Publications

The following published manuscripts report work completed using the Cancer Genomics Cloud. Additionally, many manuscripts listed below have directly cited our CGC flagship paper:

Lau, Jessica W., et al. "The Cancer Genomics Cloud: collaborative, reproducible, and democratized—a new paradigm in large-scale computational research." Cancer Res. 77.21 (2017): e3-e6.

The list below is presented in reverse-chronological order and will be updated on a monthly basis with the latest publications.

  1. Bardadym, T. O., Gorbachuk, V. М., & Novoselova, N. А. (n.d.). Intelligent Analytical System as a Tool to Ensure the Reproducibility of Biomedical Calculations. Retrieved February 22, 2021.

  2. Bartha, Á., & Gyorffy, B. (n.d.). Whole Exome Sequencing Data Analysis Algorithms in Cancer Diagnostics. Videleaf.com.

  3. Bhattacharya, S., Hu, Z., & Butte, A. J. (2021). Opportunities and Challenges in Democratizing Immunology Datasets. Frontiers in Immunology, 12, 647536.

  4. Ahmed, A. E., Allen, J., Bhat, T., Burra, P., Fliege, C. E., Hart, S. N., Heldenbrand, J. R., Istanto, D. D., Hudson, M. E., Kalmbach, M. T., Kapraun, et al (2021). Design considerations for workflow management systems use in production genomics research and the clinic. In bioRxiv (p. 2021.04.03.437906).

  5. Patel, J. A., Dean, D. A., King, C. H., Xiao, N., Koc, S., Minina, E., Golikov, A., Brooks, P., Kahsay, R., Navelkar, R., Ray, M., Roberson, D., Armstrong, C., Mazumder, R., & Keeney, J. (2021) Bioinformatics tools developed to support BioCompute Objects. Database: The Journal of Biological Databases and Curation, 2021.

  6. Guillen, K. P., Fujita, M., Butterfield, A. J., Scherer, S. D., Bailey, M. H., Chu, Z., DeRose, Y. S., Zhao, L., Cortes-Sanchez, E., Yang, C.-H., Toner, J., Wang, G., Qiao, Y., Huang, X., Greenland, J. A., Vahrenkamp, J. M., Lum, D. H., Factor, R. E., Nelson, E. W., … Welm, A. L. (2021). A breast cancer patient-derived xenograft and organoid platform for drug discovery and precision oncology. In Cold Spring Harbor Laboratory (p. 2021.02.28.433268).

  7. Canbezdi, C., Tarin, M., Houy, A., Bellanger, D., Popova, T., Stern, M.-H., Roman-Roman, S., & Alsafadi, S. (2021). Functional and conformational impact of cancer-associated SF3B1 mutations depends on the position and the charge of amino acid substitution. Computational and Structural Biotechnology Journal.

  8. Zhao, Y., Fang, L. T., Shen, T.-W., Choudhari, S., Talsania, K., Chen, X., Shetty, J., Kriga, Y., Tran, B., Zhu, B., Chen, Z., Chen, W., Wang, C., Jaeger, E., Meerzaman, D., Lu, C., Idler, K., Zheng, Y., Shi, L., … Xiao, W. (2021). Whole Genome and Exome Sequencing Reference Datasets from A Multi-center and Cross-platform Benchmark Study. In Cold Spring Harbor Laboratory (p. 2021.02.27.433136).

  9. Bernasconi, A., Canakoglu, A., Masseroli, M., & Ceri, S. (2021). The road towards data integration in human genomics: players, steps and interactions. Briefings in Bioinformatics, 22(1), 30–44. https://doi.org/10.1093/bib/bbaa080

  10. Böck, J., Krogsaeter, E., Passon, M., Chao, Y.-K., Sharma, S., Grallert, H., Peters, A., & Grimm, C. (2021). Human genome diversity data reveal that L564P is the predominant TPC2 variant and a prerequisite for the blond hair associated M484L gain-of-function effect. PLoS Genetics, 17(1), e1009236. https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1009236

  11. Keskus, A. G., Tombaz, M., Arici, B. I., Dincaslan, F. B., Nabi, A., Shehwana, H., & Konu, O. (2020). ace2 expression is higher in intestines and liver while being tightly regulated in development and disease in zebrafish. In Cold Spring Harbor Laboratory (p. 2020.12.24.424209).

  12. Drljaca, T., Zukic, B., Kovacevic, V., Gemovic, B., Klaassen-Ljubicic, K., Perovic, V., Lazarevic, M., Pavlovic, S., & Veljkovic, N. (2020). The first insight into the genetic structure of the population of modern Serbia. In Cold Spring Harbor Laboratory (p. 2020.12.18.423408).

  13. Zayas, R., Sisson, A., Kuhnsman, A., Nagalo, B. M., Roberts, L. R., & Buetow, K. (2020). Transcriptional Landscape of Hepatocellular Carcinoma Reveals that Patient Ethnic-Origin Influences Patterns of Expression. In Cold Spring Harbor Laboratory (p. 2020.12.01.404285).

  14. Stephens, S. H., King, C. H., Watford, S., Patel, J., Dean, D. A., Koc, S., Xiao, N., Donaldson, E. F., Thompson, E. E., Purkayastha, A., Mazumder, R., Johanson, E., & Keeney, J. (2020). Strengthening the BioCompute Standard by Crowdsourcing on PrecisionFDA. In Cold Spring Harbor Laboratory (p. 2020.11.02.365528).

  15. Dai, L., Hallmark, L., Bofill De Ros, X., Crouch, H., Chen, S., Shi, T., Yang, A., Lian, C., Zhao, Y., Tran, B., & Gu, S. (2020). Novel, abundant Drosha isoforms are deficient in miRNA processing in cancer cells. RNA Biology, 17(11), 1603–1612. https://doi.org/10.1080/15476286.2020.1813439

  16. Alsafadi, S., Dayot, S., Tarin, M., Houy, A., Bellanger, D., Cornella, M., Wassef, M., Waterfall, J. J., Lehnert, E., Roman-Roman, S., Stern, M.-H., & Popova, T. (2020). Genetic alterations of SUGP1 mimic mutant-SF3B1 splice pattern in lung adenocarcinoma and other cancers. Oncogene.

  17. Xiao, N., Koc, S., Roberson, D., Brooks, P., Ray, M., & Dean, D. (2020). BCO App: tools for generating BioCompute Objects from next-generation sequencing workflows and computations. F1000Research, 9(1144), 1144. https://doi.org/10.12688/f1000research.25902.1

  18. Cappelli, E., Cumbo, F., Bernasconi, A., Canakoglu, A., Ceri, S., Masseroli, M., & Weitschek, E. (2020). OpenGDC: Unifying, Modeling, Integrating Cancer Genomic Data and Clinical Metadata. NATO Advanced Science Institutes Series E: Applied Sciences, 10(18), 6367. https://doi.org/10.3390/app10186367

  19. Vucic, N., Ray, M., Veljkovic, D., Cidilko, S., & Davis-Dusenbery, B. (2020). Abstract 4414: Single-cell analysis on the Cancer Genomics Cloud reveals changes in the transcriptome profiles of endothelial tumor cells over time - novel insights from a public dataset of a mouse model of melanoma. Cancer Research, 80(16 Supplement), 4414–4414. https://doi.org/10.1158/1538-7445.AM2020-4414

  20. Krissaane, I., De Niz, C., Gutiérrez-Sacristán, A., Korodi, G., Ede, N., Kumar, R., Lyons, J., Manrai, A., Patel, C., Kohane, I., & Avillach, P. (2020). Scalability and cost-effectiveness analysis of whole genome-wide association studies on Google Cloud Platform and Amazon Web Services. Journal of the American Medical Informatics Association: JAMIA.

  21. Kang, J., Loh, K., Belyayev, L., Cha, P., Sadat, M., Khan, K., Gusev, Y., Bhuvaneshwar, K., Ressom, H., Moturi, S., Kaiser, J., Hawksworth, J., Robson, S. C., Matsumoto, C. S., Zasloff, M., Fishbein, T. M., & Kroemer, A. (2020). Type 3 innate lymphoid cells are associated with a successful intestinal transplant. American Journal of Transplantation: Official Journal of the American Society of Transplantation and the American Society of Transplant Surgeons.

  22. McKerrow, W., Wang, X., Mita, P., Cao, S., Grivainis, M., Ding, L., LaCava, J., Boeke, J., & Fenyö, D. (2020). LINE-1 expression in cancer correlates with DNA damage response, copy number variation, and cell cycle progression. In Cold Spring Harbor Laboratory (p. 2020.06.26.174052).

  23. Srinivasan, S., Kalinava, N., Aldana, R., Li, Z., van Hagen, S., Rodenburg, S. Y. A., Wind-Rotolo, M., Sasson, A. S., Tang, H., Qian, X., & Kirov, S. (2020). Mis-annotated multi nucleotide variants in public cancer genomics datasets can lead to inaccurate mutation calls with significant implications. In Cold Spring Harbor Laboratory (p. 2020.06.05.136549).

  24. Yang, A., Shao, T.-J., Bofill-De Ros, X., Lian, C., Villanueva, P., Dai, L., & Gu, S. (2020). AGO-bound mature miRNAs are oligouridylated by TUTs and subsequently degraded by DIS3L2. Nature Communications, 11(1), 2765. https://doi.org/10.1038/s41467-020-16533-w

  25. Evrard, Y. A., Srivastava, A., Randjelovic, J., Consortium, N. P., Doroshow, J. H., Dean, D. A., Morris, J. S., & Chuang, J. H. (2020). Systematic Establishment of Robustness and Standards in Patient-Derived Xenograft Experiments and Analysis. Cancer Research.

  26. Poore, G. D., Kopylova, E., Zhu, Q., Carpenter, C., Fraraccio, S., Wandro, S., Kosciolek, T., Janssen, S., Metcalf, J., Song, S. J., Kanbar, J., Miller-Montgomery, S., Heaton, R., Mckay, R., Patel, S. P., Swafford, A. D., & Knight, R. (2020). Microbiome analyses of blood and tissues suggest cancer diagnostic approach. Nature, 579(7800), 567–574. https://doi.org/10.1038/s41586-020-2095-1

  27. Chatrath, A., Przanowska, R., Kiran, S., Su, Z., Saha, S., Wilson, B., Tsunematsu, T., Ahn, J.-H., Lee, K. Y., Paulsen, T., Sobierajska, E., Kiran, M., Tang, X., Li, T., Kumar, P., Ratan, A., & Dutta, A. (2020). The pan-cancer landscape of prognostic germline variants in 10,582 patients. Genome Medicine, 12(1), 15. https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-020-0718-7

  28. Domingues, A. F., Kulkarni, R., Giotopoulos, G., Gupta, S., Vinnenberg, L., Arede, L., Foerner, E., Khalili, M., Adao, R. R., Johns, A., Tan, S., Zeka, K., Huntly, B. J., Prabakaran, S., & Pina, C. (2020). Loss of Kat2a enhances transcriptional noise and depletes acute myeloid leukemia stem-like cells. eLife, 9.

  29. Ahlbrandt, J., Lablans, M., Glocker, K., Stahl-Toyota, S., Maier-Hein, K., Maier-Hein, L., & Ückert, F. (2020). Modern Information Technology for Cancer Research: What’s in IT for Me? An Overview of Technologies and Approaches. Oncology, 98(6), 363–369. https://www.karger.com/Article/FullText/493638

  30. Blatti, C., III, Emad, A., Berry, M. J., Gatzke, L., & Epstein, M. (2020). Knowledge-guided analysis of“ omics” data using the KnowEnG cloud platform. PLoS.

  31. Erady, C., Puntambekar, S., & Prabakaran, S. (2020). Use of short-read RNA-Seq data to identify transcripts that can translate novel ORFs. bioRxiv.

  32. Garcia, O. (2020). Prioritization of Evolutionary Events for Immune Response Studies: Introgression, Selection, and Infectious Disease Among Indigenous Americans.

  33. Silva, A., Riera, G., & Fernández Ríos, D. (2020). Cloud computing Applications for biomedical science. Reportes Científicos de La FACEN, 11(1), 39–50. http://scielo.iics.una.py/scielo.php?pid=S2222-145X2020000100039&script=sci_arttext

  34. Zhu, X., Fang, H., Gladysz, K., Barbour, J. A., & Wong, J. W. H. (2020). Overexpression of transposable elements underlies immune overdrive and poor clinical outcome in cancer patients. medRxiv.

  35. Bardadim, T., Gorbachuk, V., Osipenko, S., Novoselova, N., Skobtsov, V., & Minsk, B. (2020). Distribution of functional systems for analysis of biomedical data. Economic and Social-focused Issues of Modern World, 308. http://www.vsemvs.sk/portals/0/Subory/Conference%20Proceedings_%20VSEMvs_November_2020.pdf#page=309

  36. Hung, L.-H., Hu, J., Meiss, T., Ingersoll, A., Lloyd, W., Kristiyanto, D., Xiong, Y., Sobie, E., & Yeung, K. Y. (2019). Building Containerized Workflows Using the BioDepot-Workflow-Builder. Cell Systems, 9(5), 508–514.e3. https://doi.org/10.1016/j.cels.2019.08.007

  37. Dehghannasiri, R., Freeman, D. E., Jordanski, M., Hsieh, G. L., Damljanovic, A., Lehnert, E., & Salzman, J. (2019). Improved detection of gene fusions by applying statistical methods reveals oncogenic RNA cancer drivers. Proceedings of the National Academy of Sciences of the United States of America, 116(31), 15524–15533. https://doi.org/10.1073/pnas.1900391116

  38. Somatic Mutation Working Group Of Seqc2 Consortium, & Xiao, W. (2019). Achieving reproducibility and accuracy in cancer mutation detection with whole-genome and whole-exome sequencing. In Cold Spring Harbor.

  39. Bofill-De Ros, X., Chen, K., Chen, S., Tesic, N., Randjelovic, D., Skundric, N., Nesic, S., Varjacic, V., Williams, E. H., Malhotra, R., Jiang, M., & Gu, S. (2019). QuagmiR: a cloud-based application for isomiR big data analytics. Bioinformatics, 35(9), 1576–1578. https://doi.org/10.1093/bioinformatics/bty843

  40. Chatrath, A., Kiran, M., Kumar, P., Ratan, A., & Dutta, A. (2019). The Germline Variants rs61757955 and rs34988193 Are Predictive of Survival in Lower Grade Glioma Patients. Molecular Cancer Research: MCR, 17(5), 1075–1086. https://doi.org/10.1158/1541-7786.MCR-18-0996

  41. McCoy, M. D., Shivakumar, V., Nimmagadda, S., Jafri, M. S., & Madhavan, S. (2019). SNP2SIM: a modular workflow for standardizing molecular simulation and functional analysis of protein variants. BMC Bioinformatics, 20(1), 171. https://doi.org/10.1186/s12859-019-2774-9

  42. Kaushik, G., & Davis-Dusenbery, B. (2019). Building Portable and Reproducible Cancer Informatics Workflows: An RNA Sequencing Case Study. Methods in Molecular Biology, 1878, 39–64. https://doi.org/10.1007/978-1-4939-8868-6_2

  43. Peri, S., Roberts, S., Kreko, I. R., McHan, L. B., Naron, A., Ram, A., Murphy, R. L., Lyons, E., Gregory, B. D., Devisetty, U. K., & Nelson, A. D. L. (2019). Read Mapping and Transcript Assembly: A Scalable and High-Throughput Workflow for the Processing and Analysis of Ribonucleic Acid Sequencing Data. Frontiers in Genetics, 10, 1361. https://doi.org/10.3389/fgene.2019.01361

  44. Xiang, Y., Ye, Y., Zhang, Z., & Han, L. (2018). Maximizing the Utility of Cancer Transcriptomic Data. Trends in Cancer Research, 4(12), 823–837. https://doi.org/10.1016/j.trecan.2018.09.009

  45. PGP-UK Consortium. (2018). Personal Genome Project UK (PGP-UK): a research and citizen science hybrid project in support of personalized medicine. BMC Medical Genomics, 11(1), 108. https://doi.org/10.1186/s12920-018-0423-1

  46. Liu, Y., He, Q., & Sun, W. (2018). Association analysis using somatic mutations. PLoS Genetics, 14(11), e1007746. https://doi.org/10.1371/journal.pgen.1007746

  47. 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. (2018). Using Semantic Web Technologies to Enable Cancer Genomics Discovery at Petabyte Scale. Cancer Informatics, 17, 1176935118774787. https://doi.org/10.1177/1176935118774787

  48. Heath, A. P., Raman, P., Zhu, Y., Lilly, J. V., Taylor, D., Storm, P. B., Waanders, A. J., Volchenboum, S., Stein, L., Ellrott, K., Margolin, A., Davis-Dusenbery, B., Grossman, R., Ferretti, V., Mueller, S., Nazarian, J., & Resnick, A. C. (2018). TBIO-27. Gabriella Miller Kids First Data Resource Center Advancing Genetic Research in Childhood Cancer and Structural Birth Defects Through Large-scale Integrated Data-driven Discovery and Cloud-based Platforms for Collaborative Analysis. Neuro-Oncology, 20(Suppl 2), i186. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6012831/

  49. Thorsson, V., Gibbs, D. L., Brown, S. D., Wolf, D., Bortone, D. S., Ou Yang, T.-H., Porta-Pardo, E., Gao, G. F., Plaisier, C. L., Eddy, J. A., Ziv, E., Culhane, A. C., Paull, E. O., Sivakumar, I. K. A., Gentles, A. J., Malhotra, R., Farshidfar, F., Colaprico, A., Parker, J. S., … Shmulevich, I. (2018). The Immune Landscape of Cancer. Immunity, 48(4), 812–830.e14. https://pubmed.ncbi.nlm.nih.gov/29628290/

  50. Malhotra, R., Seth, I., Lehnert, E., Zhao, J., Kaushik, G., Williams, E. H., Sethi, A., & Davis-Dusenbery, B. N. (2017). Using the Seven Bridges Cancer Genomics Cloud to Access and Analyze Petabytes of Cancer Data. Current Protocols in Bioinformatics / Editoral Board, Andreas D. Baxevanis ... [et Al.], 60, 11.16.1–11.16.32. https://pubmed.ncbi.nlm.nih.gov/29220078/

  51. Lau, J. W., 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., … Seven Bridges CGC Team. (2017). The Cancer Genomics Cloud: Collaborative, Reproducible, and Democratized-A New Paradigm in Large-Scale Computational Research. Cancer Research, 77(21), e3–e6.

  52. Freeman, D. E., Hsieh, G. L., Howard, J. M., Lehnert, E., & Salzman, J. (2017). Precise, pan-cancer discovery of gene fusions reveals a signature of selection in primary tumors. In bioRxiv (p. 178061).

  53. Lehnert, E. D., Freeman, E., & Salzman, J. (2017). Abstract LB-005: Precise and rapid detection of gene fusions and microbial pathogens in next-generation sequencing data with sequence bloom trees. Cancer Research, 77(13 Supplement), LB – 005 – LB – 005. http://dx.doi.org/10.1158/1538-7445.AM2017-LB-005

  54. Kaushik, G., Onder, Z., Locke, D., Davis-Dusenbery, B., & Kural, D. (2016, October 20). Enabling petabyte-scale genomics in the cloud: Lessons from the NCI Cancer Genomics Cloud Pilots. ASHG, Vancouver, British Columbia. https://cancerres.aacrjournals.org/content/77/13_Supplement/2595.short

  55. Tesic, N. (November 6-9, 2019). QuagmiR: a cloud-based application for isomiR big data analytics. Genome Informatics, Cold Spring Harbor Labs. https://pubmed.ncbi.nlm.nih.gov/30295744/

  56. Williams, E. H., Kaushik, G., Lehnert, E., Malhotra, R., Sethi, A., Onder, Z., & Davis-Dusenbery, B. (Oct 17-21, 2017). Abstract 750: The Seven Bridges Cancer Genomics Cloud: Enabling discovery from petabyte-scale human genomic data resources. ASHG, Orange County Convention Center.

  57. Kaushik, G., Li, Y., Lehnert, E., Onder, Z., Locke, D., Davis-Dusenbery, B. N., & Kural, D. (2017). Abstract 2595: Enabling petabyte-scale cancer genomics with the NCI Cancer Cloud Pilots. Bioinformatics and Systems Biology, 2595–2595. http://cancerres.aacrjournals.org/lookup/doi/10.1158/1538-7445.AM2017-2595