A multi-omics digital research object for the genetics of sleep regulation
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Ioannis Xenarios | Paul Franken | Maxime Jan | Nastassia Gobet | Shanaz Diessler | I. Xenarios | P. Franken | Maxime Jan | Nastassia Gobet | S. Diessler
[1] A. Malafosse,et al. Genetic variation in EEG activity during sleep in inbred mice. , 1998, American journal of physiology. Regulatory, integrative and comparative physiology.
[2] P. Franken,et al. Hypocretin (orexin) is critical in sustaining theta/gamma-rich waking behaviors that drive sleep need , 2017, Proceedings of the National Academy of Sciences.
[3] N. Baliga,et al. The State of Systems Genetics in 2017. , 2017, Cell systems.
[4] S. Pradervand,et al. Homer1a is a core brain molecular correlate of sleep loss , 2007, Proceedings of the National Academy of Sciences.
[5] Max Kuhn,et al. caret: Classification and Regression Training , 2015 .
[6] Sarah L Burgess-Herbert,et al. Practical Applications of the Bioinformatics Toolbox for Narrowing Quantitative Trait Loci , 2008, Genetics.
[7] Ioannis Xenarios,et al. FastEpistasis: a high performance computing solution for quantitative trait epistasis , 2010, Bioinform..
[8] Emmanouil T. Dermitzakis,et al. Fast and efficient QTL mapper for thousands of molecular phenotypes , 2015, bioRxiv.
[9] Jesse D. Ziebarth,et al. Segregation of a Spontaneous Klrd1 (CD94) Mutation in DBA/2 Mouse Substrains , 2014, G3: Genes, Genomes, Genetics.
[10] Ruben Verborgh,et al. Developing a framework for digital objects in the Big Data to Knowledge (BD2K) commons: Report from the Commons Framework Pilots workshop , 2017, J. Biomed. Informatics.
[11] Nataša Pržulj,et al. Methods for biological data integration: perspectives and challenges , 2015, Journal of The Royal Society Interface.
[12] E. Lander,et al. Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results , 1995, Nature Genetics.
[13] Kathleen M Jagodnik,et al. Massive mining of publicly available RNA-seq data from human and mouse , 2017, Nature Communications.
[14] Charity W. Law,et al. voom: precision weights unlock linear model analysis tools for RNA-seq read counts , 2014, Genome Biology.
[15] Anton Nekrutenko,et al. Ten Simple Rules for Reproducible Computational Research , 2013, PLoS Comput. Biol..
[16] John P. A. Ioannidis,et al. A manifesto for reproducible science , 2017, Nature Human Behaviour.
[17] K. Broman,et al. A Guide to QTL Mapping with R/qtl , 2009 .
[18] J. Ioannidis,et al. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015–2017 , 2018, PLoS biology.
[19] Emmanouil T. Dermitzakis,et al. Fast and efficient QTL mapper for thousands of molecular phenotypes , 2015 .
[20] Alban Gaignard,et al. Scientific workflows for computational reproducibility in the life sciences: Status, challenges and opportunities , 2017, Future Gener. Comput. Syst..
[21] P. Bork,et al. A method and server for predicting damaging missense mutations , 2010, Nature Methods.
[22] G. Buzsáki. Theta Oscillations in the Hippocampus , 2002, Neuron.
[23] Denis Torre,et al. BioJupies: Automated Generation of Interactive Notebooks for RNA-Seq Data Analysis in the Cloud. , 2018, Cell systems.
[24] M. Robinson,et al. A scaling normalization method for differential expression analysis of RNA-seq data , 2010, Genome Biology.
[25] Morris A. Swertz,et al. Bioinformatics tools and database resources for systems genetics analysis in mice—a short review and an evaluation of future needs , 2011, Briefings Bioinform..
[26] Jing Wang,et al. CrossMap: a versatile tool for coordinate conversion between genome assemblies , 2014, Bioinform..
[27] D. Skene,et al. Twenty-four-hour rhythmicity of circulating metabolites: effect of body mass and type 2 diabetes , 2017, FASEB journal : official publication of the Federation of American Societies for Experimental Biology.
[28] Robert W. Williams,et al. Systems genetics identifies Hp1bp3 as a novel modulator of cognitive aging , 2016, Neurobiology of Aging.
[29] Daniel J. Gaffney,et al. A survey of best practices for RNA-seq data analysis , 2016, Genome Biology.
[30] Ben Baumer,et al. R Markdown: Integrating A Reproducible Analysis Tool into Introductory Statistics , 2014, 1402.1894.
[31] Ruben Verborgh,et al. Interoperability and FAIRness through a novel combination of Web technologies , 2017, PeerJ Prepr..
[32] Ning Jiang,et al. Our path to better science in less time using open data science tools , 2017, Nature Ecology &Evolution.
[33] M. DePristo,et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. , 2010, Genome research.
[34] Inanç Birol,et al. Hive plots - rational approach to visualizing networks , 2012, Briefings Bioinform..
[35] Florence I. Raynaud,et al. Effect of sleep deprivation on the human metabolome , 2014, Proceedings of the National Academy of Sciences.
[36] H. Hakonarson,et al. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data , 2010, Nucleic acids research.
[37] Mauricio O. Carneiro,et al. From FastQ Data to High‐Confidence Variant Calls: The Genome Analysis Toolkit Best Practices Pipeline , 2013, Current protocols in bioinformatics.
[38] Paul Theodor Pyl,et al. HTSeq—a Python framework to work with high-throughput sequencing data , 2014, bioRxiv.
[39] Yihui Xie,et al. knitr: A Comprehensive Tool for Reproducible Research in R , 2018, Implementing Reproducible Research.
[40] Thomas R. Gingeras,et al. STAR: ultrafast universal RNA-seq aligner , 2013, Bioinform..
[41] L. Ryan. Characterization of cortical spindles in DBA/2 and C57BL/6 inbred mice , 1984, Brain Research Bulletin.
[42] Paul Franken,et al. Sleep and EEG Phenotyping in Mice. , 2012, Current protocols in mouse biology.
[43] B. Thorens,et al. A Genetic Screen Identifies Hypothalamic Fgf15 as a Regulator of Glucagon Secretion , 2016, Cell reports.
[44] M. DePristo,et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data , 2011, Nature Genetics.
[45] Carole A. Goble,et al. Why Linked Data is Not Enough for Scientists , 2010, 2010 IEEE Sixth International Conference on e-Science.
[46] Lior Pachter,et al. Near-optimal probabilistic RNA-seq quantification , 2016, Nature Biotechnology.
[47] Robert W. Williams,et al. Systems Genetics of Metabolism: The Use of the BXD Murine Reference Panel for Multiscalar Integration of Traits , 2012, Cell.
[48] Robert W. Williams,et al. A new set of BXD recombinant inbred lines from advanced intercross populations in mice , 2004, BMC Genetics.
[49] A. Lusis,et al. Systems genetics approaches to understand complex traits , 2013, Nature Reviews Genetics.
[50] Anne E. Trefethen,et al. Toward interoperable bioscience data , 2012, Nature Genetics.
[51] E. Birney,et al. Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt , 2009, Nature Protocols.
[52] Nicole A. Vasilevsky,et al. Reproducible and reusable research: are journal data sharing policies meeting the mark? , 2017, PeerJ.
[53] James Taylor,et al. Next-generation sequencing data interpretation: enhancing reproducibility and accessibility , 2012, Nature Reviews Genetics.
[54] N. Guex,et al. A systems genetics resource and analysis of sleep regulation in the mouse , 2018, PLoS biology.
[55] D. Welsh,et al. A circadian rhythm of hippocampal theta activity in the mouse , 1985, Physiology & Behavior.
[56] M. Hallschmid,et al. The metabolic burden of sleep loss. , 2015, The lancet. Diabetes & endocrinology.
[57] Matthew E. Ritchie,et al. limma powers differential expression analyses for RNA-sequencing and microarray studies , 2015, Nucleic acids research.
[58] Ana Sofia Figueiredo,et al. Data Sharing: Convert Challenges into Opportunities , 2017, Front. Public Health.