Identifying atypically expressed chromosome regions using RNA-Seq data
Author
Abstract
Suggested Citation
DOI: 10.1007/s10260-019-00496-4
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Bivand, Roger & Piras, Gianfranco, 2015.
"Comparing Implementations of Estimation Methods for Spatial Econometrics,"
Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i18).
- Roger Bivand & Gianfranco Piras, 2013. "Comparing Implementations of Estimation Methods for Spatial Econometrics," Working Papers Working Paper 2013-01, Regional Research Institute, West Virginia University.
- Lewin Alex & Bochkina Natalia & Richardson Sylvia, 2007. "Fully Bayesian Mixture Model for Differential Gene Expression: Simulations and Model Checks," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 6(1), pages 1-28, December.
- Kim‐Anh Do & Peter Müller & Feng Tang, 2005. "A Bayesian mixture model for differential gene expression," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(3), pages 627-644, June.
- Panagiotis Papastamoulis & Magnus Rattray, 2018. "A Bayesian model selection approach for identifying differentially expressed transcripts from RNA sequencing data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(1), pages 3-23, January.
- Christopher A. Maher & Chandan Kumar-Sinha & Xuhong Cao & Shanker Kalyana-Sundaram & Bo Han & Xiaojun Jing & Lee Sam & Terrence Barrette & Nallasivam Palanisamy & Arul M. Chinnaiyan, 2009. "Transcriptome sequencing to detect gene fusions in cancer," Nature, Nature, vol. 458(7234), pages 97-101, March.
- Vinícius Diniz Mayrink & Flávio Bambirra Gonçalves, 2017. "A Bayesian hidden Markov mixture model to detect overexpressed chromosome regions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(2), pages 387-412, February.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Vinícius Diniz Mayrink & Flávio Bambirra Gonçalves, 2017. "A Bayesian hidden Markov mixture model to detect overexpressed chromosome regions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(2), pages 387-412, February.
- Guohuan Su & Adam Mertel & Sébastien Brosse & Justin M. Calabrese, 2023. "Species invasiveness and community invasibility of North American freshwater fish fauna revealed via trait-based analysis," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
- Kuschnig, Nikolas, 2021.
"Bayesian Spatial Econometrics and the Need for Software,"
Department of Economics Working Paper Series
318, WU Vienna University of Economics and Business.
- Nikolas Kuschnig, 2021. "Bayesian Spatial Econometrics and the Need for Software," Department of Economics Working Papers wuwp318, Vienna University of Economics and Business, Department of Economics.
- Chakir, Raja & Lungarska, Anna, 2015. "Agricultural land rents in land use models: a spatial econometric analysis," 150th Seminar, October 22-23, 2015, Edinburgh, Scotland 212641, European Association of Agricultural Economists.
- Marcos-Martinez, Raymundo & Measham, Thomas G. & Fleming-Muñoz, David A., 2019. "Economic impacts of early unconventional gas mining: Lessons from the coal seam gas industry in New South Wales, Australia," Energy Policy, Elsevier, vol. 125(C), pages 338-346.
- Meilan An & Jeffrey Vitale & Kwideok Han & John N. Ng’ombe & Inbae Ji, 2021. "Effects of Spatial Characteristics on the Spread of the Highly Pathogenic Avian Influenza (HPAI) in Korea," IJERPH, MDPI, vol. 18(8), pages 1-13, April.
- Demidova, Olga, 2021. "Methods of spatial econometrics and evaluation of government programs effectiveness," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 64, pages 107-134.
- Biarnès, Anne & Bailly, Jean-Stéphane & Mekki, Insaf & Ferchichi, Intissar, 2021. "Land use mosaics in Mediterranean rainfed agricultural areas as an indicator of collective crop successions: Insights from a land use time series study conducted in Cap Bon, Tunisia," Agricultural Systems, Elsevier, vol. 194(C).
- Iacopo Odoardi & Donatella Furia & Piera Cascioli, 2021. "Can social support compensate for missing family support? An examination of dropout rates in Italy," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(1), pages 121-139, February.
- Ozgun, Burcu & Broekel, Tom, 2021.
"The geography of innovation and technology news - An empirical study of the German news media,"
Technological Forecasting and Social Change, Elsevier, vol. 167(C).
- Burcu Ozgun & Tom Broekel, 2021. "The geography of innovation and technology news - An empirical study of the German news media," Papers in Evolutionary Economic Geography (PEEG) 2110, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Mar 2021.
- Han, Bing & Dalal, Siddhartha R., 2012. "A Bernstein-type estimator for decreasing density with application to p-value adjustments," Computational Statistics & Data Analysis, Elsevier, vol. 56(2), pages 427-437.
- Pinto, Allan & Griffin, Terry W., 2022. "Detecting bubbles via single time-series variable: applying spatial specification tests to farmland values," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322534, Agricultural and Applied Economics Association.
- Jan Paul Baginski & Christoph Weber, "undated". "Coherent estimations for residential photovoltaic uptake in Germany including spatial spillover effects," EWL Working Papers 1902, University of Duisburg-Essen, Chair for Management Science and Energy Economics.
- Gianfranco Piras & Mauricio Sarrias, 2023. "Heterogeneous spatial models in R: spatial regimes models," Journal of Spatial Econometrics, Springer, vol. 4(1), pages 1-32, December.
- Wang Chamont & Gevertz Jana L., 2016. "Finding causative genes from high-dimensional data: an appraisal of statistical and machine learning approaches," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 15(4), pages 321-347, August.
- Kandt, Jens & Leak, Alistair, 2019. "Examining inclusive mobility through smartcard data: What shall we make of senior citizens' declining bus patronage in the West Midlands?," Journal of Transport Geography, Elsevier, vol. 79(C), pages 1-1.
- Paola Cardamone, 2018. "Firm innovation and spillovers in Italy: Does geographical proximity matter?," Letters in Spatial and Resource Sciences, Springer, vol. 11(1), pages 1-16, March.
- Alfo' Marco & Farcomeni Alessio & Tardella Luca, 2011. "A Three Component Latent Class Model for Robust Semiparametric Gene Discovery," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-19, January.
- Mauricio R. Bellon & Alicia Mastretta-Yanes & Alejandro Ponce-Mendoza & Daniel Ortiz-Santa María & Oswaldo Oliveros-Galindo & Hugo Perales & Francisca Acevedo & José Sarukhán, 2021. "Beyond subsistence: the aggregate contribution of campesinos to the supply and conservation of native maize across Mexico," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 13(1), pages 39-53, February.
- Bivand, Roger & Piras, Gianfranco, 2015.
"Comparing Implementations of Estimation Methods for Spatial Econometrics,"
Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i18).
- Roger Bivand & Gianfranco Piras, 2013. "Comparing Implementations of Estimation Methods for Spatial Econometrics," Working Papers Working Paper 2013-01, Regional Research Institute, West Virginia University.
More about this item
Keywords
Bayesian inference; Mixture model; Gibbs sampling; Gene expression; Cancer;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:stmapp:v:29:y:2020:i:3:d:10.1007_s10260-019-00496-4. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.