Publications

1. Gorla A, Witonsky J, Chen ZJ, Elhawary JR, Mefford J, Perez-Garcia J, Madore AM, Huntsman S, Hu D, Eng C, Bhakta NR, Woodruff PG, Laprise C, Sankararaman S, Flint J, Allen CDC, Ziv E, Zaitlen N, Burchard E, Rahmani E. Epigenetic patient stratification reveals a sub-endotype of type 2 asthma with altered B-cell response.. medRxiv : the preprint server for health sciences, 2025.
2. Chen ZJ, Das SS, Kar A, Lee SHT, Abuhanna KD, Alvarez M, Sukhatme MG, Wang Z, Gelev KZ, Heffel MG, Zhang Y, Avram O, Rahmani E, Sankararaman S, Laakso M, Heinonen S, Peltoniemi H, Halperin E, Pietiläinen KH, Luo C, Pajukanta P. Single-cell DNA methylome and 3D genome atlas of human subcutaneous adipose tissue.. Nature genetics, 2025.
3. Zhu J, Kalantzis G, Pazokitoroudi A, Gunnarsson ÁF, Loya H, Chen H, Sankararaman S, Palamara PF. Fast variance component analysis using large-scale ancestral recombination graphs.. bioRxiv : the preprint server for biology, 2025.
4. Fu M, Sankararaman S, Pasaniuc B, Vossel K, Chang TS. Identifying common disease trajectories of Alzheimer's disease with electronic health records.. EBioMedicine, 2025.
5. Wei A, Border R, Fu B, Cullina S, Brandes N, Jang SK, Sankararaman S, Kenny EE, Udler MS, Ntranos V, Zaitlen N, Arboleda VA. Investigating the sources of variable impact of pathogenic variants in monogenic metabolic conditions.. Nature communications, 2025.
6. Fu M, Sankararaman S, Vossel KA, Chang TS. Identifying Common Disease Trajectories of Progressive Supranuclear Palsy with Electronic Health Records.. Movement disorders clinical practice, 2025.
7. Zhang X, Yang J, Zhu L, Sachdev N, Mooney J, Sankararaman S, Lohmueller KE. Neanderthal introgressed ancestry reveals human genomic regions enriched with recessive deleterious mutations.. bioRxiv : the preprint server for biology, 2025.
8. Xue A, Rao J, Sankararaman S, Pimentel H. dotears: Scalable and consistent directed acyclic graph estimation using observational and interventional data.. iScience, 2024.
9. Sadowski M, Thompson M, Mefford J, Haldar T, Oni-Orisan A, Border R, Pazokitoroudi A, Cai N, Ayroles JF, Sankararaman S, Dahl AW, Zaitlen N. Characterizing the genetic architecture of drug response using gene-context interaction methods.. Cell genomics, 2024.
10. Chen ZJ, Das SS, Kar A, Lee SHT, Abuhanna KD, Alvarez M, Sukhatme MG, Gelev KZ, Heffel MG, Zhang Y, Avram O, Rahmani E, Sankararaman S, Heinonen S, Peltoniemi H, Halperin E, Pietiläinen KH, Luo C, Pajukanta P. Single-cell DNA methylome and 3D genome atlas of the human subcutaneous adipose tissue.. bioRxiv : the preprint server for biology, 2024.
11. Fu B, Anand P, Anand A, Mefford J, Sankararaman S. A scalable adaptive quadratic kernel method for interpretable epistasis analysis in complex traits.. Genome research, 2024.
12. Jeong M, Pazokitoroudi A, Liu Z, Sankararaman S. Scalable summary-statistics-based heritability estimation method with individual genotype level accuracy.. Genome research, 2024.
13. Avram O, Durmus B, Rakocz N, Corradetti G, An U, Nittala MG, Terway P, Rudas A, Chen ZJ, Wakatsuki Y, Hirabayashi K, Velaga S, Tiosano L, Corvi F, Verma A, Karamat A, Lindenberg S, Oncel D, Almidani L, Hull V, Fasih-Ahmad S, Esmaeilkhanian H, Cannesson M, Wykoff CC, Rahmani E, Arnold CW, Zhou B, Zaitlen N, Gronau I, Sankararaman S, Chiang JN, Sadda SR, Halperin E. Accurate prediction of disease-risk factors from volumetric medical scans by a deep vision model pre-trained with 2D scans.. Nature biomedical engineering, 2024.
14. Gorla A, Witonsky J, Elhawary JR, Chen ZJ, Mefford J, Perez-Garcia J, Huntsman S, Hu D, Eng C, Woodruff PG, Sankararaman S, Ziv E, Flint J, Zaitlen N, Burchard E, Rahmani E. Epigenetic patient stratification via contrastive machine learning refines hallmark biomarkers in minoritized children with asthma.. Research square, 2024.
15. Sarwal V, Lee S, Yang J, Sankararaman S, Chaisson M, Eskin E, Mangul S. VISTA: an integrated framework for structural variant discovery.. Briefings in bioinformatics, 2024.
16. Pazokitoroudi A, Liu Z, Dahl A, Zaitlen N, Rosset S, Sankararaman S. A scalable and robust variance components method reveals insights into the architecture of gene-environment interactions underlying complex traits.. American journal of human genetics, 2024.
17. Boetto C, Frouin A, Henches L, Auvergne A, Suzuki Y, Patin E, Bredon M, Chiu A, Consortium MI, Sankararaman S, Zaitlen N, Kennedy SP, Quintana-Murci L, Duffy D, Sokol H, Aschard H. MANOCCA: a robust and computationally efficient test of covariance in high-dimension multivariate omics data.. Briefings in bioinformatics, 2024.
18. Wei A, Border R, Fu B, Cullina S, Brandes N, Jang SK, Sankararaman S, Kenny E, Udler MS, Ntranos V, Zaitlen N, Arboleda V. Investigating the sources of variable impact of pathogenic variants in monogenic metabolic conditions.. medRxiv : the preprint server for health sciences, 2024.
19. Balliu B, Douglas C, Seok D, Shenhav L, Wu Y, Chatzopoulou D, Kaiser W, Chen V, Kim J, Deverasetty S, Arnaudova I, Gibbons R, Congdon E, Craske MG, Freimer N, Halperin E, Sankararaman S, Flint J. Personalized mood prediction from patterns of behavior collected with smartphones.. NPJ digital medicine, 2024.
20. Pazokitoroudi A, Dahl A, Zaitlen N, Rosset S, Sankararaman S. A scalable and robust variance components method reveals insights into the architecture of gene-environment interactions underlying complex traits.. bioRxiv : the preprint server for biology, 2023.
21. Avram O, Durmus B, Rakocz N, Corradetti G, An U, Nitalla MG, Rudas A, Wakatsuki Y, Hirabayashi K, Velaga S, Tiosano L, Corvi F, Verma A, Karamat A, Lindenberg S, Oncel D, Almidani L, Hull V, Fasih-Ahmad S, Esmaeilkhanian H, Wykoff CC, Rahmani E, Arnold CW, Zhou B, Zaitlen N, Gronau I, Sankararaman S, Chiang JN, Sadda SR, Halperin E. SLIViT: a general AI framework for clinical-feature diagnosis from limited 3D biomedical-imaging data.. Research square, 2023.
22. An U, Pazokitoroudi A, Alvarez M, Huang L, Bacanu S, Schork AJ, Kendler K, Pajukanta P, Flint J, Zaitlen N, Cai N, Dahl A, Sankararaman S. Deep learning-based phenotype imputation on population-scale biobank data increases genetic discoveries.. Nature genetics, 2023.
23. Dahl A, Thompson M, An U, Krebs M, Appadurai V, Border R, Bacanu SA, Werge T, Flint J, Schork AJ, Sankararaman S, Kendler KS, Cai N. Phenotype integration improves power and preserves specificity in biobank-based genetic studies of major depressive disorder.. Nature genetics, 2023.
24. Fu B, Pazokitoroudi A, Xue A, Anand A, Anand P, Zaitlen N, Sankararaman S. A biobank-scale test of marginal epistasis reveals genome-wide signals of polygenic epistasis.. bioRxiv : the preprint server for biology, 2023.
25. Fu B, Pazokitoroudi A, Sudarshan M, Liu Z, Subramanian L, Sankararaman S. Fast kernel-based association testing of non-linear genetic effects for biobank-scale data.. Nature communications, 2023.
26. Dang M, Liu A, Wei X, Sankararaman S, Van den Broeck G. Tractable and Expressive Generative Models of Genetic Variation Data.. bioRxiv : the preprint server for biology, 2023.
27. LaPierre N, Fu B, Turnbull S, Eskin E, Sankararaman S. Leveraging family data to design Mendelian randomization that is provably robust to population stratification.. Genome research, 2023.
28. Hou K, Ding Y, Xu Z, Wu Y, Bhattacharya A, Mester R, Belbin GM, Buyske S, Conti DV, Darst BF, Fornage M, Gignoux C, Guo X, Haiman C, Kenny EE, Kim M, Kooperberg C, Lange L, Manichaikul A, North KE, Peters U, Rasmussen-Torvik LJ, Rich SS, Rotter JI, Wheeler HE, Wojcik GL, Zhou Y, Sankararaman S, Pasaniuc B. Causal effects on complex traits are similar for common variants across segments of different continental ancestries within admixed individuals.. Nature genetics, 2023.
29. Wei X, Robles CR, Pazokitoroudi A, Ganna A, Gusev A, Durvasula A, Gazal S, Loh PR, Reich D, Sankararaman S. The lingering effects of Neanderthal introgression on human complex traits.. eLife, 2023.
30. LaPierre N, Fu B, Turnbull S, Eskin E, Sankararaman S. Leveraging family data to design Mendelian Randomization that is provably robust to population stratification.. bioRxiv : the preprint server for biology, 2023.
31. Gorla A, Sankararaman S, Burchard E, Flint J, Zaitlen N, Rahmani E. Phenotypic subtyping via contrastive learning.. bioRxiv : the preprint server for biology, 2023.
32. Zhang X, Kim B, Singh A, Sankararaman S, Durvasula A, Lohmueller KE. MaLAdapt Reveals Novel Targets of Adaptive Introgression From Neanderthals and Denisovans in Worldwide Human Populations.. Molecular biology and evolution, 2023.
33. Zou J, Zhou J, Faller S, Brown RP, Sankararaman SS, Eskin E. Accurate modeling of replication rates in genome-wide association studies by accounting for Winner's Curse and study-specific heterogeneity.. G3 (Bethesda, Md.), 2022.
34. Border R, Athanasiadis G, Buil A, Schork AJ, Cai N, Young AI, Werge T, Flint J, Kendler KS, Sankararaman S, Dahl AW, Zaitlen NA. Cross-trait assortative mating is widespread and inflates genetic correlation estimates.. Science (New York, N.Y.), 2022.
35. Johnson R, Ding Y, Venkateswaran V, Bhattacharya A, Boulier K, Chiu A, Knyazev S, Schwarz T, Freund M, Zhan L, Burch KS, Caggiano C, Hill B, Rakocz N, Balliu B, Denny CT, Sul JH, Zaitlen N, Arboleda VA, Halperin E, Sankararaman S, Butte MJ, UCLA Precision Health Data Discovery Repository Working Group, UCLA Precision Health ATLAS Working G, Lajonchere C, Geschwind DH, Pasaniuc B. Author Correction: Leveraging genomic diversity for discovery in an electronic health record linked biobank: the UCLA ATLAS Community Health Initiative.. Genome medicine, 2022.
36. Lin H, Yu W, Suarez JED, Athavan H, Wang Y, Yeung C, Lin S, Sankararaman S, Milla C, Emaminejad S. Autonomous wearable sweat rate monitoring based on digitized microbubble detection.. Lab on a chip, 2022.
37. Johnson R, Ding Y, Venkateswaran V, Bhattacharya A, Boulier K, Chiu A, Knyazev S, Schwarz T, Freund M, Zhan L, Burch KS, Caggiano C, Hill B, Rakocz N, Balliu B, Denny CT, Sul JH, Zaitlen N, Arboleda VA, Halperin E, Sankararaman S, Butte MJ, UCLA Precision Health Data Discovery Repository Working Group, UCLA Precision Health ATLAS Working G, Lajonchere C, Geschwind DH, Pasaniuc B. Leveraging genomic diversity for discovery in an electronic health record linked biobank: the UCLA ATLAS Community Health Initiative.. Genome medicine, 2022.
38. An U, Shenhav L, Olson CA, Hsiao EY, Halperin E, Sankararaman S. STENSL: Microbial Source Tracking with ENvironment SeLection.. mSystems, 2022.
39. Thompson M, Hill BL, Rakocz N, Chiang JN, Geschwind D, Sankararaman S, Hofer I, Cannesson M, Zaitlen N, Halperin E. Methylation risk scores are associated with a collection of phenotypes within electronic health record systems.. NPJ genomic medicine, 2022.
40. Chiang JN, Corradetti G, Nittala MG, Corvi F, Rakocz N, Rudas A, Durmus B, An U, Sankararaman S, Chiu A, Halperin E, Sadda SR. Automated Identification of Incomplete and Complete Retinal Epithelial Pigment and Outer Retinal Atrophy Using Machine Learning.. Ophthalmology. Retina, 2022.
41. Coller HA, Beggs S, Andrews S, Maloy J, Chiu A, Sankararaman S, Pellegrini M, Freimer N, Johnson T, Papp J, Eskin E, Hoffmann A. Bruins-in-Genomics: Evaluation of the impact of a UCLA undergraduate summer program in computational biology on participating students.. PloS one, 2022.
42. Chiu AM, Molloy EK, Tan Z, Talwalkar A, Sankararaman S. Inferring population structure in biobank-scale genomic data.. American journal of human genetics, 2022.
43. Cinelli C, LaPierre N, Hill BL, Sankararaman S, Eskin E. Robust Mendelian randomization in the presence of residual population stratification, batch effects and horizontal pleiotropy.. Nature communications, 2022.
44. Briscoe L, Balliu B, Sankararaman S, Halperin E, Garud NR. Evaluating supervised and unsupervised background noise correction in human gut microbiome data.. PLoS computational biology, 2022.
45. Jagoda E, Xue JR, Reilly SK, Dannemann M, Racimo F, Huerta-Sanchez E, Sankararaman S, Kelso J, Pagani L, Sabeti PC, Capellini TD. Detection of Neanderthal Adaptively Introgressed Genetic Variants That Modulate Reporter Gene Expression in Human Immune Cells.. Molecular biology and evolution, 2022.
46. Ding Y, Hou K, Burch KS, Lapinska S, Privé F, Vilhjálmsson B, Sankararaman S, Pasaniuc B. Large uncertainty in individual polygenic risk score estimation impacts PRS-based risk stratification.. Nature genetics, 2021.
47. Wu Y, Burch KS, Ganna A, Pajukanta P, Pasaniuc B, Sankararaman S. Fast estimation of genetic correlation for biobank-scale data.. American journal of human genetics, 2021.
48. Johnson R, Burch KS, Hou K, Paciuc M, Pasaniuc B, Sankararaman S. Estimation of regional polygenicity from GWAS provides insights into the genetic architecture of complex traits.. PLoS computational biology, 2021.
49. Molloy EK, Durvasula A, Sankararaman S. Advancing admixture graph estimation via maximum likelihood network orientation.. Bioinformatics (Oxford, England), 2021.
50. Catav A, Fu B, Zoabi Y, Weiss-Meilik A, Shomron N, Ernst J, Sankararaman S, Gilad-Bachrach R. Marginal Contribution Feature Importance - an Axiomatic Approach for Explaining Data.. Proceedings of machine learning research, 2021.
51. Findley AS, Monziani A, Richards AL, Rhodes K, Ward MC, Kalita CA, Alazizi A, Pazokitoroudi A, Sankararaman S, Wen X, Lanfear DE, Pique-Regi R, Gilad Y, Luca F. Functional dynamic genetic effects on gene regulation are specific to particular cell types and environmental conditions.. eLife, 2021.
52. Majumdar A, Burch KS, Haldar T, Sankararaman S, Pasaniuc B, Gauderman WJ, Witte JS. A two-step approach to testing overall effect of gene-environment interaction for multiple phenotypes.. Bioinformatics (Oxford, England), 2021.
53. Pazokitoroudi A, Chiu AM, Burch KS, Pasaniuc B, Sankararaman S. Quantifying the contribution of dominance deviation effects to complex trait variation in biobank-scale data.. American journal of human genetics, 2021.
54. Sudarshan M, Puli A, Subramanian L, Sankararaman S, Ranganath R. Contra: Contrarian statistics for controlled variable selection.. Proceedings of machine learning research, 2021.
55. Rakocz N, Chiang JN, Nittala MG, Corradetti G, Tiosano L, Velaga S, Thompson M, Hill BL, Sankararaman S, Haines JL, Pericak-Vance MA, Stambolian D, Sadda SR, Halperin E. Automated identification of clinical features from sparsely annotated 3-dimensional medical imaging.. NPJ digital medicine, 2021.
56. Jew B, Li J, Sankararaman S, Sul JH. An efficient linear mixed model framework for meta-analytic association studies across multiple contexts.. Algorithms in bioinformatics : ... International Workshop, WABI ..., proceedings. WABI (Workshop), 2021.
57. Pazokitoroudi A, Wu Y, Burch KS, Hou K, Zhou A, Pasaniuc B, Sankararaman S. Efficient variance components analysis across millions of genomes.. Nature communications, 2020.
58. Sankararaman S. Methods for detecting introgressed archaic sequences.. Current opinion in genetics & development, 2020.
59. Plumb G, Terhorst J, Sankararaman S, Talwalkar A. Explaining Groups of Points in Low-Dimensional Representations.. Proceedings of machine learning research, 2020.
60. Agrawal A, Chiu AM, Le M, Halperin E, Sankararaman S. Scalable probabilistic PCA for large-scale genetic variation data.. PLoS genetics, 2020.
61. Wu Y, Eskin E, Sankararaman S. A Unifying Framework for Imputing Summary Statistics in Genome-Wide Association Studies.. Journal of computational biology : a journal of computational molecular cell biology, 2020.
62. Durvasula A, Sankararaman S. Recovering signals of ghost archaic introgression in African populations.. Science advances, 2020.
63. Hill BL, Brown R, Gabel E, Rakocz N, Lee C, Cannesson M, Baldi P, Olde Loohuis L, Johnson R, Jew B, Maoz U, Mahajan A, Sankararaman S, Hofer I, Halperin E. An automated machine learning-based model predicts postoperative mortality using readily-extractable preoperative electronic health record data.. British journal of anaesthesia, 2019.
64. Rahmani E, Schweiger R, Rhead B, Criswell LA, Barcellos LF, Eskin E, Rosset S, Sankararaman S, Halperin E. Cell-type-specific resolution epigenetics without the need for cell sorting or single-cell biology.. Nature communications, 2019.
65. Hou K, Burch KS, Majumdar A, Shi H, Mancuso N, Wu Y, Sankararaman S, Pasaniuc B. Accurate estimation of SNP-heritability from biobank-scale data irrespective of genetic architecture.. Nature genetics, 2019.
66. Durvasula A, Sankararaman S. A statistical model for reference-free inference of archaic local ancestry.. PLoS genetics, 2019.
67. Chiang CWK, Mangul S, Robles C, Sankararaman S. A Comprehensive Map of Genetic Variation in the World's Largest Ethnic Group-Han Chinese.. Molecular biology and evolution, 2018.
68. Wu Y, Sankararaman S. A scalable estimator of SNP heritability for biobank-scale data.. Bioinformatics (Oxford, England), 2018.
69. Johnson R, Shi H, Pasaniuc B, Sankararaman S. A unifying framework for joint trait analysis under a non-infinitesimal model.. Bioinformatics (Oxford, England), 2018.
70. Schumer M, Xu C, Powell DL, Durvasula A, Skov L, Holland C, Blazier JC, Sankararaman S, Andolfatto P, Rosenthal GG, Przeworski M. Natural selection interacts with recombination to shape the evolution of hybrid genomes.. Science (New York, N.Y.), 2018.
71. Jégou B, Sankararaman S, Rolland AD, Reich D, Chalmel F. Meiotic Genes Are Enriched in Regions of Reduced Archaic Ancestry.. Molecular biology and evolution, 2017.
72. Hormozdiari F, Zhu A, Kichaev G, Ju CJ, Segrè AV, Joo JWJ, Won H, Sankararaman S, Pasaniuc B, Shifman S, Eskin E. Widespread Allelic Heterogeneity in Complex Traits.. American journal of human genetics, 2017.
73. Hormozdiari F, van de Bunt M, Segrè AV, Li X, Joo JWJ, Bilow M, Sul JH, Sankararaman S, Pasaniuc B, Eskin E. Colocalization of GWAS and eQTL Signals Detects Target Genes.. American journal of human genetics, 2016.
74. Mallick S, Li H, Lipson M, Mathieson I, Gymrek M, Racimo F, Zhao M, Chennagiri N, Nordenfelt S, Tandon A, Skoglund P, Lazaridis I, Sankararaman S, Fu Q, Rohland N, Renaud G, Erlich Y, Willems T, Gallo C, Spence JP, Song YS, Poletti G, Balloux F, van Driem G, de Knijff P, Romero IG, Jha AR, Behar DM, Bravi CM, Capelli C, Hervig T, Moreno-Estrada A, Posukh OL, Balanovska E, Balanovsky O, Karachanak-Yankova S, Sahakyan H, Toncheva D, Yepiskoposyan L, Tyler-Smith C, Xue Y, Abdullah MS, Ruiz-Linares A, Beall CM, Di Rienzo A, Jeong C, Starikovskaya EB, Metspalu E, Parik J, Villems R, Henn BM, Hodoglugil U, Mahley R, Sajantila A, Stamatoyannopoulos G, Wee JT, Khusainova R, Khusnutdinova E, Litvinov S, Ayodo G, Comas D, Hammer MF, Kivisild T, Klitz W, Winkler CA, Labuda D, Bamshad M, Jorde LB, Tishkoff SA, Watkins WS, Metspalu M, Dryomov S, Sukernik R, Singh L, Thangaraj K, Pääbo S, Kelso J, Patterson N, Reich D. The Simons Genome Diversity Project: 300 genomes from 142 diverse populations.. Nature, 2016.
75. Moorjani P, Sankararaman S, Fu Q, Przeworski M, Patterson N, Reich D. A genetic method for dating ancient genomes provides a direct estimate of human generation interval in the last 45,000 years.. Proceedings of the National Academy of Sciences of the United States of America, 2016.
76. Sankararaman S, Mallick S, Patterson N, Reich D. The Combined Landscape of Denisovan and Neanderthal Ancestry in Present-Day Humans.. Current biology : CB, 2016.
77. Lipson M, Loh PR, Sankararaman S, Patterson N, Berger B, Reich D. Calibrating the Human Mutation Rate via Ancestral Recombination Density in Diploid Genomes.. PLoS genetics, 2015.
78. Palamara PF, Francioli LC, Wilton PR, Genovese G, Gusev A, Finucane HK, Sankararaman S, Genome of the Netherlands Consortium, Sunyaev SR, de Bakker PI, Wakeley J, Pe'er I, Price AL. Leveraging Distant Relatedness to Quantify Human Mutation and Gene-Conversion Rates.. American journal of human genetics, 2015.
79. Zou JY, Park DS, Burchard EG, Torgerson DG, Pino-Yanes M, Song YS, Sankararaman S, Halperin E, Zaitlen N. Genetic and socioeconomic study of mate choice in Latinos reveals novel assortment patterns.. Proceedings of the National Academy of Sciences of the United States of America, 2015.
80. Zou JY, Halperin E, Burchard E, Sankararaman S. Inferring parental genomic ancestries using pooled semi-Markov processes.. Bioinformatics (Oxford, England), 2015.
81. Racimo F, Sankararaman S, Nielsen R, Huerta-Sánchez E. Evidence for archaic adaptive introgression in humans.. Nature reviews. Genetics, 2015.
82. Zaitlen N, Pasaniuc B, Sankararaman S, Bhatia G, Zhang J, Gusev A, Young T, Tandon A, Pollack S, Vilhjálmsson BJ, Assimes TL, Berndt SI, Blot WJ, Chanock S, Franceschini N, Goodman PG, He J, Hennis AJ, Hsing A, Ingles SA, Isaacs W, Kittles RA, Klein EA, Lange LA, Nemesure B, Patterson N, Reich D, Rybicki BA, Stanford JL, Stevens VL, Strom SS, Whitsel EA, Witte JS, Xu J, Haiman C, Wilson JG, Kooperberg C, Stram D, Reiner AP, Tang H, Price AL. Leveraging population admixture to characterize the heritability of complex traits.. Nature genetics, 2014.
83. Sankararaman S, Mallick S, Dannemann M, Prüfer K, Kelso J, Pääbo S, Patterson N, Reich D. The genomic landscape of Neanderthal ancestry in present-day humans.. Nature, 2014.
84. Prüfer K, Racimo F, Patterson N, Jay F, Sankararaman S, Sawyer S, Heinze A, Renaud G, Sudmant PH, de Filippo C, Li H, Mallick S, Dannemann M, Fu Q, Kircher M, Kuhlwilm M, Lachmann M, Meyer M, Ongyerth M, Siebauer M, Theunert C, Tandon A, Moorjani P, Pickrell J, Mullikin JC, Vohr SH, Green RE, Hellmann I, Johnson PL, Blanche H, Cann H, Kitzman JO, Shendure J, Eichler EE, Lein ES, Bakken TE, Golovanova LV, Doronichev VB, Shunkov MV, Derevianko AP, Viola B, Slatkin M, Reich D, Kelso J, Pääbo S. The complete genome sequence of a Neanderthal from the Altai Mountains.. Nature, 2013.
85. Bhatia G, Patterson N, Sankararaman S, Price AL. Estimating and interpreting FST: the impact of rare variants.. Genome research, 2013.
86. Pasaniuc B, Sankararaman S, Torgerson DG, Gignoux C, Zaitlen N, Eng C, Rodriguez-Cintron W, Chapela R, Ford JG, Avila PC, Rodriguez-Santana J, Chen GK, Le Marchand L, Henderson B, Reich D, Haiman CA, Gonzàlez Burchard E, Halperin E. Analysis of Latino populations from GALA and MEC studies reveals genomic loci with biased local ancestry estimation.. Bioinformatics (Oxford, England), 2013.
87. Sankararaman S, Patterson N, Li H, Pääbo S, Reich D. The date of interbreeding between Neandertals and modern humans.. PLoS genetics, 2012.
88. Turchin MC, Chiang CW, Palmer CD, Sankararaman S, Reich D, Genetic Investigation of ANthropometric Traits (GIANT) Consortium, Hirschhorn JN. Evidence of widespread selection on standing variation in Europe at height-associated SNPs.. Nature genetics, 2012.
89. Baran Y, Pasaniuc B, Sankararaman S, Torgerson DG, Gignoux C, Eng C, Rodriguez-Cintron W, Chapela R, Ford JG, Avila PC, Rodriguez-Santana J, Burchard EG, Halperin E. Fast and accurate inference of local ancestry in Latino populations.. Bioinformatics (Oxford, England), 2012.
90. Bouchard-Côté A, Sankararaman S, Jordan MI. Phylogenetic inference via sequential Monte Carlo.. Systematic biology, 2012.
91. Hodgkinson CA, Enoch MA, Srivastava V, Cummins-Oman JS, Ferrier C, Iarikova P, Sankararaman S, Yamini G, Yuan Q, Zhou Z, Albaugh B, White KV, Shen PH, Goldman D. Genome-wide association identifies candidate genes that influence the human electroencephalogram.. Proceedings of the National Academy of Sciences of the United States of America, 2010.
92. Sankararaman S, Sha F, Kirsch JF, Jordan MI, Sjölander K. Active site prediction using evolutionary and structural information.. Bioinformatics (Oxford, England), 2010.
93. Sankararaman S, Obozinski G, Jordan MI, Halperin E. Genomic privacy and limits of individual detection in a pool.. Nature genetics, 2009.
94. Alterovitz R, Arvey A, Sankararaman S, Dallett C, Freund Y, Sjölander K. ResBoost: characterizing and predicting catalytic residues in enzymes.. BMC bioinformatics, 2009.
95. Pasaniuc B, Sankararaman S, Kimmel G, Halperin E. Inference of locus-specific ancestry in closely related populations.. Bioinformatics (Oxford, England), 2009.
96. Sankararaman S, Kolaczkowski B, Sjölander K. INTREPID: a web server for prediction of functionally important residues by evolutionary analysis.. Nucleic acids research, 2009.
97. Sankararaman S, Sjölander K. INTREPID--INformation-theoretic TREe traversal for Protein functional site IDentification.. Bioinformatics (Oxford, England), 2008.
98. Skibola CF, Bracci PM, Halperin E, Nieters A, Hubbard A, Paynter RA, Skibola DR, Agana L, Becker N, Tressler P, Forrest MS, Sankararaman S, Conde L, Holly EA, Smith MT. Polymorphisms in the estrogen receptor 1 and vitamin C and matrix metalloproteinase gene families are associated with susceptibility to lymphoma.. PloS one, 2008.
99. Sankararaman S, Kimmel G, Halperin E, Jordan MI. On the inference of ancestries in admixed populations.. Genome research, 2008.
100. Sankararaman S, Sridhar S, Kimmel G, Halperin E. Estimating local ancestry in admixed populations.. American journal of human genetics, 2008.