308.6013.
  42. Leek, J. T., W. E. Johnson, H. S. Parker, A. E. Jaffe, and J. D. Storey (2012). “The sva package for removing batch effects and other unwanted variation in high-throughput experiments”. Bioinformatics 28.6, pp. 882-883. https://dx.doi.org/10.1093/bioinformatics/bts034.
  43. Desai, K. H. and J. D. Storey (2012). “Cross-dimensional inference of dependent high-dimensional data”. Journal of the American Statistical Association 107.497, pp. 135-151. https://dx.doi.org/10.1080/01621459.2011.645777.
  44. Marstrand, T. T. and J. D. Storey (2011). “Identifying and mapping cell-type specific chromatin programming of gene expression”. arXiv 1210.3313. https://arxiv.org/abs/1210.3313.
  45. Xu, W., J. Seok, M. N. Mindrinos, A. C. Schweitzer, H. Jiang, J. Wilhelmy, et al. (2011). “Human transcriptome array for high-throughput clinical studies”. Proceedings of the National Academy of Sciences 108.9, pp. 3707-3712. https://dx.doi.org/10.1073/pnas.1019753108.
  46. Xiao, W., M. N. Mindrinos, J. Seok, J. Cuschieri, A. G. Cuenca, H. Gao, et al. (2011). “A genomic storm in critically injured humans”. The Journal of Experimental Medicine 208.13, pp. 2581-2590. https://dx.doi.org/10.1084/jem.20111354.
  47. Storey, J. D. (2011). “False discovery rate”. In: International Encyclopedia of Statistical Science. Ed. by M. Lovric. Springer Nature, pp. 504-508. https://dx.doi.org/10.1007/978-3-642-04898-2_248.
  48. Leek, J. T. and J. D. Storey (2011). “The joint null criterion for multiple hypothesis tests”. Statistical Applications in Genetics and Molecular Biology 10.1, pp. 2361-2373. https://dx.doi.org/10.2202/1544-6115.1673.
  49. Kanodia, J. S., Y. Kim, R. Tomer, Z. Khan, K. Chung, J. D. Storey, et al. (2011). “A computational statistics approach for estimating the spatial range of morphogen gradients”. Development 138.22, pp. 4867-4874. https://dx.doi.org/10.1242/dev.071571.
  50. Desai, K. H., C. S. Tan, J. T. Leek, R. V. Maier, R. G. Tompkins, and J. D. Storey (2011). “Dissecting inflammatory complications in critically injured patients by within-patient gene expression changes: A longitudinal clinical genomics study”. PLoS Medicine 8.9, p. e1001093. https://dx.doi.org/10.1371/journal.pmed.1001093.
  51. Woo, S., J. T. Leek, and J. D. Storey (2010). “A computationally efficient modular optimal discovery procedure”. Bioinformatics 27.4, pp. 509-515. https://dx.doi.org/10.1093/bioinformatics/btq701.
  52. Gresham, D., V. M. Boer, A. Caudy, N. Ziv, N. J. Brandt, J. D. Storey, et al. (2010). “System-level analysis of genes and functions affecting survival during nutrient starvation in Saccharomyces cerevisiae”. Genetics 187.1, pp. 299-317. https://dx.doi.org/10.1534/genetics.110.120766.
  53. Mecham, B. H., P. S. Nelson, and J. D. Storey (2010). “Supervised normalization of microarrays”. Bioinformatics 26.10, pp. 1308-1315. https://dx.doi.org/10.1093/bioinformatics/btq118.
  54. Kruglyak, L. and J. D. Storey (2009). “Cause and express”. Nature Biotechnology 27.6, pp. 544-545. https://dx.doi.org/10.1038/nbt0609-544.
  55. Kall, L., J. D. Storey, and W. S. Noble (2009). “QVALITY: Non-parametric estimation of q-values and posterior error probabilities”. Bioinformatics 25.7, pp. 964-966. https://dx.doi.org/10.1093/bioinformatics/btp021.
  56. Schadt, E. E., C. Molony, E. Chudin, K. Hao, X. Yang, P. Y. Lum, et al. (2008). “Mapping the genetic architecture of gene expression in human liver”. PLoS Biology 6.5. Ed. by G. Abecassis, p. e107. https://dx.doi.org/10.1371/journal.pbio.0060107.
  57. Leek, J. T. and J. D. Storey (2008). “A general framework for multiple testing dependence”. Proceedings of the National Academy of Sciences 105.48, pp. 18718-18723. https://dx.doi.org/10.1073/pnas.0808709105.
  58. Kall, L., J. D. Storey, and W. S. Noble (2008). “Non-parametric estimation of posterior error probabilities associated with peptides identified by tandem mass spectrometry”. Bioinformatics 24.16, pp. i42-i48. https://dx.doi.org/10.1093/bioinformatics/btn294.
  59. Käll, L., J. D. Storey, M. J. MacCoss, and W. S. Noble (2008). “Posterior error probabilities and false discovery rates: two sides of the same coin”. Journal of Proteome Research 7.1, pp. 40-44. https://dx.doi.org/10.1021/pr700739d.
  60. Käll, L., J. D. Storey, M. J. MacCoss, and W. S. Noble (2008). “Assigning significance to peptides identified by tandem mass spectrometry using decoy databases”. Journal of Proteome Research 7.1, pp. 29-34. https://dx.doi.org/10.1021/pr700600n.
  61. Idaghdour, Y., J. D. Storey, S. J. Jadallah, and G. Gibson (2008). “A genome-wide gene expression signature of environmental geography in leukocytes of Moroccan Amazighs”. PLoS Genetics 4.4. Ed. by G. Barsh, p. e1000052. https://dx.doi.org/10.1371/journal.pgen.1000052.
  62. Hao, K., E. E. Schadt, and J. D. Storey (2008). “Calibrating the performance of SNP arrays for whole-genome association studies”. PLoS Genetics 4.6. Ed. by G. R. Abecasis, p. e1000109. https://dx.doi.org/10.1371/journal.pgen.1000109.
  63. Chen, L. S. and J. D. Storey (2008). “Eigen-$R^2$ for dissecting variation in high-dimensional studies”. Bioinformatics 24.19, pp. 2260-2262. https://dx.doi.org/10.1093/bioinformatics/btn411.
  64. Biswas, S., J. D. Storey, and J. M. Akey (2008). “Mapping gene expression quantitative trait loci by singular value decomposition and independent component analysis”. BMC Bioinformatics 9.1, p. 244. https://dx.doi.org/10.1186/1471-2105-9-244.
  65. Storey, J. D., J. Madeoy, J. L. Strout, M. Wurfel, J. Ronald, and J. M. Akey (2007). “Gene-Expression Variation Within and Among Human Populations”. The American Journal of Human Genetics 80.3, pp. 502-509. https://dx.doi.org/10.1086/512017.
  66. Storey, J. D. (2007). “The optimal discovery procedure: a new approach to simultaneous significance testing”. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 69.3, pp. 347-368. https://dx.doi.org/10.1111/j.1467-9868.2007.005592.x.
  67. Leek, J. T. and J. D. Storey (2007). “Capturing heterogeneity in gene expression studies by surrogate variable analysis”. PLoS Genetics 3.9, p. e161. https://dx.doi.org/10.1371/journal.pgen.0030161.
  68. Dabney, A. R. and J. D. Storey (2007). “Optimality driven nearest centroid classification from genomic data”. PLoS ONE 2.10. Ed. by J. Zhu, p. e1002. https://dx.doi.org/10.1371/journal.pone.0001002.
  69. Dabney, A. R. and J. D. Storey (2007). “Normalization of two-channel microarrays accounting for experimental design and intensity-dependent relationships”. Genome Biology 8.3, p. R44. https://dx.doi.org/10.1186/gb-2007-8-3-r44.
  70. Chen, L. S., F. Emmert-Streib, and J. D. Storey (2007). “Harnessing naturally randomized transcription to infer regulatory relationships among genes”. Genome Biology 8.10, p. R219. https://dx.doi.org/10.1186/gb-2007-8-10-r219.
  71. Akey, J. M., S. Biswas, J. T. Leek, and J. D. Storey (2007). “On the design and analysis of gene expression studies in human populations”. Nature Genetics 39.7, pp. 807-808. https://dx.doi.org/10.1038/ng0707-807.
  72. Storey, J. D., J. Y. Dai, and J. T. Leek (2006). “The optimal discovery procedure for large-scale significance testing, with applications to comparative microarray experiments”. Biostatistics 8.2, pp. 414-432. https://dx.doi.org/10.1093/biostatistics/kxl019.
  73. Dabney, A. R. and J. D. Storey (2006). “A new approach to intensity-dependent normalization of two-channel microarrays”. Biostatistics 8.1, pp. 128-139. https://dx.doi.org/10.1093/biostatistics/kxj038.
  74. Dabney, A. R. and J. D. Storey (2006). “A reanalysis of a published Affymetrix GeneChip control dataset”. Genome Biology 7.3, p. 401. https://dx.doi.org/10.1186/gb-2006-7-3-401.
  75. Chen, L. (2006). “Relaxed significance criteria for linkage analysis”. Genetics 173.4, pp. 2371-2381. https://dx.doi.org/10.1534/genetics.105.052506.
  76. Leek, J. T., E. Monsen, A. R. Dabney, and J. D. Storey (2005). “Edge: extraction and analysis of differential gene expression”. Bioinformatics 22.4, pp. 507-508. https://dx.doi.org/10.1093/bioinformatics/btk005.
  77. Storey, J. D., W. Xiao, J. T. Leek, R. G. Tompkins, and R. W. Davis (2005). “Significance analysis of time course microarray experiments”. Proceedings of the National Academy of Sciences 102.36, pp. 12837-12842. https://dx.doi.org/10.1073/pnas.0504609102.
  78. Storey, J. D., J. M. Akey, and L. Kruglyak (2005). “Multiple locus linkage analysis of genomewide expression in yeast”. PLoS Biology 3.8, p. e267. https://dx.doi.org/10.1371/journal.pbio.0030267.
  79. Brem, R. B., J. D. Storey, J. Whittle, and L. Kruglyak (2005). “Genetic interactions between polymorphisms that affect gene expression in yeast”. Nature 436.7051, pp. 701-703. https://dx.doi.org/10.1038/nature03865.
  80. Storey, J. D., J. E. Taylor, and D. Siegmund (2004). “Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates: A unified approach”. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 66.1, pp. 187-205. https://dx.doi.org/10.1111/j.1467-9868.2004.00439.x.
  81. Vaszar, L. T., T. Nishimura, J. D. Storey, G. Zhao, D. Qiu, J. L. Faul, et al. (2004). “Longitudinal transcriptional analysis of developing neointimal vascular occlusion and pulmonary hypertension in rats”. Physiological Genomics 17.2, pp. 150-156. https://dx.doi.org/10.1152/physiolgenomics.00198.2003.
  82. Storey, J. D. and R. Tibshirani (2003). “Statistical significance for genomewide studies”. Proceedings of the National Academy of Sciences 100.16, pp. 9440-9445. https://dx.doi.org/10.1073/pnas.1530509100.
  83. Storey, J. D. and R. Tibshirani (2003). “Statistical methods for identifying differentially expressed genes in DNA microarrays”. In: Functional Genomics: Methods and Protocols. Ed. by M. Kaufmann and C. Klinger. Springer Nature, pp. 149-158. https://dx.doi.org/10.1385/1-59259-364-X:149.
  84. Storey, J. D. and R. Tibshirani (2003). “SAM thresholding and false discovery rates for detecting differential gene expression in DNA microarrays”. In: The Analysis of Gene Expression Data: Methods and Software. Ed. by G. Parmigiani, E. S. Garett, R. A. Irizarry and S. L. Zeger. Springer New York, pp. 272-290. https://dx.doi.org/10.1007/b97411.
  85. Storey, J. D. (2003). “The positive false discovery rate: A Bayesian interpretation and the q-value”. Annals of Statistics 31.6, pp. 2013-2035. https://dx.doi.org/10.1214/aos/1074290335.
  86. Arava, Y., Y. Wang, J. D. Storey, C. L. Liu, P. O. Brown, and D. Herschlag (2003). “Genome-wide analysis of mRNA translation profiles in Saccharomyces cerevisiae”. Proceedings of the National Academy of Sciences 100.7, pp. 3889-3894. https://dx.doi.org/10.1073/pnas.0635171100.
  87. Wang, Y., C. L. Liu, J. D. Storey, R. J. Tibshirani, D. Herschlag, and P. O. Brown (2002). “Precision and functional specificity in mRNA decay”. Proceedings of the National Academy of Sciences 99.9, pp. 5860-5865. https://dx.doi.org/10.1073/pnas.092538799.
  88. Storey, J. D. (2002). “False discovery rates: Theory and applications to DNA microarrays”. PhD Dissertation. Stanford University. https://searchworks.stanford.edu/view/5417184.
  89. Clement, K. (2002). “In vivo regulation of human skeletal muscle gene expression by thyroid hormone”. Genome Research 12.2, pp. 281-291. https://dx.doi.org/10.1101/gr.207702.
  90. Storey, J. D. (2002). “A direct approach to false discovery rates”. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 64.3, pp. 479-498. https://dx.doi.org/10.1111/1467-9868.00346.
  91. Efron, B., R. Tibshirani, J. D. Storey, and V. Tusher (2001). “Empirical Bayes analysis of a microarray experiment”. Journal of the American Statistical Association 96.456, pp. 1151-1160. https://dx.doi.org/10.1198/016214501753382129.
  92. Storey, J. D. and R. Tibshirani (2001). “Estimating the positive false discovery rate under dependence, with applications to DNA microarrays”. Technical Report 2001-28. Department of Statistics, Stanford University. http://storeylab.org/doc/2001-28.pdf.
  93. Efron, B., J. D. Storey, and R. Tibshirani (2001). “Microarrays, empirical Bayes methods, and false discovery rates”. Technical Report Bio-217. Department of Statistics, Stanford University. http://storeylab.org/doc/BIO217.pdf.
  94. Storey, J. D. (2001). “A new approach to false discovery rates and multiple hypothesis testing”. Technical Report 2001-18. Department of Statistics, Stanford University. http://storeylab.org/doc/2001-18.pdf.
  95. Efron, B., R. Tibshirani, J. D. Storey, and V. Tusher (2001). “Empirical Bayes analysis of a microarray experiment”. Technical Report Bio-216. Department of Statistics, Stanford University. http://storeylab.org/doc/BIO216.pdf.
  96. Storey, J. D. (2001). “The false discovery rate: A Bayesian interpretation and the q-value”. Technical Report 2001-12. Department of Statistics, Stanford University. http://storeylab.org/doc/2001-12.pdf.
  97. Gilbert, C. L., J. D. Kolesar, C. A. Reiter, and J. D. Storey (2001). “Function digraphs of quadratic maps modulo p”. Fibonacci Quarterly 39.1, pp. 32-49.
  98. Storey, J. D. and D. Siegmund (2001). “Approximate p-values for local sequence alignments: Numerical studies”. Journal of Computational Biology 8.5, pp. 549-556. https://dx.doi.org/10.1089/106652701753216530.