Warren Kibbe

Overview:

Warren A. Kibbe, PhD, is chief for Translational Biomedical Informatics in the Department of Biostatistics and Bioinformatics and Chief Data Officer for the Duke Cancer Institute. He joined the Duke University School of Medicine in August after serving as the acting deputy director of the National Cancer Institute (NCI) and director of the NCI’s Center for Biomedical Informatics and Information Technology where he oversaw 60 federal employees and more than 600 contractors, and served as an acting Deputy Director for NCI. As an acting Deputy Director, Dr. Kibbe was involved in the myriad of activities that NCI oversees as a research organization, as a convening body for cancer research, and as a major funder of cancer research, funding nearly $4B US annually in cancer research throughout the United States. 

Positions:

Professor in Biostatistics and Bioinformatics

Biostatistics & Bioinformatics
School of Medicine

Chief, Division of Translational Biomedical Informatics

Biostatistics & Bioinformatics
School of Medicine

Chief Data Officer, DCI

Biostatistics & Bioinformatics
School of Medicine

Member of the Duke Cancer Institute

Duke Cancer Institute
School of Medicine

Education:

Ph.D. 1990

California Institute of Technology

Publications:

Defining the role of common variation in the genomic and biological architecture of adult human height.

Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.
Authors
Wood, AR; Esko, T; Yang, J; Vedantam, S; Pers, TH; Gustafsson, S; Chu, AY; Estrada, K; Luan, J; Kutalik, Z; Amin, N; Buchkovich, ML; Croteau-Chonka, DC; Day, FR; Duan, Y; Fall, T; Fehrmann, R; Ferreira, T; Jackson, AU; Karjalainen, J; Lo, KS; Locke, AE; Mägi, R; Mihailov, E; Porcu, E; Randall, JC; Scherag, A; Vinkhuyzen, AAE; Westra, H-J; Winkler, TW; Workalemahu, T; Zhao, JH; Absher, D; Albrecht, E; Anderson, D; Baron, J; Beekman, M; Demirkan, A; Ehret, GB; Feenstra, B; Feitosa, MF; Fischer, K; Fraser, RM; Goel, A; Gong, J; Justice, AE; Kanoni, S; Kleber, ME; Kristiansson, K; Lim, U; Lotay, V; Lui, JC; Mangino, M; Mateo Leach, I; Medina-Gomez, C; Nalls, MA; Nyholt, DR; Palmer, CD; Pasko, D; Pechlivanis, S; Prokopenko, I; Ried, JS; Ripke, S; Shungin, D; Stancáková, A; Strawbridge, RJ; Sung, YJ; Tanaka, T; Teumer, A; Trompet, S; van der Laan, SW; van Setten, J; Van Vliet-Ostaptchouk, JV; Wang, Z; Yengo, L; Zhang, W; Afzal, U; Arnlöv, J; Arscott, GM; Bandinelli, S; Barrett, A; Bellis, C; Bennett, AJ; Berne, C; Blüher, M; Bolton, JL; Böttcher, Y; Boyd, HA; Bruinenberg, M; Buckley, BM; Buyske, S; Caspersen, IH; Chines, PS; Clarke, R; Claudi-Boehm, S; Cooper, M; Daw, EW; De Jong, PA; Deelen, J; Delgado, G; Denny, JC; Dhonukshe-Rutten, R; Dimitriou, M; Doney, ASF; Dörr, M; Eklund, N; Eury, E; Folkersen, L; Garcia, ME; Geller, F; Giedraitis, V; Go, AS; Grallert, H; Grammer, TB; Gräßler, J; Grönberg, H; de Groot, LCPGM; Groves, CJ; Haessler, J; Hall, P; Haller, T; Hallmans, G; Hannemann, A; Hartman, CA; Hassinen, M; Hayward, C; Heard-Costa, NL; Helmer, Q; Hemani, G; Henders, AK; Hillege, HL; Hlatky, MA; Hoffmann, W; Hoffmann, P; Holmen, O; Houwing-Duistermaat, JJ; Illig, T; Isaacs, A; James, AL; Jeff, J; Johansen, B; Johansson, Å; Jolley, J; Juliusdottir, T; Junttila, J; Kho, AN; Kinnunen, L; Klopp, N; Kocher, T; Kratzer, W; Lichtner, P; Lind, L; Lindström, J; Lobbens, S; Lorentzon, M; Lu, Y; Lyssenko, V; Magnusson, PKE; Mahajan, A; Maillard, M; McArdle, WL; McKenzie, CA; McLachlan, S; McLaren, PJ; Menni, C; Merger, S; Milani, L; Moayyeri, A; Monda, KL; Morken, MA; Müller, G; Müller-Nurasyid, M; Musk, AW; Narisu, N; Nauck, M; Nolte, IM; Nöthen, MM; Oozageer, L; Pilz, S; Rayner, NW; Renstrom, F; Robertson, NR; Rose, LM; Roussel, R; Sanna, S; Scharnagl, H; Scholtens, S; Schumacher, FR; Schunkert, H; Scott, RA; Sehmi, J; Seufferlein, T; Shi, J; Silventoinen, K; Smit, JH; Smith, AV; Smolonska, J; Stanton, AV; Stirrups, K; Stott, DJ; Stringham, HM; Sundström, J; Swertz, MA; Syvänen, A-C; Tayo, BO; Thorleifsson, G; Tyrer, JP; van Dijk, S; van Schoor, NM; van der Velde, N; van Heemst, D; van Oort, FVA; Vermeulen, SH; Verweij, N; Vonk, JM; Waite, LL; Waldenberger, M; Wennauer, R; Wilkens, LR; Willenborg, C; Wilsgaard, T; Wojczynski, MK; Wong, A; Wright, AF; Zhang, Q; Arveiler, D; Bakker, SJL; Beilby, J; Bergman, RN; Bergmann, S; Biffar, R; Blangero, J; Boomsma, DI; Bornstein, SR; Bovet, P; Brambilla, P; Brown, MJ; Campbell, H; Caulfield, MJ; Chakravarti, A; Collins, R; Collins, FS; Crawford, DC; Cupples, LA; Danesh, J; de Faire, U; den Ruijter, HM; Erbel, R; Erdmann, J; Eriksson, JG; Farrall, M; Ferrannini, E; Ferrières, J; Ford, I; Forouhi, NG; Forrester, T; Gansevoort, RT; Gejman, PV; Gieger, C; Golay, A; Gottesman, O; Gudnason, V; Gyllensten, U; Haas, DW; Hall, AS; Harris, TB; Hattersley, AT; Heath, AC; Hengstenberg, C; Hicks, AA; Hindorff, LA; Hingorani, AD; Hofman, A; Hovingh, GK; Humphries, SE; Hunt, SC; Hypponen, E; Jacobs, KB; Jarvelin, M-R; Jousilahti, P; Jula, AM; Kaprio, J; Kastelein, JJP; Kayser, M; Kee, F; Keinanen-Kiukaanniemi, SM; Kiemeney, LA; Kooner, JS; Kooperberg, C; Koskinen, S; Kovacs, P; Kraja, AT; Kumari, M; Kuusisto, J; Lakka, TA; Langenberg, C; Le Marchand, L; Lehtimäki, T; Lupoli, S; Madden, PAF; Männistö, S; Manunta, P; Marette, A; Matise, TC; McKnight, B; Meitinger, T; Moll, FL; Montgomery, GW; Morris, AD; Morris, AP; Murray, JC; Nelis, M; Ohlsson, C; Oldehinkel, AJ; Ong, KK; Ouwehand, WH; Pasterkamp, G; Peters, A; Pramstaller, PP; Price, JF; Qi, L; Raitakari, OT; Rankinen, T; Rao, DC; Rice, TK; Ritchie, M; Rudan, I; Salomaa, V; Samani, NJ; Saramies, J; Sarzynski, MA; Schwarz, PEH; Sebert, S; Sever, P; Shuldiner, AR; Sinisalo, J; Steinthorsdottir, V; Stolk, RP; Tardif, J-C; Tönjes, A; Tremblay, A; Tremoli, E; Virtamo, J; Vohl, M-C; Electronic Medical Records and Genomics (eMEMERGEGE) Consortium,; MIGen Consortium,; PAGEGE Consortium,; LifeLines Cohort Study,; Amouyel, P; Asselbergs, FW; Assimes, TL; Bochud, M; Boehm, BO; Boerwinkle, E; Bottinger, EP; Bouchard, C; Cauchi, S; Chambers, JC; Chanock, SJ; Cooper, RS; de Bakker, PIW; Dedoussis, G; Ferrucci, L; Franks, PW; Froguel, P; Groop, LC; Haiman, CA; Hamsten, A; Hayes, MG; Hui, J; Hunter, DJ; Hveem, K; Jukema, JW; Kaplan, RC; Kivimaki, M; Kuh, D; Laakso, M; Liu, Y; Martin, NG; März, W; Melbye, M; Moebus, S; Munroe, PB; Njølstad, I; Oostra, BA; Palmer, CNA; Pedersen, NL; Perola, M; Pérusse, L; Peters, U; Powell, JE; Power, C; Quertermous, T; Rauramaa, R; Reinmaa, E; Ridker, PM; Rivadeneira, F; Rotter, JI; Saaristo, TE; Saleheen, D; Schlessinger, D; Slagboom, PE; Snieder, H; Spector, TD; Strauch, K; Stumvoll, M; Tuomilehto, J; Uusitupa, M; van der Harst, P; Völzke, H; Walker, M; Wareham, NJ; Watkins, H; Wichmann, H-E; Wilson, JF; Zanen, P; Deloukas, P; Heid, IM; Lindgren, CM; Mohlke, KL; Speliotes, EK; Thorsteinsdottir, U; Barroso, I; Fox, CS; North, KE; Strachan, DP; Beckmann, JS; Berndt, SI; Boehnke, M; Borecki, IB; McCarthy, MI; Metspalu, A; Stefansson, K; Uitterlinden, AG; van Duijn, CM; Franke, L; Willer, CJ; Price, AL; Lettre, G; Loos, RJF; Weedon, MN; Ingelsson, E; O'Connell, JR; Abecasis, GR; Chasman, DI; Goddard, ME; Visscher, PM; Hirschhorn, JN; Frayling, TM
MLA Citation
Wood, Andrew R., et al. “Defining the role of common variation in the genomic and biological architecture of adult human height..” Nat Genet, vol. 46, no. 11, Nov. 2014, pp. 1173–86. Pubmed, doi:10.1038/ng.3097.
URI
https://scholars.duke.edu/individual/pub1236717
PMID
25282103
Source
pubmed
Published In
Nat Genet
Volume
46
Published Date
Start Page
1173
End Page
1186
DOI
10.1038/ng.3097

Introduction

Authors
Fleming, M; Bresler, L; O'Toole, J
MLA Citation
Fleming, M., et al. Introduction. 2015, pp. 1–6.
URI
https://scholars.duke.edu/individual/pub1253888
Source
scopus
Published Date
Start Page
1
End Page
6

Using the bioconductor GeneAnswers package to interpret gene lists.

Use of microarray data to generate expression profiles of genes associated with disease can aid in identification of markers of disease and potential therapeutic targets. Pathway analysis methods further extend expression profiling by creating inferred networks that provide an interpretable structure of the gene list and visualize gene interactions. This chapter describes GeneAnswers, a novel gene-concept network analysis tool available as an open source Bioconductor package. GeneAnswers creates a gene-concept network and also can be used to build protein-protein interaction networks. The package includes an example multiple myeloma cell line dataset and tutorial. Several network analysis methods are included in GeneAnswers, and the tutorial highlights the conditions under which each type of analysis is most beneficial and provides sample code.
Authors
Feng, G; Shaw, P; Rosen, ST; Lin, SM; Kibbe, WA
MLA Citation
Feng, Gang, et al. “Using the bioconductor GeneAnswers package to interpret gene lists..” Methods Mol Biol, vol. 802, 2012, pp. 101–12. Pubmed, doi:10.1007/978-1-61779-400-1_7.
URI
https://scholars.duke.edu/individual/pub1276710
PMID
22130876
Source
pubmed
Published In
Methods Mol Biol
Volume
802
Published Date
Start Page
101
End Page
112
DOI
10.1007/978-1-61779-400-1_7

A divide-and-conquer strategy to solve the out-of-memory problem of processing thousands of Affymetrix microarrays.

Out-of-memory problem was frequently encountered when processing thousands of CEL files using Bioconductor. We propose a divide-and-conquer strategy combined with randomised resampling to solve this problem. The CAMDA 2007 META-analysis data set which contains 5896 CEL files was used to test the approach on a typical commodity computer cluster by running established pre-processing algorithms for Affymetrix arrays in the Bioconductor package. The results were validated against a golden standard obtained by using a supercomputer. In addition to the performance improvement, the general divide-and-conquer strategy can be applied to any other normalisation algorithms without modifying the underlying implementation.
Authors
Lee, C-J; Fu, D; Du, P; Jiang, H; Lin, SM; Kibbe, W
MLA Citation
Lee, Chia-Ju, et al. “A divide-and-conquer strategy to solve the out-of-memory problem of processing thousands of Affymetrix microarrays..” Int J Comput Biol Drug Des, vol. 1, no. 4, 2008, pp. 396–405. Pubmed, doi:10.1504/ijcbdd.2008.022209.
URI
https://scholars.duke.edu/individual/pub1278277
PMID
20063464
Source
pubmed
Published In
International Journal of Computational Biology and Drug Design
Volume
1
Published Date
Start Page
396
End Page
405
DOI
10.1504/ijcbdd.2008.022209

dictyBase, the model organism database for Dictyostelium discoideum.

dictyBase (http://dictybase.org) is the model organism database (MOD) for the social amoeba Dictyostelium discoideum. The unique biology and phylogenetic position of Dictyostelium offer a great opportunity to gain knowledge of processes not characterized in other organisms. The recent completion of the 34 MB genome sequence, together with the sizable scientific literature using Dictyostelium as a research organism, provided the necessary tools to create a well-annotated genome. dictyBase has leveraged software developed by the Saccharomyces Genome Database and the Generic Model Organism Database project. This has reduced the time required to develop a full-featured MOD and greatly facilitated our ability to focus on annotation and providing new functionality. We hope that manual curation of the Dictyostelium genome will facilitate the annotation of other genomes.
Authors
Chisholm, RL; Gaudet, P; Just, EM; Pilcher, KE; Fey, P; Merchant, SN; Kibbe, WA
MLA Citation
Chisholm, R. L., et al. “dictyBase, the model organism database for Dictyostelium discoideum..” Nucleic Acids Research, vol. 34, no. Database issue, Jan. 2006.
URI
https://scholars.duke.edu/individual/pub1278284
Source
scopus
Published In
Nucleic Acids Res
Volume
34
Published Date

Research Areas:

Bioinformatics
Clinical medicine--Research
Informatics
Medical Informatics
Software
Software Design
Software Validation