Seven Bridges Publications

Goran Rakocevic, Vladimir Semenyuk, Wan-Ping Lee, James Spencer, John Browning, Ivan J. Johnson, Vladan Arsenijevic, Jelena Nadj, Kaushik Ghose, Maria C. Suciu, Sun-Gou Ji, Gülfem Demir, Lizao Li, Berke Ç. Toptaş, Alexey Dolgoborodov, Björn Pollex, Iosif Spulber, Irina Glotova, Péter Kómár, Andrew L. Stachyra, Yilong Li, Milos Popovic, Morten Källberg, Amit Jain and Deniz Kural
Nature Genetics (2019) 51 (354–362) doi: https://doi.org/10.1038/s41588-018-0316-4

Initial publication of our graph-based tool set for genomic data analysis. Furthering the pan-genome paradigm using a sequence variation graph representation of genome variation.

Gil Alterovitz, Dennis Dean, Carole Goble, Michael R. Crusoe, Stian Soiland-Reyes, Amanda Bell, Anais Hayes, Anita Suresh, Anjan Purkayastha, Charles H. King, Dan Taylor, Elaine Johanson, Elaine E. Thompson, Eric Donaldson, Hiroki Morizono, Hsinyi Tsang, Jeet K. Vora, Jeremy Goecks, Jianchao Yao, Jonas S. Almeida, Jonathon Keeney, KanakaDurga Addepalli, Konstantinos Krampis, Krista M. Smith, Lydia Guo, Mark Walderhaug, Marco Schito, Matthew Ezewudo, Nuria Guimera, Paul Walsh, Robel Kahsay, Srikanth Gottipati, Timothy C. Rodwell, Toby Bloom, Yuching Lai, Vahan Simonyan, Raja Mazumder
PLoS Biology (December 31, 2018) doi: https://doi.org/10.1371/journal.pbio.3000099

A personalized approach based on a patient’s or pathogen’s unique genomic sequence is the foundation of precision medicine.

Stephan Beck, Alison M Berner, Graham Bignell, Maggie Bond, Martin J Callanan, Olga Chervova, Lucia Conde, Manuel Corpas, Simone Ecker, Hannah R Elliott, Silvana A Fioramonti, Adrienne M Flanagan, Ricarda Gaentzsch, Elizabeth H. Williams, David Graham, Deirdre Gribbin, Jose Afonso Guerra-Assuncao, Rifat Hamoudi, Vincent Harding, Paul L Harrison, Javier Herrero, Jana Hofmann, Erica Jones, Saif Khan, Jane Kaye, Polly Kerr, Emanuele Libertini, Laura McCormack, Ismail Moghul, Nikolas Pontikos, Sharmini Rajanayagam, Kirti Rana, Momodou Semega-Janneh, Colin P Smith, Louise Strom, Sevgi Urmur, Amy P Webster, Karen Wint, John N Wood
BMC Medical Genomics (27 November 2018) 11: 108 doi: 10.1186/s12920-018-0423-1

Yang Liu, Qianchan He, Wei Sun
PLoS Genetics (2 November 2018) doi: https://doi.org/10.1371/journal.pgen.1007746

Xavier Bofill-De Ros, Kevin Chen, Susanna Chen, Nikola Tesic, Dusan Randjelovic, Nikola Skundric, Svetozar Nesic, Vojislav Varjacic, Elizabeth H. Williams, Raunaq Malhotra, Minjie Jiang, Shuo Gu
Bioinformatics (8 Oct 2018) doi: 10.1093/bioinformatics/bty843

Cejovic J, Radenkovic J, Mladenovic V, Stanojevic A, Miletic M, Radanovic S, Bajcic D, Djordjevic D, Jelic F, Nesic M, Lau J, Grady P, Groves-Kirkby N, Kural D, Davis-Dusenbery B
Cancer Informatics (28 Sept 2018) doi: 10.1177/1176935118774787

This paper describes a Semantic-Web-based Data Browser for the Cancer Genomics Cloud, which allows users to visually build and execute ontology-driven queries, improving data access and usability.

Vesteinn Thorsson, David L. Gibbs, Scott D. Brown, Denise Wolf, Dante S. Bortone, Tai-Hsien Ou Yang, Eduard Porta Pardo, Galen Gao, Christopher L. Plaisier, James A. Eddy, Elad Ziv, Aedin C. Culhane, Evan O. Paull, I.K. Ashok Sivakumar, Andrew J. Gentles, Raunaq Malhotra, Farshad Farshidfar, Antonio Colaprico, Joel S. Parker, Lisle E. Mose, Nam Sy Vo, Jianfang Liu, Yuexin Liu, Janet Rader, Varsha Dhankani, Sheila M. Reynolds, Reanne Bowlby, Andrea Califano, Andrew D. Cherniack, Dimitris Anastassiou, Davide Bedognetti, Arvind Rao, Ken Chen, Alexander Krasnitz, Hai Hu, Tathiane M. Malta, Houtan Noushmehr, Chandra Sekhar Pedamallu, Susan Bullman, Akinyemi I. Ojesina, Andrew Lamb, Wanding Zhou, Hui Shen, Toni K. Choueiri, John N. Weinstein, Justin Guinney, Joel Saltz, Robert A. Holt, Charles E. Rabkin, The Cancer Genome Atlas Research Network, Alex J. Lazar, Jonathan S. Serody, Elizabeth G. Demicco, Mary L. Disis, Benjamin Vincent, llya Shmulevich
Immunity 48 (4) (5 Apr 2018) doi: 10.1016/j.immuni.2018.03.023

Lau JW, Lehnert E, Sethi A, Malhotra R, Kaushik G, Onder Z, Groves-Kirkby N, Mihajlovic A, DiGiovanna J, Srdic M, Bajcic D, Radenkovic J, Mladenovic V, Krstanovic D, Arsenijevic V, Klisic D, Mitrovic M, Bogicevic I, Kural D, Davis-Dusenbery B; for The Seven Bridges CGC Team
Cancer Research (2017) 77 (21): e3–6. doi: 10.1158/0008-5472.CAN-17-0387

This publication describes the Seven Bridges Cancer Genomics Cloud, a cloud-based system that enables researchers to rapidly access and collaborate on massive public cancer genomics datasets, including The Cancer Genome Atlas.

Grossman RL, Abel B, Angiuoli S, Barrett JC, Bassett D, Bramlett K, Blumenthal GM, Carlsson A, Cortese R, DiGiovanna J, Davis-Dusenbery B, Dittamore R, Eberhard DA, Febbo P, Fitzsimons M, Flamig Z, Godsey J, Goswami J, Gruen A, Ortuño F, Han J, Hayes D, Hicks J, Holloway D, Hovelson D, Johnson J, Juhl H, Kalamegham R, Kamal R, Kang Q, Kelloff GJ, Klozenbuecher M, Kolatkar A, Kuhn P, Langone K, Leary R, Loverso P, Manmathan H, Martin A-M, Martini J, Miller D, Mitchell M, Morgan T, Mulpuri R, Nguyen T, Otto G, Pathak A, Peters E, Philip R, Posadas E, Reese D, Reese MG, Robinson D, Dei Rossi A, Sakul H, Schageman J, Singh S, Scher HI, Schmitt K, Silvestro A, Simmons J, Simmons T, Sislow J, Talasaz A, Tang P, Tewari M, Tomlins S, Toukhy H, Tseng HR, Tuck M, Tzou A, Vinson J, Wang Y, Wells W, Welsh A, Wilbanks J, Wolf J, Young L, Lee JSH, Leiman LC
Clin Pharmacol Ther (2017) 101 (5): 589–592. doi: 10.1002/cpt.666

This article introduces the The Blood Profiling Atlas in Cancer (BloodPAC), which works to harmonize and make available data, to accelerate the development of minimally invasive blood profiling assays for cancer assessment and monitoring.

Yung CK, O’Connor BD, Yakneen S, Zhang J, Ellrott K, Kleinheinz K, Miyoshi N, Raine KM, Royo R, Saksena GB, Schlesner M, Shorser SI, Vazquez M, Weischenfeldt J, Yuen D, Butler AP, Davis-Dusenbery BN, Eils R, Ferretti V, Grossman RL, Harismendy O, Kim Y, Nakagawa H, Newhouse SJ, Torrents D, Stein LD; PCAWG Technical Working Group
bioRxiv 161638; doi: https://doi.org/10.1101/161638

This preprint describes Seven Bridges’ role as part of the PCAWG Technical Working Group to generate high-quality validated consensus variants, forming the basis of the highest resolution collection of cancer genomes to date.

Kaushik G, Ivkovic S, Simonovic J, Tijanic N, Davis-Dusenbery B, Kural D
Pac Symp Biocomput (2016) 22: 154–165

This paper describes the Rabix Executor, an open-source workflow engine designed to improve computational reproducibility through reusability and interoperability of workflow descriptions.

Arsenijevic V, Davis-Dusenbery BN
Methods Mol Biol (2016) 1381: 223–237. doi: 10.1007/978-1-4939-3204-7_13

This chapter describes an approach to leverage cloud computing technology for fusion detection from RNA-sequencing data at any scale.

Diermeier SD, Chang KC, Freier SM, Song J, El Demerdash O, Krasnitz A,
Rigo F, Bennett CF, Spector D
Cell Rep (2016) 17 (1): 261–274. doi: 10.1016/j.celrep.2016.08.081

Collado-Torres L, Nellore A, Kammers K, Ellis SE, Taub MA, Hansen KD,
Jaffe AE, Langmead B, Leek JT
Nat Biotechnol (2017) 35 (4): 319–321. doi: 10.1038/nbt.3838

Hsinyi Tsang, Sean Davis
https://f1000research.com/posters/6-163

Bhuvaneshwar K, Al Hossiny M, Gusev Y, Madhavan S,
Upadhyay G
In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017
Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr
3568. doi:10.1158/1538-7445.AM2017-3568

Bais P, Namburi S, Gatti DM, Zhang X, Chuang JH
Bioinformatics (2017) 33 (19): 3110–3112. doi: 10.1093/bioinformatics/btx375

Jack DiGiovanna. Keynote. Festival of Genomics Boston 2016

Brandi Davis-Dusenbery. AACR 2017

Gaurav Kaushik. ASHG 2016

Jack DiGiovanna. Keystone Symposia: Cancer Immunology and Immunotherapy 2017

Deniz Kural. Festival of Genomics, London 2017

Deniz Kural. Keynote. Proventa Bioinformatics 2016

Vladimir Kovacevic. ISMB/ECCB 2017

Davis-Dusenbery B
GEN (2017) 37 (2): January 15

In this article, Seven Bridges CEO Brandi Davis-Dusenbery explains how the volume of NGS data gathered by massive genomics projects is driving a fundamental rethinking of data management and analysis methods.

Stephens ZD, Lee SY, Faghri F, Campbell RH, Zhai C, Efron MJ, Iyer R, Schatz MC, Sinha S, Robinson GE
PLoS Biology (2015) 13 (7): e1002195. doi: 10.1371/journal.pbio.1002195

This paper shows how genomics is on par with astronomy, YouTube, and Twitter in terms of data acquisition, storage, distribution and analysis, and how new technologies are needed to meet these computational challenges.

Lawrence MS, Stojanov P, Mermel CH, Robinson JT, Garraway LA, Golub TR, Meyerson M, Gabriel SB, Lander ES, Getz G
Nature (2014) 505 (7484): 495–501. doi: 10.1038/nature12912

This paper illustrates how large-scale genomic analysis contributes to identifying cancer genes across multiple tumor types.

Stein LD, Knoppers BM, Campbell P, Getz G, Korbel JO
Nature (2015) 523 (7559): 149–151. doi: 10.1038/523149a

This paper sets out the benefits of making large biological data sets available via cloud services to enable easy access and fast analysis.

Novak AM, Hickey G, Garrison E, Blum S, Connelly A, Dilthey A, Eizenga J, Elmohamed MAS, Guthrie S, Kahles A, Keenan S, Kelleher J, Kural D, Li H, Lin MF, Miga K, Ouyang N, Rakocevic G, Smuga-Otto M, Zaranek AW, Durbin R, McVean G, Haussler D, Paten B
bioRxiv 101378; doi: https://doi.org/10.1101/101378

This preprint from leaders in graph genome research discusses how representing variation as part of a directed acyclic graph-based reference structure can reduce reference bias and improve the accuracy of alignment and variant calling.

Nelson MR, Tipney H, Painter JL, Shen J, Nicoletti P, Shen Y, Floratos A, Sham PC, Li MJ, Wang J, Cardon LR, Whittaker JC, Sanseau P
Nat Genet (2015) 47: 856–860. doi: 10.1038/ng.3314

This article, led by researchers at GlaxoSmithKline, shows how obtaining genetic support for targets can double the success rate in clinical development.

Finan C, Gaulton A, Kruger FA, Lumbers RT, Shah T, Engmann J, Galver L, Kelley R, Karlsson A, Santos R, Overington JP, Hingorani AD, Casas JP
Sci Translat Med (2017) 9: eaag1166. doi:10.1126/scitranslmed.aag1166

In this paper, researchers from University College London combine data from numerous existing genome-wide association studies to identify and connect druggable proteins and known drugs across multiple diseases, facilitating the design of new targeted therapeutics.