(For more info on the statistical modelling book, Data and Software, please see the tabs above. For ongoing works on sequencing data analysis go to our biostatwiki page)


Pawitan Y: In All Likelihood: Statistical modeling and inference using likelihood. 525 pages. Oxford University Press. 2001.

Lee Y, Nelder J and Pawitan Y: Generalized linear models with random effects. 396 pages, Chapman and Hall, July 2006. 2nd Edition 2017.

ArXiv articles

  1. Pawitan Y (2020). Defending the P-value.
  2. Pawitan Y and Sjölander, A. (2020). Dealing with multiple testing: To adjust or not to adjust.
  3. Pawitan Y. (2020). Likelihood-based solution to the Monty Hall puzzle and a related 3-prisoner paradox.
  4. Pawitan Y (2021). Lottery paradox, DNA evidence and other stories: How to accept uncertain statements.
  5. Pawitan Y (2021). A nonBayesian view of Hempel’s paradox of the ravens.
  6. Pawitan Y and Lee Y (2021). On rereading Savage.
  7. Pawitan Y,  Lee H and Lee Y. Epistemic confidence, the Dutch Book and relevant subsets.
  8. Lee Y and Pawitan Y. Popper’s falsification and corroboration from the statistical perspectives.

Refereed Articles

  1. Ning Z, Pawitan Y, Shen X. High-definition likelihood inference of genetic correlations across human complex traits. Nat Genet. 2020 Aug;52(8):859-864. doi: 10.1038/s41588-020-0653-y.
  2. Reproducibility of Methods to Detect Differentially Expressed Genes from Single-Cell RNA Sequencing. Mou T, Deng W, Gu F, Pawitan Y, Vu TN. Front Genet. 2020 Jan 17;10:1331. doi: 10.3389/fgene.2019.01331. 
  3. Grassmann F, Pawitan Y, Czene K. A systems genomics approach to uncover the molecular properties of cancer genes. Sci Rep. 2020 Oct 27;10(1):18392. doi: 10.1038/s41598-020-75400-2.
  4. Cui C, Longinetti E, Larsson H, Andersson J, Pawitan Y, Piehl F, Fang F. Associations between autoimmune diseases and amyotrophic lateral sclerosis: a register-based study. Amyotroph Lateral Scler Frontotemporal Degener. 2020 Dec 17:1-9. doi: 10.1080/21678421.2020.1861022.
  5. Cui C, Sun J, Pawitan Y, Piehl F, Chen H, Ingre C, Wirdefeldt K, Evans M, Andersson J, Carrero JJ, Fang F. Creatinine and C-reactive protein in amyotrophic lateral sclerosis, multiple sclerosis and Parkinson’s disease. Brain Commun. 2020 Sep 18;2(2):fcaa152. doi: 10.1093/braincomms/fcaa152
  6. Hong MG, Dodig-Crnković T, Chen X, Drobin K, Lee W, Wang Y, Edfors F, Kotol D, Thomas CE, Sjöberg R, Odeberg J, Hamsten A, Silveira A, Hall P, Nilsson P, Pawitan Y, Uhlén M, Pedersen NL, Hägg S, Magnusson PK, Schwenk JM. Profiles of histidine-rich glycoprotein associate with age and risk of all-cause mortality. Life Sci Alliance. 2020 Jul 31;3(10):e202000817. doi: 10.26508/lsa.202000817
  7. Yang H, Pawitan Y, He W, Eriksson L, Holowko N, Hall P, Czene K. Disease trajectories and mortality among women diagnosed with breast cancer. Breast Cancer Res. 2019 Aug 16;21(1):95. doi: 10.1186/s13058-019-1181-5
  8. Sun J, Zhan Y, Mariosa D, Larsson H, Almqvist C, Ingre C, Zagai U, Pawitan Y, Fang F. Antibiotics use and risk of amyotrophic lateral sclerosis in Sweden. Eur J Neurol. 2019 Nov;26(11):1355-1361. doi: 10.1111/ene.13986. Epub 2019 Jun 7.
  9. Deng W, Mou T, Niu N, Wang L, Pawitan Y, Vu TN. Alternating EM algorithm for a bilinear model in isoform quantification from RNA-seq data. Bioinformatics. 2019 Aug 10. pii: btz640. doi: 10.1093/bioinformatics/btz640. [Epub ahead of print]
  10. Vu TN, Nguyen HN, Calza S, Kalari KR, Wang L, Pawitan Y. Cell-level somatic mutation detection from single-cell RNA sequencing. Bioinformatics. 2019 Nov 1;35(22):4679-4687. doi: 10.1093/bioinformatics/btz288.
  11. Dahlqwist E, Magnusson PKE, Pawitan Y, Sjölander A. On the relationship between the heritability and the attributable fraction. Hum Genet. 2019 Apr;138(4):425-435. doi: 10.1007/s00439-019-02006-8. Epub 2019 Apr 2.
  12. Hwang W, Calza S, Silvestri M, Pawitan Y, Lee Y. CREDO: Highly confident disease-relevant A-to-I RNA-editing discovery in breast cancer. Sci Rep. 2019 Mar 25;9(1):5064. doi: 10.1038/s41598-019-41294-y
  13. Yang H, Pawitan Y, He W, Eriksson L, Holowko N, Hall P, Czene K. Disease trajectories and mortality among women diagnosed with breast cancer. Breast Cancer Res. 2019 Aug 16;21(1):95. doi: 10.1186/s13058-019-1181-5
  14. Sun J, Zhan Y, Mariosa D, Larsson H, Almqvist C, Ingre C, Zagai U, Pawitan Y, Fang F. Antibiotics use and risk of amyotrophic lateral sclerosis in Sweden. Eur J Neurol. 2019 Nov;26(11):1355-1361. doi: 10.1111/ene.13986. Epub 2019 Jun 7.
  15. Vu, Trung Nghia; Wills, Quin F; Kalari, Krishna R; Niu, Nifang; Wang, Liewei; Pawitan, Yudi; Rantalainen, Mattias. Isoform-level gene expression patterns in single-cell RNA-sequencing data, Bioinformatics, 2018 Jul 15;34(14):2392-2400.
  16. Lee, Woojoo; Sjölander, Arvid; Larsson, Anton; Pawitan, Yudi; Likelihood-based inference for bounds of causal parameters, Stat Med. 2018 Dec 30;37(30):4695-4706.
  17. Lee, Sangin; Lee, Youngjo; Pawitan, Yudi; Sparse pathway-based prediction models for high-throughput molecular data. Computational Statistics & Data Analysis 2018, 126,125-135.
  18. [Based on the winning submission to the ‘Neuroblastoma Data Integration Challenge’, a 2017 international data analysis competition organized by CAMDA (Critical Assessment of Massive Data Analysis).] Suo, Chen; Deng, Wenjiang; Vu, Trung Nghia; Li, Mingrui; Shi, Leming; Pawitan, Yudi; Accumulation of potential driver genes with genomic alterations predicts survival of high-risk neuroblastoma patients, Biology direct, 2018 Jul 16;13(1):14.1.
  19. Yang H, Pawitan Y, He W, Eriksson L, Holowko N, Hall P, Czene K. Disease trajectories and mortality among women diagnosed with breast cancer. Breast Cancer Res. 2019 Aug 16;21(1):95. doi: 10.1186/s13058-019-1181-5
  20. Sun J, Zhan Y, Mariosa D, Larsson H, Almqvist C, Ingre C, Zagai U, Pawitan Y, Fang F. Antibiotics use and risk of amyotrophic lateral sclerosis in Sweden. Eur J Neurol. 2019 Nov;26(11):1355-1361. doi: 10.1111/ene.13986. Epub 2019 Jun 7.
  21. Vu, Trung Nghia; Deng, Wenjiang; Trac, Quang Thinh; Calza, Stefano; Hwang, Woochang; Pawitan, Yudi; ,A fast detection of fusion genes from paired-end RNA-seq data. BMC Genomics, 2018 Nov 1;19(1):786
  22. Liu XR, Pawitan Y, Clements MS. Generalized survival models for correlated time-to-event data. Stat Med. 2017 Sep 14. [Epub ahead of print]
  23. Dahlqwist E, Pawitan Y, Sjölander A. Regression standardization and attributable fraction estimation with between-within frailty models for clustered survival data. Stat Methods Med Res. 2017 Jan 1. [Epub ahead of print]
  24. Wang, Mi; Uebbing, Severin; Pawitan, Yudi; Scofield, Douglas G; RPASE: individual based allele-specific expression detection without prior knowledge of haplotype phase,Molecular ecology resources. Mol Ecol Resour. 2018 Nov;18(6):1247-1262.
  25. Yip, Benjamin Hon Kei; Bai, Dan; Mahjani, Behrang; Klei, Lambertus; Pawitan, Yudi; Hultman, Christina M; Grice, Dorothy E; Roeder, Kathryn; Buxbaum, Joseph D; Devlin, Bernie; ,”Heritable variation, with little or no maternal effect, accounts for recurrence risk to autism spectrum disorder in Sweden”, Biological psychiatry 2018, 83,7, 589-597.
  26. Pawitan Y and Lee Y. Wallet game: probability, likelihood and extended likelihood. The American Statistician 2017, 71: 120-122.
  27. Eriksson M, Czene K, Pawitan Y, Leifland K, Darabi H, Hall P. A clinical model for identifying the short-term risk of breast cancer. Breast Cancer Res. 2017 Mar 14;19(1):29. doi: 10.1186/s13058-017-0820-y.
  28. Setiawan A, Yin L, Auer G, Czene K, Smedby KE, Pawitan Y. Patterns of acute inflammatory symptoms prior to cancer diagnosis. Sci Rep. 2017 Mar 6;7(1):67. doi: 10.1038/s41598-017-00133-8.
  29. Pettersson A, Gerke T, Fall K, Pawitan Y, Holmberg L, Giovannucci EL, Kantoff PW, Adami HO, Rider JR, Mucci LA; Transdisciplinary Prostate Cancer Partnership (ToPCaP). The ABC model of prostate cancer: A conceptual framework for the design and interpretation of prognostic studies. Cancer. 2017 Feb 2. doi: 10.1002/cncr.30582. [Epub ahead of print]
  30. Vu TN, Wills QF, Kalari KR, Niu N, Wang L, Rantalainen M, Pawitan Y. Beta-Poisson model for single-cell RNA-seq data analyses. Bioinformatics. 2016 Apr 19. pii: btw202. [Epub ahead of print]
  31. Dahlqwist E, Zetterqvist J, Pawitan Y, Sjölander A. Model-based estimation of the attributable fraction for cross-sectional, case-control and cohort studies using the R package AF. Eur J Epidemiol. 2016 Mar 18. [Epub ahead of print]
  32. Lee W, Sjölander A, Pawitan Y. A Critical Look at Entropy-Based Gene-Gene Interaction Measures. Genet Epidemiol. 2016 May 27. doi: 10.1002/gepi.21974. [Epub ahead of print]
  33. [This is based on a DREAM Challenge project in Alzheimer’s Disease, where our team ADDT was a joint winner with Guan Lab.] Allen GI, Amoroso N, Anghel C, Balagurusamy V, Bare CJ, Beaton D, Bellotti R, Bennett DA, Boehme KL, Boutros PC, Caberlotto L, Caloian C, Campbell F, Chaibub Neto E, Chang YC, Chen B, Chen CY, Chien TY, Clark T, Das S, Davatzikos C, Deng J, Dillenberger D, Dobson RJ, Dong Q, Doshi J, Duma D, Errico R, Erus G, Everett E, Fardo DW, Friend SH, Fröhlich H, Gan J, St George-Hyslop P, Ghosh SS, Glaab E, Green RC, Guan Y, Hong MY, Huang C, Hwang J, Ibrahim J, Inglese P, Iyappan A, Jiang Q, Katsumata Y, Kauwe JS, Klein A, Kong D, Krause R, Lalonde E, Lauria M, Lee E, Lin X, Liu Z, Livingstone J, Logsdon BA, Lovestone S, Ma TW, Malhotra A, Mangravite LM, Maxwell TJ, Merrill E, Nagorski J, Namasivayam A, Narayan M, Naz M, Newhouse SJ, Norman TC, Nurtdinov RN, Oyang YJ, Pawitan Y, Peng S, Peters MA, Piccolo SR, Praveen P, Priami C, Sabelnykova VY, Senger P, Shen X, Simmons A, Sotiras A, Stolovitzky G, Tangaro S, Tateo A, Tung YA, Tustison NJ, Varol E, Vradenburg G, Weiner MW, Xiao G, Xie L, Xie Y, Xu J, Yang H, Zhan X, Zhou Y, Zhu F, Zhu H, Zhu S; Alzheimer’s Disease Neuroimaging Initiative. Crowdsourced estimation of cognitive decline and resilience in Alzheimer’s disease. Alzheimers Dement. 2016 Apr 11. pii: S1552-5260(16)00081-9. doi: 10.1016/j.jalz.2016.02.006. [Epub ahead of print]
  34. Magnusson PK, Lee D, Chen X, Szatkiewicz J, Pramana S, Teo S, Sullivan PF, Feuk L, Pawitan Y. One CNV Discordance in NRXN1 Observed Upon Genome-wide Screening in 38 Pairs of Adult Healthy Monozygotic Twins. Twin Res Hum Genet. 2016 Feb 22:1-7. [Epub ahead of print]
  35. Lee D, Ganna A, Pawitan Y, Lee W. Nonparametric estimation of the rediscovery rate. Stat Med. 2016 Feb 22. doi: 10.1002/sim.6915. [Epub ahead of print]
  36. Zetterqvist J, Vansteelandt S, Pawitan Y, Sjölander A. Doubly robust methods for handling confounding by cluster. Biostatistics. 2015 Oct 26. pii: kxv041. [Epub ahead of print]
  37. Lee W, Lee D, Pawitan Y. Likelihood ratio and score burden tests for detecting disease-associated rare variants. Stat Appl Genet Mol Biol. 2015 Nov 1;14(5):481-95. doi: 10.1515/sagmb-2014-0089.
  38. Lee W, Alexeyenko A, Pernemalm M, Guegan J, Dessen P, Lazar V, Lehtiö J, Pawitan Y. Identifying and Assessing Interesting Subgroups in a Heterogeneous Population. Biomed Res Int. 2015;2015:462549. doi: 10.1155/2015/462549. Epub 2015 Aug 3.
  39. Lee S, Pawitan Y, Ingelsson E, Lee Y. Sparse estimation of gene-gene interactions in prediction models. Stat Methods Med Res. 2015 Aug 11. pii: 0962280215597261. [Epub ahead of print]
  40. Suo C, Hrydziuszko O, Lee D, Pramana S, Saputra D, Joshi H, Calza S, Pawitan Y. Integration of somatic mutation, expression and functional data reveals potential driver genes predictive of breast cancer survival. Bioinformatics. 2015 Mar 24. pii: btv164. [Epub ahead of print]
  41. Peng Z, Andersson K, Lindholm J, Dethlefsen O, Pramana S, Pawitan Y, Nistér M, Nilsson S, Li C. Improving the Prediction of Prostate Cancer Overall Survival by Supplementing Readily Available Clinical Data with Gene Expression Levels of IGFBP3 and F3 in Formalin-Fixed Paraffin Embedded Core Needle Biopsy Material. PLoS One. 2016 Jan 5;11(1):e0145545.
  42. Hägg S, Ganna A, Van Der Laan SW, Esko T, Pers TH, Locke AE, Berndt SI, Justice AE, Kahali B, Siemelink MA, Pasterkamp G; GIANT Consortium, Strachan DP, Speliotes EK, North KE, Loos RJ, Hirschhorn JN, Pawitan Y, Ingelsson E. Gene-based meta-analysis of genome-wide association studies implicates new loci involved in obesity. Hum Mol Genet. 2015 Dec 1;24(23):6849-60. doi: 10.1093/hmg/ddv379. Epub 2015 Sep 16.
  43. Lazar V, Rubin E, Depil S, Pawitan Y, Martini JF, Gomez-Navarro J, Yver A, Kan Z, Dry JR, Kehren J, Validire P, Rodon J, Vielh P, Ducreux M, Galbraith S, Lehnert M, Onn A, Berger R, Pierotti MA, Porgador A, Pramesh CS, Ye DW, Carvalho AL, Batist G, Le Chevalier T, Morice P, Besse B, Vassal G, Mortlock A, Hansson J, Berindan-Neagoe I, Dann R, Haspel J, Irimie A, Laderman S, Nechushtan H, Al Omari AS, Haywood T, Bresson C, Soo KC, Osman I, Mata H, Lee JJ, Jhaveri K, Meurice G, Palmer G, Lacroix L, Koscielny S, Eterovic KA, Blay JY, Buller R, Eggermont A, Schilsky RL, Mendelsohn J, Soria JC, Rothenberg M, Scoazec JY, Hong WK, Kurzrock R. A simplified interventional mapping system (SIMS) for the selection of combinations of targeted treatments in non-small cell lung cancer. Oncotarget. 2015 Jun 10;6(16):14139-52.
  44. Sinnott JA, Rider JR, Carlsson J, Gerke T, Tyekucheva S, Penney KL, Sesso HD, Loda M, Fall K, Stampfer MJ, Mucci LA, Pawitan Y, Andersson SO, Andrén O. Molecular differences in transition zone and peripheral zone prostate tumors. Carcinogenesis. 2015 Jun;36(6):632-8. doi: 10.1093/carcin/bgv051. Epub 2015 Apr 13.
  45. Pawitan Y, Yin L, Setiawan A, Auer G, Smedby KE, Czene K. Distinct effects of anti-inflammatory and anti-thrombotic drugs on cancer characteristics at diagnosis. Eur J Cancer. 2015 Feb 25. [Epub ahead of print]
  46. Schwaederle M, Vladimir L, Validire P, Hansson J, Lacroix L, Soria JC, Pawitan Y, Kurzrock R. VEGF-A Expression Correlates with TP53 Mutations in Non-Small Cell Lung Cancer: Implications for Anti-Angiogenesis Therapy. Cancer Res. 2015 Feb 11. pii: canres.2305.2014. [Epub ahead of print]
  47. Ganna A, Lee D, Ingelsson E, Pawitan Y. Rediscovery rate estimation for assessing the validation of significant findings in high-throughput studies. Brief Bioinform. 2014 Sep 24. pii: bbu033. [Epub ahead of print]
  48. Sjölander A, Lee W, Källberg H, Pawitan Y. Bounds on sufficient-cause interaction. Eur J Epidemiol. 2014 Nov;29(11):813-20.
  49. Sjölander A, Lee W, Källberg H, Pawitan Y. Bounds on causal interactions for binary outcomes. Biometrics. 2014 Mar 12. doi: 10.1111/biom.12166. [Epub ahead of print]
  50. Gaugler T, Klei L, Sanders SJ, Bodea CA, Goldberg AP, Lee AB, Mahajan M, Manaa D, Pawitan Y, Reichert J, Ripke S, Sandin S, Sklar P, Svantesson O, Reichenberg A, Hultman CM, Devlin B, Roeder K, Buxbaum JD. Most genetic risk for autism resides with common variation. Nat Genet. 2014 Aug;46(8):881-5. doi: 10.1038/ng.3039. Epub 2014 Jul 20.
  51. Holmes MD, Olsson H, Pawitan Y, Holm J, Lundholm C, Andersson TM, Adami HO, Askling J, Smedby KE. Aspirin intake and breast cancer survival – a nation-wide study using prospectively recorded data in Sweden. BMC Cancer. 2014 Jun 2;14:391. doi: 10.1186/1471-2407-14-391.
  52. Bachmann J, Burté F, Pramana S, Conte I, Brown BJ, Orimadegun AE, Ajetunmobi WA, Afolabi NK, Akinkunmi F, Omokhodion S, Akinbami FO, Shokunbi WA, Kampf C, Pawitan Y, Uhlén M, Sodeinde O, Schwenk JM, Wahlgren M, Fernandez-Reyes D, Nilsson P. Affinity proteomics reveals elevated muscle proteins in plasma of children with cerebral malaria. PLoS Pathog. 2014 Apr 17;10(4):e1004038.doi: 10.1371/journal.ppat.1004038. eCollection 2014 Apr.
  53. Peng Z, Skoog L, Hellborg H, Jonstam G, Wingmo IL, Hjälm-Eriksson M, Harmenberg U, Cedermark GC, Andersson K, Ahrlund-Richter L, Pramana S, Pawitan Y, Nistér M, Nilsson S, Li C. An expression signature at diagnosis to estimate prostate cancer patients’ overall survival. Prostate Cancer Prostatic Dis. 2014 Jan 7. doi: 10.1038/pcan.2013.57. [Epub ahead of print]
  54. Suo C, Calza S, Salim A, Pawitan Y. Joint estimation of isoform expression and isoform-specific read distribution using multisample RNA-Seq data. Bioinformatics. 2013 Dec 27. [Epub ahead of print]
  55. Lazar V, Suo C, Orear C, van den Oord J, Balogh Z, Guegan J, Job B, Meurice G, Ripoche H, Calza S, Hasmats J, Lundeberg J, Lacroix L, Vielh P, Dufour F, Lehtiö J, Napieralski R, Eggermont A, Schmitt M, Cadranel J, Besse B, Girard P, Blackhall F, Validire P, Soria JC, Dessen P, Hansson J, Pawitan Y. Integrated molecular portrait of non-small cell lung cancers. BMC Med Genomics. 2013 Dec 3;6:53. doi: 10.1186/1755-8794-6-53.
  56. Lee D, Lee Y, Pawitan Y, Lee W. Sparse partial least-squares regression for high-throughput survival data analysis. Stat Med. 2013 Dec 30;32(30):5340-52.
  57. Gusnanto A, Ploner A, Shuweihdi F, Pawitan Y. Partial least squares and logistic regression random-effects estimates for gene selection in supervised classification of gene expression data. J Biomed Inform. 2013 Aug;46(4):697-709.
  58. Peng Z, Skoog L, Hellborg H, Jonstam G, Wingmo IL, Hjälm-Eriksson M, Harmenberg U, Cedermark GC, Andersson K, Ahrlund-Richter L, Pramana S, Pawitan Y, Nistér M, Nilsson S, Li C. An expression signature at diagnosis to estimate prostate cancer patients’ overall survival. Prostate Cancer Prostatic Dis. 2014 Jan 7. doi: 10.1038/pcan.2013.57. [Epub ahead of print]
  59. Jonsson F, Yin L, Lundholm C, Smedby KE, Czene K, Pawitan Y. Low-dose aspirin use and cancer characteristics: a population-based cohort study. Br J Cancer. 2013 Jul 25. [Epub ahead of print]
  60. Berndt SI, Gustafsson S, Mägi R, Ganna A, … ,North KE, Loos RJ, Ingelsson E. Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture. Nat Genet. 2013 May;45(5):501-12.
  61. Pernemalm M, De Petris L, Branca RM, Forshed J, Kanter L, Soria JC, Girard P, Validire P, Pawitan Y, van den Oord J, Lazar V, Påhlman S, Lewensohn R, Lehtiö J. Quantitative proteomics profiling of primary lung adenocarcinoma tumors reveals functional perturbations in tumor metabolism. J Proteome Res. 2013 Sep 6;12(9):3934-43.
  62. Sjölander A, Lichtenstein P, Larsson H, Pawitan Y. Between-within models for survival analysis. Stat Med. 2013 Mar 3. [Epub ahead of print]
  63. Sjölander A, Johansson ALV, Lundholm C, Altman D, Almqvist C, Pawitan Y. (2012). Analysis of 1:1 matched cohort studies and twin studies, with binary exposures and binary outcomes. Statistical Science 27(3), 395–411.
  64. Sjölander A, Lichtenstein P, Larsson H, Pawitan Y. Between-within models for survival analysis. Stat Med. 2013 Mar 3. [Epub ahead of print]
  65. Teo SM, Pawitan Y, Ku CS, Chia KS, Salim A. Statistical challenges associated  with detecting copy number variations with next-generation sequencing. Bioinformatics, 2012 Nov 1;28(21):2711-8. doi: 10.1093/bioinformatics/bts535. Epub 2012 Aug 31.
  66. Alexeyenko A, Lee W, Pernemalm M, Guegan J, Dessen P, Lazar V, Lehtiö J, Pawitan Y. Network enrichment analysis: extension of gene-set enrichment analysis to gene networks. BMC Bioinformatics, 2012 Sep 11;13:226. doi: 10.1186/1471-2105-13-226.
  67. Hong MG, Karlsson R, Magnusson PK, Lewis MR, Isaacs W, Zheng LS, Xu J, Grönberg H, Ingelsson E, Pawitan Y, Broeckling C, Prenni JE, Wiklund F, Prince JA. A Genome-Wide Assessment of Variability in Human Serum Metabolism. Hum Mutat. 2012 Dec 24. doi: 10.1002/humu.22267. [Epub ahead of print]
  68. Handali S, Pawitan Y. Verifying elimination programs with a special emphasis on cysticercosis endpoints and postelimination surveillance. J Parasitol Res. 2012;2012:974950. doi: 10.1155/2012/974950. Epub 2012 Nov 14.
  69. Frisell T, Pawitan Y, Långström N. Is the association between general cognitive ability and violent crime caused by family-level confounders? PLOS One,  2012;7(7):e41783. doi: 10.1371/journal.pone.0041783. Epub 2012 Jul 24.
  70. Eschrich SA, Fulp WJ, Pawitan Y, Foekens JA, Smid M, Martens JW, Echevarria M, Kamath V, Lee JH, Harris EE, Bergh J, Torres-Roca JF. Validation of a radiosensitivity molecular signature in breast cancer. Clin Cancer Res. 2012 Sep 15;18(18):5134-43. Epub 2012 Jul 25.
  71. Kuja-Halkola R, Pawitan Y, D’Onofrio BM, Långström N, Lichtenstein P. Advancing paternal age and offspring violent offending: a sibling-comparison study. Dev Psychopathol. 2012 Aug;24(3):739-53. doi: 10.1017/S095457941200034X.
  72. Ku CS, Polychronakos C, Tan EK, Naidoo N, Pawitan Y, Roukos DH, Mort M, Cooper DN. A new paradigm emerges from the study of de novo mutations in the context of neurodevelopmental disease. Mol Psychiatry. 2012 May 29. doi: 10.1038/mp.2012.58. [Epub ahead of print]
  73. Ku CS, Cooper DN, Wu M, Roukos DH, Pawitan Y, Soong R, Iacopetta B. Gene discovery in familial cancer syndromes by exome sequencing: prospects for the elucidation of familial colorectal cancer type X. Mod Pathol. 2012 Aug;25(8):1055-68. doi: 10.1038/modpathol.2012.62. Epub 2012 Apr 20. Review.
  74. Ku CS, Wu M, Cooper DN, Naidoo N, Pawitan Y, Pang B, Iacopetta B, Soong R. Exome versus transcriptome sequencing in identifying coding region variants. Expert Rev Mol Diagn. 2012 Apr;12(3):241-51. doi: 10.1586/erm.12.10. Review.
  75. Ku CS, Wu M, Cooper DN, Naidoo N, Pawitan Y, Pang B, Iacopetta B, Soong R. Technological advances in DNA sequence enrichment and sequencing for germline genetic diagnosis. Expert Rev Mol Diagn. 2012 Mar;12(2):159-73. doi: 10.1586/erm.11.95. Review.
  76. Ward A, Balwierz A, Zhang JD, Küblbeck M, Pawitan Y, Hielscher T, Wiemann S, Sahin O. Re-expression of microRNA-375 reverses both tamoxifen resistance and accompanying EMT-like properties in breast cancer. Oncogene. 2012 Apr 16. doi: 10.1038/onc.2012.128. [Epub ahead of print]
  77. Naidoo N, Pawitan Y, Soong R, Cooper DN, Ku CS. Human genetics and genomics a decade after the release of the draft sequence of the human genome. Hum Genomics. 2011 Oct 1;5(6):577-622.
  78. Teo SM, Ku CS, Salim A, Naidoo N, Chia KS, Pawitan Y.  Regions of homozygosity in three Southeast Asian populations. J Hum Genet. 2011 Dec 1. [Epub ahead of print]
  79. Fernberg P, Edgren G, Adami J, Ingvar A, Bellocco R, Tufveson G, Höglund P, Kinch A, Simard JF, Baecklund E, Lindelöf B, Pawitan Y, Smedby KE. Time Trends in Risk and Risk Determinants of Non-Hodgkin Lymphoma in Solid Organ Transplant Recipients. Am J Transplant. 2011 Aug 22. [Epub ahead of print]
  80. Ku CS, Teo SM, Naidoo N, Sim X, Teo YY, Pawitan Y, Seielstad M, Chia KS, Salim A.  Copy number polymorphisms in new HapMap III and Singapore populations. J Hum Genet. 2011 Aug;56(8):552-60.
  81. Frisell T, Pawitan Y, Långström N, Lichtenstein P. Heritability, Assortative Mating and Gender Differences in Violent Crime: Results from a Total Population Sample Using Twin, Adoption, and Sibling Models. Behav Genet. 2011 Jul 15. [Epub ahead of print]
  82. Lee W, Gusnanto A, Salim A, Magnusson PK, Perelman E, Sim X, Tai E, Pawitan Y. Estimating the number of true discoveries in genome-wide association studies. Statistics in Medicine 11 Oct 2011.
  83. Gusnanto A, Wood HM, Pawitan Y, Rabbitts P, and Berri S. Estimating copy number alterations in cancer genomes from clinical samples using next-generation sequencing. Bioinformatics. 2012 Jan 1;28(1):40-7.
  84. Lee D, Lee W, Lee Y, Pawitan Y. Sparse partial least-squares regression and its applications to high-throughput data analysis. Chemometrics and Intelligent Laboratory Systems. Available online 29 July 2011.
  85. Lee W, Lee D, Lee Y and Pawitan Y. Sparse Canonical Covariance Analysis for High-throughput Data.  Statistical Applications in Genetics and Molecular Biology, 2011, Vol 10: 1, Article 13.
  86. Teo SM, Pawitan Y, Kumar V, Thalamuthu A, Seielstad M, Chia KS, Salim A. Multi-platform segmentation for joint detection of copy number variants. Bioinformatics. 2011 Jun 1;27(11):1555-61.
  87. Ku CS, Teo SM, Naidoo N, Sim X, Teo YY, Pawitan Y, Seielstad M, Chia KS, Salim A.  Copy number polymorphisms in new HapMap III and Singapore populations. J Hum Genet. 2011 Aug;56(8):552-60.
  88. Frisell T, Pawitan Y, Långström N, Lichtenstein P. Heritability, Assortative Mating and Gender Differences in Violent Crime: Results from a Total Population Sample Using Twin, Adoption, and Sibling Models. Behav Genet. 2011 Jul 15. [Epub ahead of print]
  89. Teo SM, Ku CS, Naidoo N, Hall P, Chia KS, Salim A, Pawitan Y. A population-based study of copy number variants and regions of homozygosity in healthy Swedish individuals. J Hum Genet. 2011 Jul;56(7):524-33.
  90. Penney KL, Sinnott JA, Fall K, Pawitan Y, Hoshida Y, Kraft P, Stark JR, Fiorentino M, Perner S, Finn S, Calza S, Flavin R, Freedman ML, Setlur S, Sesso HD, Andersson SO, Martin N, Kantoff PW, Johansson JE, Adami HO, Rubin MA, Loda M, Golub TR, Andrén O, Stampfer MJ, Mucci LA. mRNA expression signature of Gleason grade predicts lethal prostate cancer. J Clin Oncol. 2011 Jun 10;29(17):2391-6.
  91. Ku CS, Naidoo N, Pawitan Y. Revisiting Mendelian disorders through exome sequencing. Hum Genet. 2011 Apr;129(4):351-70.
  92. Ku CS, Naidoo N, Teo SM, Pawitan Y. Regions of homozygosity and their impact on complex diseases and traits. Hum Genet. 2011 Jan;129(1):1-15.
  93. Suo C, Salim A, Chia KS, Pawitan Y, Calza S. Modified least-variant set normalization for miRNA microarray.  RNA. 2010 Oct 27. [Epub ahead of print]
  94. Calza S, Pawitan Y. Normalization of gene-expression microarray data. Methods Mol Biol. 2010; 673:37-52.
  95. Lee D, Lee W, Lee Y, Pawitan Y. Super-sparse principal component analyses for high-throughput genomic data. BMC Bioinformatics. 2010 Jun 2;11:296.
  96. Mei TS, Salim A, Calza S, Seng KC, Seng CK, Pawitan Y. Identification of recurrent regions of Copy-Number Variants across multiple individuals. BMC Bioinformatics. 2010 Mar 22;11:147.
  97. Yip BH, Moger TA, Pawitan Y. Genetic analysis of age-at-onset traits based on case-control family data. Statistics in Medicine, to appear in 2010.
  98. Yip BH, Reilly M, Cnattingius S, Pawitan Y. Matched Ascertainment of Informative Families for Complex Genetic Modelling. Behav Genet. 2009 Dec 24. [Epub ahead of print]
  99. Pawitan Y, Seng KC, Magnusson PK. How many genetic variants remain to be discovered? PLoS One. 2009 Dec 2;4(12):e7969.PMID: 199565393.
  100. Huang J, Salim A, Lei K, O’Sullivan K, Pawitan Y. Classification of array CGH data using smoothed logistic regression model. Stat Med. 2009 Dec 30;28(30):3798-810.
  101. Ku CS, Pawitan Y, Sim X, Ong RT, Seielstad M, Lee EJ, Teo YY, Chia KS, Salim A. Genomic copy number variations in three Southeast Asian populations. Hum Mutat. 2010 Jul;31(7):851-7.
  102. Ku CS, Loy EY, Salim A, Pawitan Y, Chia KS. The discovery of human genetic variations and their use as disease markers: past, present and future. J Hum Genet. 2010 Jul;55(7):403-15. Epub 2010 May 20.
  103. Ku CS, Loy EY, Pawitan Y, Chia KS. The pursuit of genome-wide association studies: where are we now? J Hum Genet. 2010 Mar 19. [Epub ahead of print]
  104. Sboner A, Demichelis F, Calza S, Pawitan Y, Setlur SR, Hoshida Y, Perner S, Adami HO, Fall K, Mucci LA, Kantoff PW, Stampfer M, Andersson SO, Varenhorst E, Johansson JE, Gerstein MB, Golub TR, Rubin MA, Andren O. Molecular sampling of prostate cancer: a dilemma for predicting disease progression. BMC Med Genomics. 2010 Mar 16; 3(1):8. [Epub ahead of print]
  105. Svensson AC, Sandin S, Cnattingius S, Reilly M, Pawitan Y, Hultman CM, Lichtenstein P. Maternal effects for preterm birth: a genetic epidemiologic study of 630,000 families. Am J Epidemiol. 2009 Dec 1;170(11):1365-72. Epub 2009 Oct 23.
  106. Lichtenstein P, Yip BH, Björk C, Pawitan Y, Cannon TD, Sullivan PF, Hultman CM. Common genetic determinants of schizophrenia and bipolar disorder in Swedish families: a population-based study. Lancet. 2009 Jan 17;373(9659):234-9.
  107. Hong MG, Pawitan Y, Magnusson PK, Prince JA. Strategies and issues in the detection of pathway enrichment in genome-wide association studies. Hum Genet. 2009 Aug; 126(2):289-301. Epub 2009 May 1.
  108. Tan CS, Salim A, Ploner A, Lehtiö J, Chia KS, Pawitan Y. Correlating gene and protein expression data using Correlated  Factor Analysis.  BMC Bioinformatics. 2009 Sep 1; 10: 272
  109. Weichselbaum RR, Ishwaran H, Yoon T, Nuyten DS, Baker SW, Khodarev N, Su AW, Shaikh AY, Roach P, Kreike B, Roizman B, Bergh J, Pawitan Y, van de Vijver MJ, Minn AJ. An interferon-related gene signature for DNA damage resistance is a predictive marker for chemotherapy and radiation for breast cancer. Proc Natl Acad Sci U S A. 2008 Nov 25;105(47):18490-5. Epub 2008 Nov 10.
  110. Demissie M; Mascialino B; Calza S; Pawitan Y. Unequal group variances in microarray data analyses. Bioinformatics. 2008 May 1;24(9):1168-74. Epub 2008 Mar 14.
  111. Calza S, Valentini D, Pawitan Y. Normalization of oligonucleotide arrays based on the least-variant set of genes. BMC Bioinformatics. 2008 Mar 5;9(1):140 [Epub ahead of print]
  112. Calza S, Raffelsberger W, Ploner A, Sahel J, Leveillard T, Pawitan Y. Filtering genes to improve sensitivity in oligonucleotide microarray data analysis. Nucleic Acids Research. 2007 Aug 15; [Epub ahead of print]
  113. Huang J, Gusnanto A, O’Sullivan K, Staaf J, Borg A, Pawitan Y. Robust smooth segmentation approach for array CGH data analysis. Bioinformatics. 2007 Sep 15;23(18):2463-9. Epub 2007 Jul 27.
  114. Moger TA, Pawitan Y, Borgan O. Case-cohort methods for survival data on families from routine registers. Stat Med. 2008 Mar 30;27(7):1062-74
  115. Yip BH, Bjork C, Lichtenstein P, Hultman CM, Pawitan Y. Covariance component models for multivariate binary traits in family data analysis. Stat Med. 2008 Mar 30;27(7):1086-1095
  116. Gusnanto A, Calza S, Pawitan Y. Identification of differentially expressed genes and false discovery rate in microarray studies. Current Opinion in Lipidology. 2007 Apr;18(2):187-93.
  117. Salim A, Pawitan Y. Model-Based Maximum Covariance Analysis for Irregularly Observed Climatological Data. Journal of Agricultural, Biological & Environmental Statistics 12: 1-24, 2007.
  118. Ha ID, Lee Y, Pawitan Y. Genetic Mixed Linear Models for Twin Survival Data. Behavior Genetics. 2007Jul;37(4):621-30. Epub 2007 Mar 31.
  119. Perelman E, Ploner A, Calza S, Pawitan Y. Detecting differential expression in microarray data: comparison of optimal procedures. BMC Bioinformatics. 2007 Jan 26; 8:28.
  120. Pawitan Y, Calza S and Ploner A. Estimation of false discovery proportion under general dependence. Bioinformatics 22: 3025 – 3031, 2006
  121. Finding regions of significance in SELDI measurements for identifying protein biomarkers. Bioinformatics (2006): Advance Access, 27 March 2006.
  122. Multidimensional local false discovery rate for microarray studies. Bioinformatics 22: 556-565, 2006.
  123. An expression signature for p53 status in human breast cancer predicts mutation status, transcriptional effects and patient survival. Proceedings of the National Academy of Science (PNAS) 2005
  124. Multi-component variance estimation from binary traits in family based-studies. Genetic Epidemiology 2005.
  125. Gene expression profiling spares early breast cancer patients from adjuvant therapy. Breast cancer research 2005
  126. Bias in the estimation of false discovery rate in microarray studies. Bioinformatics 2005.
  127. Robust ascertainment-adjusted parameter estimation. Genetic Epidemiology  2005.
  128. Using correlations to evaluate low-level analysis procedures for high-density oligonucleotide microarray data. BMC Bioifnormatics 2005.
  129. FDR, sensitivity and sample size for microarray studies. Bioinformatics 2005.
  130. NonGaussian smoothing of short transmission scans for PET whole body studies. IEEE Transaction in Medical Imaging. 2005.
  131. Maximal covariance analysis of two spatio-temporal processes. JRSS(C): Applied Statistics 2005.
  132. Modelling infectious disease transmission with complex exposure pattern and sparse outcome data. Statistics in Medicine. 2004.
  133. Estimation of genetic and environmental factors for binary traits using family data. Statistics in Medicine. 2004.
  134. Gene expression profiling for prognosis using Cox regression. Statistics in Medicine. 2004.
  135. Analysis and prediction of BSE in Ireland. Preventive Veterinary Medicine. 2004.
  136. Maternal and paternal contributions in the risk of preeclampsia. American Journal of Medical Genetics 2004.
  137. Improved grading of breast adenocarcinomas based on genomic instability. Cancer Research 2004.
  138. Risk and protective factors for Parkinson’s disease: a study in Swedish twins. Annals of Neorology 2004.
  139. Profound alterations in breast cancer incidence may reflect changes into a westernized lifestyle. International Journal of Cancer 2004.
  140. Variable selection in random calibration of near-infrared instruments: ridge regression and partial least squares regression settings. Journal of Chemometrics. 2003.
  141. Extensions of Bartlett-Lewis model for rainfall processes. Statistical Modelling. 2003.
  142. Constrained clustering of irregularly sampled spatial data. Journal of Statistical Computation and Simulation. 2003.

List of older publications

Likelihood Modelling and Inference

  1. In All Likelihood: modelling and inference using the likelihood. 2001. Oxford University Press.
  2. Estimating variance components in generalized linear mixed models using quasi-likelihood. Journal of Statistical Computation and Simulation, 2000.
  3. Computing empirical likelihood from the bootstrap. Statistics and Probability Letters, 2000 
  4. Reminder of the fallibility of Wald statistic: likelihood explanation. American Statistician, 2000.

Time series analysis

  1. Quasi-likelihood estimation of non-invertible moving average processes. Scandinavian Journal of Statistics, 2000
  2. Consistent estimation of noncausal nonGaussian autoregressive processes. Journal of Time Series Analysis, 1999.
  3. Whittle likelihood. Encyclopaedia of Statistical Science, 1999.
  4. Change point problems. Encyclopaedia of Biostatistics, 1999.
  5. Seasonal time series. Encyclopaedia of Biostatistics, 1999.
  6. Coherence between time series. Encyclopaedia of Biostatistics, 1999.
  7. Automatic estimation of coherence of bivariate time series. Biometrika, 1996.
  8. Penalized Whittle likelihood estimate of spectral density functions. Journal of American Statistical Association, 1994.
  9. Efficient bias corrected nonparametric spectral estimation. Biometrika, 1991.
  10. Spectral estimation and deconvolution for a linear time series model. Journal of Time Series Analysis, 1989.
  11. Modelling mortality fluctuations in Los Angeles as functions of pollution and weather effects. Environmental Research, 1988.

Statistical methods in medical imaging

  1. Mixed inverse problems arising in the estimation of PET calibration factors.Journal of the Royal Statistical Society, Series C, 1998.
  2. PET system calibration and attenuation correction. IEEE Transaction on Nuclear Science, 1997.
  3. Bandwidth selection for indirect density estimation. Journal of American Statistical Association, 1996.
  4. Multivariate density estimation by tomography. Journal of the Royal Statistical Society, Series B, 1993.
  5. Data dependent bandwidth selection for emission computed tomography. IEEE Transactions on medical Imaging, 1993.
  6. Reducing negativity artifacts in emission tomography. IEEE Transactions on Medical Imaging, 1993.
  7. Discussion of “From image deblurring to optimal investment: maximum likelihood solutions for positive linear inverse problems” by Y. Vardi and D. Lee. Journal of the Royal Statistical Society, Series B, 1993.

Biostatistics: methods and applications

  1. Association between ease of suppression of ventricular arrhythmia and survival. Circulation, 1995. Note: Comment in: Circulation 91(1): 245-7, 1995.
  2. Modelling disease markers in acquired immunodeficiency syndrome. Journal of American Statistical Association, 1993.
  3. Identification of secondary peak in myocardial infarction onset 11 and 12 hours after awakening. Journal of American College of Cardiology, 1993.
  4. Methods for assessing quality of life in the Cardiac Arrhythmia Suppression Trial. Quality of Life Research, 1992.
  5. Effects of advancing age on the efficacy and side effects of antiarrhythmic drugs. Journal of the American Geriatric Society, 1992.
  6. Modeling a marker of disease progression and onset of disease. AIDS Epidemiology: Methodological Issues, 1992.
  7. Congestive heart failure with preserved left ventricular function. Journal of American College of Cardiology, 1991.
  8. Events in Cardiac Arrhythmia Suppression Trial: Analysis of the placebo group. Journal of American College of Cardiology, 1991.
  9. Prevalence, characteristics and significance of ventricular arrhythmia in the Cardiac Arrhythmia Suppression Trial. American Journal of Cardiology, 1991.
  10. Increased risk of deaths and cardiac arrests from encainide and flecainide in patients after non-Q-wave myocardial infarction. American Journal of Cardiology, 1991.
  11. Statistical interim monitoring of the Cardiac Arrhythmia Suppression Trial. Statistics in Medicine 1990.
  12. Effect of encainide and flecainide on mortality in a randomized trial of arrhythmia suppression after myocardial infarction. New England Journal of Medicine, 1989.


  1. Selecting random numbers for the lotto. Journal of Statistical Education, 1999.
  2. Two-sided P-values from discrete asymmetric distributions. Statistician: Journal of the Royal Statistical Society, Series D, 1997.