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Influenza Diallel Analysis
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README.md

README.md

flu-diallel

Summary

This respository contains data and code required to reproduce analysis for an infection diallel, using influenza A virus (H1N1) in inbred and F1 mice (n=1,043). The title for this project is: "Bayesian diallel analysis reveals Mx1-dependent and Mx1-independent effects on response to influenza A virus in mice". Our manuscript has been published in G3: http://www.g3journal.org/content/8/2/427.

This repository may be updated post-publication. A static version of the data, software, and scripts used to analyze this data is available at DOI: 10.5281/zenodo.293015.

Presentation

Learn more about this study via slides I presented at the Complex Trait Community Meeting in Memphis, TN (June 16, 2017): CTC-2017-Maurizio.

Data Sets

  1. FluDiData.csv

  2. Flu-preCC-data.csv

  3. Flu-CC-RIX-data.csv

Software

  1. BayesDiallel http://valdarlab.unc.edu/software/bayesdiallel/BayesDiallel.html

  2. Diploffect http://valdarlab.unc.edu/software/diploffect/index.html

  3. treatmentResponseDiallel https://github.com/mauriziopaul/treatmentResponseDiallel

More Information

For more information about my research interests, please visit https://mauriziopaul.github.io/. To learn more about research in the Heise and Valdar labs, please visit and https://unclineberger.org/people/mark-heise and http://valdarlab.unc.edu.

Key References

Maurizio PL, Ferris MT, Keele GR, Miller DR, Shaw GD, Whitmore AC, West A, Morrison CR, Noll KE, Plante KS, Cockrell AS, Threadgill DW, Pardo-Manuel de Villena F, Baric RS, Heise MT & Valdar W (2018) Bayesian diallel analysis reveals Mx1-dependent and Mx1-independent effects on response to influenza A virus in mice. G3: Genes, Genomes, Genetics 8(2):427-445. 10.1534/g3.117.300438. PMID:29187420.

Maurizio PL & Ferris MT (2017) “Chapter 28: The Collaborative Cross Resource for Systems Genetics Research of Infectious Diseases.” Methods in Molecular Biology: Systems Genetics – Methods and Protocols. Springer Science+Business Media, New York, NY. Klaus Schughart and Robert W. Williams (eds.) 1488:579-596. eBook ISBN: 978-1-4939-6427-7, hardcover ISBN: 978-1-4939-6425-3. doi: 10.1007/978-1-4939-6427-7_28

Zhang Z, Wang W & Valdar W (2014) Bayesian modeling of haplotype effects in multiparent populations. Genetics 198(1):139-56. doi: 10.1534/genetics.114.166249

Crowley JJ, Kim Y, Lenarcic AB, Quackenbush CR, Barrick C, Adkins DE, Shaw GS, Miller DR, Pardo Manuel de Villena F, Sullivan PF & Valdar W (2014) Genetics of adverse reactions to haloperidol in a mouse diallel: A drug-placebo experiment and Bayesian causal analysis. Genetics 196(1):321-47. doi: 10.1534/genetics.113.156901

Ferris MT, Aylor DL, Bottomly D, Whitmore AC, Aicher LD, Bell TA, Bradel-Tretheway B, Bryan JT, Buus RJ, Gralinski LE, Haagmans BL, McMillan L, Miller DR, Rosenzweig E, Valdar W, Wang J, Churchill GA, Threadgill DW, McWeeney SK, Katze MG, Pardo-Manuel de Villena F, Baric RS & Heise MT (2013) Modeling host genetic regulation of influenza pathogenesis in the Collaborative Cross. PLoS Pathogens 9(2):e1003196. doi: 10.1371/journal.ppat.1003196

Lenarcic AB, Svenson KL, Churchill GA & Valdar W (2012) A general Bayesian approach to analyzing diallel crosses of inbred strains. Genetics 190:413-435. doi: 10.1534/genetics.111.132563

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