test.bib
... ...
@@ -0,0 +1,31 @@
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+@article{abateDistinctViralMutational2015a,
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+ title = {Distinct {{Viral}} and {{Mutational Spectrum}} of {{Endemic Burkitt Lymphoma}}},
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+ author = {Abate, F. and Ambrosio, M. and Mundo, L. and Laginestra, M. and Fuligni, F. and Rossi, M. and Zairis, Sakellarios and Gazaneo, Sara and Falco, G. De and Lazzi, S. and Bellan, C. and Rocca, B. J. and Amato, T. and Marasco, E. and Etebari, Maryam and Ogwang, M. and Calbi, V. and Ndede, I. and Patel, K. and Chumba, D. and Piccaluga, P. and Pileri, S. and Leoncini, L. and Rabadán, R.},
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+ date = {2015},
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+ journaltitle = {PLoS Pathogens},
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+ shortjournal = {PLoS Pathogens},
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+ volume = {11},
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+ doi = {10.1371/journal.ppat.1005158},
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+ file = {/Users/rmorin/Zotero/storage/8CUFAQ4L/Abate et al. - 2015 - Distinct Viral and Mutational Spectrum of Endemic .pdf}
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+}
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+
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+@article{albuquerqueEnhancingKnowledgeDiscovery2017a,
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+ title = {Enhancing Knowledge Discovery from Cancer Genomics Data with {{Galaxy}}},
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+ author = {Albuquerque, Marco A. and Grande, Bruno M. and Ritch, Elie J. and Pararajalingam, Prasath and Jessa, Selin and Krzywinski, Martin and Grewal, Jasleen K. and Shah, Sohrab P. and Boutros, Paul C. and Morin, Ryan D.},
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+ date = {2017-05-01},
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+ journaltitle = {GigaScience},
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+ shortjournal = {Gigascience},
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+ volume = {6},
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+ number = {5},
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+ eprint = {28327945},
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+ eprinttype = {pmid},
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+ pages = {1--13},
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+ issn = {2047-217X},
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+ doi = {10.1093/gigascience/gix015},
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+ abstract = {The field of cancer genomics has demonstrated the power of massively parallel sequencing techniques to inform on the genes and specific alterations that drive tumor onset and progression. Although large comprehensive sequence data sets continue to be made increasingly available, data analysis remains an ongoing challenge, particularly for laboratories lacking dedicated resources and bioinformatics expertise. To address this, we have produced a collection of Galaxy tools that represent many popular algorithms for detecting somatic genetic alterations from cancer genome and exome data. We developed new methods for parallelization of these tools within Galaxy to accelerate runtime and have demonstrated their usability and summarized their runtimes on multiple cloud service providers. Some tools represent extensions or refinement of existing toolkits to yield visualizations suited to cohort-wide cancer genomic analysis. For example, we present Oncocircos and Oncoprintplus, which generate data-rich summaries of exome-derived somatic mutation. Workflows that integrate these to achieve data integration and visualizations are demonstrated on a cohort of 96 diffuse large B-cell lymphomas and enabled the discovery of multiple candidate lymphoma-related genes. Our toolkit is available from our GitHub repository as Galaxy tool and dependency definitions and has been deployed using virtualization on multiple platforms including Docker.},
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+ langid = {english},
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+ pmcid = {PMC5437943},
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+ keywords = {Algorithms,Cancer,Cloud,Driver,Genome,Genomics,Humans,Internet,Lymphoma,Lymphoma Large B-Cell Diffuse,Mutation,Pipeline,Software,Tool,Workflow},
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+ file = {/Users/rmorin/Zotero/storage/SCLMAU55/Albuquerque et al. - 2017 - Enhancing knowledge discovery from cancer genomics.pdf}
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+}
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+
test.md
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1 1
---
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-bibliography: 'morinlab.bib'
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+bibliography: 'test.bib'
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csl: 'NLM.csl'
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---
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# DLBCL genes
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-@paneaWholeGenomeLandscape2019; @reddyGeneticFunctionalDrivers2017
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+@abateDistinctViralMutational2015a
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+
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+@albuquerqueEnhancingKnowledgeDiscovery2017a
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+
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+
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10 14
# References