An empirical Bayes mixture model for SNP detection in pooled sequencing data

Bioinformatics

Volumn 28, Issue 20, 2012, Pages 2569-2575

  Zhou, Baiyu ^a  

^a ALBERT EINSTEIN COLLEGE OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BAYES THEOREM; DNA SEQUENCE; EVALUATION; GENE FREQUENCY; GENOMICS; HUMAN; METHODOLOGY; SINGLE NUCLEOTIDE POLYMORPHISM; STATISTICAL MODEL;

BAYES THEOREM; GENE FREQUENCY; GENOMICS; HUMANS; MODELS, STATISTICAL; POLYMORPHISM, SINGLE NUCLEOTIDE; SEQUENCE ANALYSIS, DNA;

EID: 84870464503     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/bts501     Document Type: Article

References (31)

1. Bansal, V. (2010) A statistical method for the detection of variants from next-generation resequencing of DNA pools. Bioinformatics, 26, 1318-1324.
2. Bansal, V. et al. (2010) Accurate detection and genotyping of SNPs utilizing population sequencing data. Genome Res., 20, 537-545.
3. Bansal, V. et al. (2011) Efficient and cost effective population resequencing by pooling and in-solution hybridization. PLoS One, 6, el8353.
4. Benjamini, Y. and Hochberg, Y. (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc B., 57, 289-300.
5. Bodmer, W. and Bonilla, C. (2008) Common and rare variants in multifactorial susceptibility to common diseases. Nat Genet., 40, 695-701.
6. Brown, L.D. (2008) In-season prediction of batting averages: a field test of empirical Bayes and Bayes methodologies. Ann. Appl. Statist., 2, 113-152.
7. Cohen, J.C. et al. (2006) Multiple rare variants in NPC1L1 associated with reduced sterol absorption and plasma low-density lipoprotein levels. Proc. Natl. Acad, Sei. USA., 103, 1810-1815.
8. Druley, T.E. et al. (2009) Quantification of rare allelic variants from pooled genomic DNA. Nat. Methods, 6, 263-265.
9. Efron, B. (2007) Size, power and false discovery rates. Ann. Statist., 35, 1351-1377.
10. Efron, B. et al. (2001) Empirical bayes analysis of a microarray experiment. J. Am. Stat. Assoc, 96, 1151-1160.
11. Efron, B. and Morris, C. (1975) Data analysis using Stein's estimator and its generalizations. J. Amer. Stat. Assoc, 70, 311-319.
12. Finner, H. and Roters, M. (2002) Multiple hypotheses testing and expected number of type I errors. Ann. Stat., 30, 220-238.
13. Ji, W. et al. (2008) Rare independent mutations in renal salt handling genes contribute to blood pressure variation. Nat. Genet., 40, 592-599.
14. Kim, S.Y. et al. (2010) Design of association studies with pooled or un-pooled next-generation sequencing data. Genet. Epidemiol., 34, 479-491.
15. Koboldt, D.C. et al. (2009) VarScan: variant detection in massively parallel sequencing of individual and pooled samples. Bioinformatics, 25, 2283-2285.
16. Li, H. et al. (2008) Mapping short DNA sequencing reads and calling variants using mapping quality scores. Genome Res., 18, 1851-1858.
17. Li, H. and Durbin, R. (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics, 25, 1754-1760.
18. Liao, J.G. et al. (2004) A mixture model for estimating the local false discovery rate in DNA microarray analysis. Bioinformatics, 20, 2694-2701.
19. Manolio, T.A et al. (2009) Finding the missing heritability of complex diseases. Nature, 461, 747-753.
20. Martin, E.R. et al. (2010) SeqEM: an adaptive genotype-calling approach for next-generation sequencing studies. Bioinformatics, 26, 2803-2810.
21. Meng, X. and Rubin, D.B. (1993) Maximum likelihood estimation via the ECM algorithm: a general framework. Biometrika, 80, 267-278.
22. Muralidharan, O. (2010) An empirical Bayes mixture method for effect size and false discovery rate estimation. Ann. Appl. Stat., 4, 422-438.
23. Muralidharan, O. et al. (2011) A cross-sample statistical model for SNP detection in short-read sequencing data. Nucleic Acids Res., doi: 10.1093/nar/gkr851.
24. Nejentsev, S. et al. (2009) Rare variants of IFIH1, a gene implicated in antiviral responses, protect against type 1 diabetes. Science, 324, 387-389.
25. Pan, W. et al. (2003) A mixture model approach to detecting differentially expressed genes with microarray data. Fund. Integr. Genomics, 3, 117-124.
26. Rivas et al. (2011) Deep resequencing of GWAS loci identifies independent rare variants associated with inflammatory bowel disease. Nat. Genet., 43, 1066-1073.
27. Robbins, H. (1954) An empirical Bayes approach to statistics. In Neyman, J. (ed.) Proc. Thrid Berkeley Sympos. Math. Statist. Prohah. 1. Univ. California Press, Berkeley, CA, pp. 157-163.
28. Storey, J.D. (2002) A direct approach to false discovery rates. J. R. Stat. Soc B, 64, 479-498.
29. Wang, T et al. (2010) Resequencing of pooled DNA for detecting disease associations with rare variants. Genet. Epidemiol., 34, 492-501.
30. Wei, Z et al. (2011) SNVer: a statistical tool for variant calling in analysis of pooled or individual next-generation sequencing data. Nucleic Acids Res., 39, el32, doi: 10.1093/nar/gkr599.
31. Zhou, B. and Whittemore, A.S. (2012) Improving sequence-based genotype calls with linkage disequilibrium and pedigree information. Ann. Appl. Stat., 6, 457-475.